## SMD 95%-CI %W(fixed) %W(random)
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Bækkerud 2016 0.3799 [0.2229; 0.5370] < 0.0001 0.1147 0.3387 41.3%
## Omitting Beetham 2019 0.3963 [0.2424; 0.5503] < 0.0001 0.1048 0.3238 39.2%
## Omitting Burgomaster 2008 0.3960 [0.2406; 0.5513] < 0.0001 0.1083 0.3290 39.8%
## Omitting Ciolac 2010 0.3749 [0.2183; 0.5316] < 0.0001 0.1127 0.3357 40.8%
## Omitting Cocks 2013 0.3979 [0.2440; 0.5518] < 0.0001 0.1040 0.3225 38.9%
## Omitting Conraads 2015 0.3922 [0.2300; 0.5543] < 0.0001 0.1250 0.3536 40.3%
## Omitting Currie 2015 0.3805 [0.2233; 0.5378] < 0.0001 0.1151 0.3393 41.3%
## Omitting Earnest 2013 0.3959 [0.2390; 0.5527] < 0.0001 0.1109 0.3331 40.0%
## Omitting Fisher 2015 0.4048 [0.2537; 0.5559] < 0.0001 0.0934 0.3057 36.3%
## Omitting Gillen 2016 0.3973 [0.2426; 0.5520] < 0.0001 0.1061 0.3257 39.3%
## Omitting Gorostiaga 1991 0.3718 [0.2175; 0.5262] < 0.0001 0.1070 0.3270 39.7%
## Omitting Grieco 2013 0.3788 [0.2215; 0.5361] < 0.0001 0.1148 0.3388 41.2%
## Omitting Helgerud 2007 0.3715 [0.2159; 0.5271] < 0.0001 0.1093 0.3307 40.1%
## Omitting Helgerud 2007 0.3737 [0.2175; 0.5298] < 0.0001 0.1114 0.3338 40.5%
## Omitting Henriksson 1976 0.3921 [0.2373; 0.5469] < 0.0001 0.1088 0.3298 40.2%
## Omitting Honkala 2017 (Healthy) 0.3727 [0.2161; 0.5293] < 0.0001 0.1117 0.3342 40.4%
## Omitting Honkala 2017 (T2D) 0.3660 [0.2138; 0.5182] < 0.0001 0.0993 0.3150 37.9%
## Omitting Keating 2014 0.3848 [0.2272; 0.5424] < 0.0001 0.1157 0.3402 41.4%
## Omitting Keteyian 2014 0.3767 [0.2192; 0.5341] < 0.0001 0.1144 0.3383 41.0%
## Omitting Kim 2015 0.3711 [0.2149; 0.5273] < 0.0001 0.1102 0.3319 40.1%
## Omitting Klonizakis 2014 0.3869 [0.2298; 0.5440] < 0.0001 0.1147 0.3387 41.3%
## Omitting Lunt 2014 0.3719 [0.2160; 0.5278] < 0.0001 0.1101 0.3318 40.2%
## Omitting Lunt 2014 0.3791 [0.2218; 0.5365] < 0.0001 0.1150 0.3391 41.2%
## Omitting Macpherson 2011 0.3911 [0.2344; 0.5479] < 0.0001 0.1129 0.3360 40.8%
## Omitting Madssen 2014 0.3783 [0.2201; 0.5364] < 0.0001 0.1159 0.3405 41.1%
## Omitting Martins 2016 0.3937 [0.2367; 0.5507] < 0.0001 0.1122 0.3350 40.4%
## Omitting Matsuo 2014 0.3762 [0.2189; 0.5334] < 0.0001 0.1140 0.3376 40.9%
## Omitting Matsuo 2015 0.3729 [0.2165; 0.5293] < 0.0001 0.1113 0.3337 40.4%
## Omitting Mitranun 2014 0.3691 [0.2135; 0.5246] < 0.0001 0.1080 0.3287 39.6%
## Omitting Molmen-Hansen 2011 0.3721 [0.2141; 0.5302] < 0.0001 0.1136 0.3371 40.2%
## Omitting Motiani 2017 0.3814 [0.2235; 0.5392] < 0.0001 0.1160 0.3406 41.3%
## Omitting Nalcakan 2014 0.3931 [0.2374; 0.5487] < 0.0001 0.1102 0.3320 40.3%
## Omitting Nie 2017 0.3896 [0.2318; 0.5473] < 0.0001 0.1151 0.3393 41.1%
## Omitting O’Leary 2018 0.3911 [0.2344; 0.5478] < 0.0001 0.1129 0.3361 40.8%
## Omitting Ramos 2016a 0.3732 [0.2156; 0.5308] < 0.0001 0.1134 0.3368 40.5%
## Omitting Ramos 2016b 0.3705 [0.2142; 0.5268] < 0.0001 0.1100 0.3317 40.0%
## Omitting Robinson 2015 0.3943 [0.2369; 0.5517] < 0.0001 0.1127 0.3358 40.4%
## Omitting Rognmo 2004 0.3788 [0.2219; 0.5356] < 0.0001 0.1143 0.3381 41.2%
## Omitting Sandvei 2012 0.3862 [0.2286; 0.5439] < 0.0001 0.1156 0.3400 41.3%
## Omitting Sawyer 2016 0.3837 [0.2264; 0.5410] < 0.0001 0.1154 0.3397 41.4%
## Omitting Scribbans 2014 0.3923 [0.2359; 0.5486] < 0.0001 0.1119 0.3344 40.6%
## Omitting Shepherd 2013 0.3979 [0.2440; 0.5518] < 0.0001 0.1040 0.3225 38.9%
## Omitting Sjöros 2018 0.3761 [0.2193; 0.5330] < 0.0001 0.1134 0.3367 40.9%
## Omitting Skleryk 2013 0.3916 [0.2354; 0.5478] < 0.0001 0.1118 0.3344 40.7%
## Omitting Tjønna 2008 0.3714 [0.2160; 0.5267] < 0.0001 0.1089 0.3300 40.0%
## Omitting Trapp 2008 0.3845 [0.2263; 0.5427] < 0.0001 0.1166 0.3414 41.4%
## Omitting Winn 2018 0.3930 [0.2372; 0.5488] < 0.0001 0.1105 0.3325 40.4%
## Omitting Wisløff 2007 0.3585 [0.2220; 0.4950] < 0.0001 0.0513 0.2264 24.1%
##
## Pooled estimate 0.4017 [0.2381; 0.5653] < 0.0001 0.1456 0.3816 47.1%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.4017 [ 0.2381; 0.5653] Overall
## Healthy 0.2461 [ 0.0354; 0.4568] Population
## Overweight/obese 0.1786 [-0.1067; 0.4640] Population
## Cardiac Rehabilitation 0.7734 [ 0.2385; 1.3082] Population
## Metabolic Syndrome 0.6192 [ 0.2461; 0.9922] Population
## T2D 1.0085 [ 0.4805; 1.5365] Population
## < 30 y 0.1405 [-0.1045; 0.3855] Age
## 30 - 50 y 0.4251 [ 0.1858; 0.6644] Age
## > 50 y 0.6006 [ 0.3120; 0.8892] Age
## < 5 weeks 0.4000 [ 0.0756; 0.7244] Training Duration
## 5 - 10 weeks 0.2799 [ 0.0420; 0.5178] Training Duration
## > 10 weeks 0.4893 [ 0.2237; 0.7549] Training Duration
## < 0.5 0.4651 [ 0.1920; 0.7382] Men Ratio
## > 0.5 0.3426 [ 0.1539; 0.5313] Men Ratio
## Running 0.6490 [ 0.4087; 0.8893] Type of Exercise
## Cycling 0.1894 [ 0.0189; 0.3598] Type of Exercise
## < 30% 0.4076 [ 0.2175; 0.5977] Baseline Values
## 30 - 60% 0.2537 [-0.0956; 0.6030] Baseline Values
## > 60% 0.4704 [ 0.0077; 0.9330] Baseline Values
## HIIT 0.4978 [ 0.3119; 0.6837] Type of HIIE
## SIT 0.1794 [-0.0802; 0.4390] Type of HIIE
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456; tau = 0.3816; I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Population 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Age 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Training Duration 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Men Ratio 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Type of Exercise 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Baseline Values 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
## Type of HIIE 48 0.4017 [0.2381; 0.5653] 0.1456 0.3816 88.86 47.1%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 Overweight/obese
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 Overweight/obese
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 Healthy
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 Healthy
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 Healthy
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 Cardiac Rehabilitation
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 Cardiac Rehabilitation
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 Overweight/obese
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 Overweight/obese
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 Healthy
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 Healthy
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 Healthy
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 Healthy
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 Healthy
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 Healthy
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 Healthy
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 T2D
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 Overweight/obese
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 Cardiac Rehabilitation
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 Cardiac Rehabilitation
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 Healthy
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 Overweight/obese
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 Overweight/obese
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 Healthy
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 Cardiac Rehabilitation
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 Overweight/obese
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 Healthy
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 Metabolic Syndrome
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 T2D
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 Overweight/obese
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 Healthy
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 Healthy
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 Healthy
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 Healthy
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 Metabolic Syndrome
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 Metabolic Syndrome
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 Metabolic Syndrome
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 Cardiac Rehabilitation
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 Healthy
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 Overweight/obese
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 Healthy
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 Healthy
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 T2D
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 Overweight/obese
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 Metabolic Syndrome
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 Healthy
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 Overweight/obese
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 Cardiac Rehabilitation
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 36.0% [7.5%; 55.7%]; H = 1.25 [1.04; 1.50]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 21 0.2504 [ 0.0570; 0.4439] 23.47 14.8%
## Overweight/obese 12 0.2063 [-0.0270; 0.4396] 15.67 29.8%
## Cardiac Rehabilitation 7 0.4372 [ 0.2096; 0.6647] 21.47 72.1%
## Metabolic Syndrome 5 0.6018 [ 0.2771; 0.9266] 5.15 22.3%
## T2D 3 1.0085 [ 0.4805; 1.5365] 1.44 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 11.26 4 0.0238
## Within groups 67.21 43 0.0105
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 21 0.2461 [ 0.0354; 0.4568] 0.0357 0.1889
## Overweight/obese 12 0.1786 [-0.1067; 0.4640] 0.0738 0.2717
## Cardiac Rehabilitation 7 0.7734 [ 0.2385; 1.3082] 0.3336 0.5776
## Metabolic Syndrome 5 0.6192 [ 0.2461; 0.9922] 0.0405 0.2012
## T2D 3 1.0085 [ 0.4805; 1.5365] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 12.56 4 0.0136
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1359 (SE = 0.0690)
## tau (square root of estimated tau^2 value): 0.3686
## I^2 (residual heterogeneity / unaccounted variability): 43.71%
## H^2 (unaccounted variability / sampling variability): 1.78
## R^2 (amount of heterogeneity accounted for): 6.68%
##
## Test for Residual Heterogeneity:
## QE(df = 43) = 76.3860, p-val = 0.0013
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 10.8469, p-val = 0.0283
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2487 0.1283 1.9377 0.0527 -0.0029 0.5002 .
## .byvarOverweight/obese -0.0757 0.2077 -0.3645 0.7155 -0.4827 0.3313
## .byvarCardiac Rehabilitation 0.4675 0.2426 1.9271 0.0540 -0.0080 0.9430 .
## .byvarMetabolic Syndrome 0.4132 0.2692 1.5351 0.1248 -0.1144 0.9407
## .byvarT2D 0.8365 0.3683 2.2713 0.0231 0.1147 1.5583 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 30 - 50 y
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 > 50 y
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 < 30 y
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 < 30 y
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 < 30 y
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 > 50 y
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 > 50 y
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 30 - 50 y
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 < 30 y
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 < 30 y
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 < 30 y
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 < 30 y
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 < 30 y
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 < 30 y
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 < 30 y
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 30 - 50 y
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 30 - 50 y
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 30 - 50 y
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 > 50 y
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 > 50 y
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 > 50 y
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 30 - 50 y
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 30 - 50 y
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 < 30 y
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 > 50 y
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 30 - 50 y
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 < 30 y
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 30 - 50 y
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 > 50 y
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 > 50 y
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 30 - 50 y
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 < 30 y
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 < 30 y
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 < 30 y
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 > 50 y
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 > 50 y
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 > 50 y
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 > 50 y
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 < 30 y
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 30 - 50 y
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 < 30 y
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 < 30 y
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 30 - 50 y
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 30 - 50 y
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 > 50 y
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 < 30 y
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 30 - 50 y
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 > 50 y
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 37.5% [10.5%; 56.3%]; H = 1.26 [1.06; 1.51]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 19 0.1453 [-0.0602; 0.3509] 25.13 28.4%
## 30 - 50 y 14 0.4194 [ 0.1920; 0.6469] 14.28 9.0%
## > 50 y 15 0.4845 [ 0.3141; 0.6548] 32.56 57.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 6.50 2 0.0388
## Within groups 71.97 45 0.0065
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 19 0.1405 [-0.1045; 0.3855] 0.0831 0.2883
## 30 - 50 y 14 0.4251 [ 0.1858; 0.6644] 0.0187 0.1369
## > 50 y 15 0.6006 [ 0.3120; 0.8892] 0.1644 0.4054
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 6.03 2 0.0492
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1149 (SE = 0.0614)
## tau (square root of estimated tau^2 value): 0.3390
## I^2 (residual heterogeneity / unaccounted variability): 40.88%
## H^2 (unaccounted variability / sampling variability): 1.69
## R^2 (amount of heterogeneity accounted for): 21.09%
##
## Test for Residual Heterogeneity:
## QE(df = 46) = 77.8116, p-val = 0.0023
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 10.6036, p-val = 0.0011
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.3055 0.2307 -1.3240 0.1855 -0.7576 0.1467
## age 0.0169 0.0052 3.2563 0.0011 0.0067 0.0271 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 5 - 10 weeks
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 > 10 weeks
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 5 - 10 weeks
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 > 10 weeks
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 5 - 10 weeks
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 > 10 weeks
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 > 10 weeks
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 5 - 10 weeks
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 5 - 10 weeks
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 > 10 weeks
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 5 - 10 weeks
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 < 5 weeks
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 5 - 10 weeks
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 5 - 10 weeks
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 5 - 10 weeks
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 < 5 weeks
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 < 5 weeks
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 > 10 weeks
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 5 - 10 weeks
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 5 - 10 weeks
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 < 5 weeks
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 > 10 weeks
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 > 10 weeks
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 5 - 10 weeks
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 > 10 weeks
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 > 10 weeks
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 5 - 10 weeks
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 5 - 10 weeks
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 5 - 10 weeks
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 > 10 weeks
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 < 5 weeks
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 5 - 10 weeks
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 > 10 weeks
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 5 - 10 weeks
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 > 10 weeks
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 > 10 weeks
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 < 5 weeks
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 5 - 10 weeks
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 5 - 10 weeks
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 5 - 10 weeks
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 5 - 10 weeks
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 5 - 10 weeks
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 < 5 weeks
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 < 5 weeks
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 > 10 weeks
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 > 10 weeks
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 < 5 weeks
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 > 10 weeks
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 41.8% [17.2%; 59.2%]; H = 1.31 [1.10; 1.56]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 9 0.3875 [0.1030; 0.6720] 10.15 21.2%
## 5 - 10 weeks 22 0.2850 [0.0957; 0.4743] 32.45 35.3%
## > 10 weeks 17 0.4167 [0.2528; 0.5807] 34.77 54.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.09 2 0.5793
## Within groups 77.38 45 0.0019
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 9 0.4000 [0.0756; 0.7244] 0.0518 0.2277
## 5 - 10 weeks 22 0.2799 [0.0420; 0.5178] 0.1124 0.3353
## > 10 weeks 17 0.4893 [0.2237; 0.7549] 0.1507 0.3882
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.34 2 0.5104
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1424 (SE = 0.0685)
## tau (square root of estimated tau^2 value): 0.3774
## I^2 (residual heterogeneity / unaccounted variability): 46.30%
## H^2 (unaccounted variability / sampling variability): 1.86
## R^2 (amount of heterogeneity accounted for): 2.20%
##
## Test for Residual Heterogeneity:
## QE(df = 46) = 85.6575, p-val = 0.0003
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 2.3382, p-val = 0.1262
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1407 0.1897 0.7420 0.4581 -0.2310 0.5125
## duration 0.0301 0.0197 1.5291 0.1262 -0.0085 0.0686
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 < 0.5
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 > 0.5
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 < 0.5
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 < 0.5
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 > 0.5
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 > 0.5
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 > 0.5
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 > 0.5
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 > 0.5
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 > 0.5
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 < 0.5
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 < 0.5
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 > 0.5
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 > 0.5
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 > 0.5
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 > 0.5
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 > 0.5
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 < 0.5
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 > 0.5
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 > 0.5
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 < 0.5
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 < 0.5
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 < 0.5
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 > 0.5
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 > 0.5
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 < 0.5
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 > 0.5
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 > 0.5
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 < 0.5
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 > 0.5
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 > 0.5
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 > 0.5
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 < 0.5
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 > 0.5
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 > 0.5
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 > 0.5
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 < 0.5
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 > 0.5
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 < 0.5
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 < 0.5
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 > 0.5
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 > 0.5
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 > 0.5
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 > 0.5
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 < 0.5
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 < 0.5
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 < 0.5
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 < 0.5
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 41.1% [16.4%; 58.5%]; H = 1.30 [1.09; 1.55]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 19 0.4114 [0.2140; 0.6087] 33.14 45.7%
## > 0.5 29 0.3414 [0.2025; 0.4804] 45.00 37.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.32 1 0.5701
## Within groups 78.15 46 0.0022
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 19 0.4651 [0.1920; 0.7382] 0.1632 0.4040
## > 0.5 29 0.3426 [0.1539; 0.5313] 0.0922 0.3037
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.52 1 0.4693
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1477 (SE = 0.0697)
## tau (square root of estimated tau^2 value): 0.3844
## I^2 (residual heterogeneity / unaccounted variability): 47.21%
## H^2 (unaccounted variability / sampling variability): 1.89
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 46) = 87.1306, p-val = 0.0002
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.3509, p-val = 0.2451
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.5981 0.1885 3.1722 0.0015 0.2286 0.9677 **
## men_ratio -0.3022 0.2600 -1.1623 0.2451 -0.8119 0.2074
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 Running
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 Running
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 Cycling
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 Running
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 Cycling
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 Cycling
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 Cycling
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 Running
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 Cycling
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 Cycling
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 Cycling
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 Cycling
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 Running
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 Running
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 Cycling
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 Cycling
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 Cycling
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 Cycling
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 Running
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 Running
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 Cycling
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 Running
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 Running
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 Cycling
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 Running
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 Cycling
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 Cycling
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 Cycling
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 Running
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 Running
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 Cycling
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 Cycling
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 Cycling
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 Cycling
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 Running
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 Running
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 Cycling
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 Running
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 Running
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 Cycling
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 Cycling
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 Cycling
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 Cycling
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 Cycling
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 Running
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 Cycling
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 Running
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 Running
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 28.7% [0.0%; 50.5%]; H = 1.18 [1.00; 1.42]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 20 0.6330 [0.4521; 0.8139] 31.77 40.2%
## Cycling 28 0.1898 [0.0438; 0.3358] 32.74 17.5%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 13.96 1 0.0002
## Within groups 64.51 46 0.0371
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 20 0.6490 [0.4087; 0.8893] 0.1159 0.3404
## Cycling 28 0.1894 [0.0189; 0.3598] 0.0346 0.1861
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 9.35 1 0.0022
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0998 (SE = 0.0577)
## tau (square root of estimated tau^2 value): 0.3159
## I^2 (residual heterogeneity / unaccounted variability): 37.56%
## H^2 (unaccounted variability / sampling variability): 1.60
## R^2 (amount of heterogeneity accounted for): 31.48%
##
## Test for Residual Heterogeneity:
## QE(df = 46) = 73.6718, p-val = 0.0059
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 9.3390, p-val = 0.0022
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1981 0.1013 1.9543 0.0507 -0.0006 0.3967 .
## type_exerciseRunning 0.4769 0.1561 3.0560 0.0022 0.1710 0.7827 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 30 - 60%
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 < 30%
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 30 - 60%
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 < 30%
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 30 - 60%
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 < 30%
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 < 30%
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 < 30%
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 < 30%
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 < 30%
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 30 - 60%
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 < 30%
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 > 60%
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 > 60%
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 > 60%
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 < 30%
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 < 30%
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 < 30%
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 < 30%
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 < 30%
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 < 30%
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 < 30%
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 < 30%
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 30 - 60%
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 < 30%
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 < 30%
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 30 - 60%
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 < 30%
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 < 30%
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 30 - 60%
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 < 30%
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 < 30%
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 < 30%
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 30 - 60%
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 < 30%
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 < 30%
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 < 30%
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 30 - 60%
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 > 60%
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 < 30%
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 > 60%
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 30 - 60%
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 < 30%
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 < 30%
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 > 60%
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 < 30%
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 < 30%
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 < 30%
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 42.2% [17.8%; 59.4%]; H = 1.32 [1.10; 1.57]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30% 32 0.3681 [0.2358; 0.5004] 56.93 45.5%
## 30 - 60% 10 0.2967 [0.0268; 0.5667] 14.05 35.9%
## > 60% 6 0.4760 [0.0866; 0.8654] 6.93 27.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.56 2 0.7559
## Within groups 77.91 45 0.0017
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30% 32 0.4076 [ 0.2175; 0.5977] 0.1259 0.3549
## 30 - 60% 10 0.2537 [-0.0956; 0.6030] 0.1104 0.3322
## > 60% 6 0.4704 [ 0.0077; 0.9330] 0.0927 0.3045
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.73 2 0.6951
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1523 (SE = 0.0708)
## tau (square root of estimated tau^2 value): 0.3903
## I^2 (residual heterogeneity / unaccounted variability): 48.09%
## H^2 (unaccounted variability / sampling variability): 1.93
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 46) = 88.6112, p-val = 0.0002
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0009, p-val = 0.9755
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.3997 0.1131 3.5347 0.0004 0.1781 0.6213 ***
## bsln_adjusted 0.0001 0.0033 0.0307 0.9755 -0.0064 0.0066
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Bækkerud 2016 0.5820 [-0.3903; 1.5542] 1.4 1.8 HIIT
## Beetham 2019 -0.6337 [-1.7518; 0.4845] 1.0 1.5 HIIT
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 1.7 2.0 SIT
## Ciolac 2010 0.7968 [-0.0715; 1.6650] 1.7 2.0 HIIT
## Cocks 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 SIT
## Conraads 2015 0.1953 [-0.1026; 0.4933] 14.5 4.1 HIIT
## Currie 2015 0.5330 [-0.3833; 1.4494] 1.5 1.9 HIIT
## Earnest 2013 -0.0715 [-0.7221; 0.5791] 3.0 2.7 HIIT
## Fisher 2015 -0.7440 [-1.5960; 0.1079] 1.8 2.1 SIT
## Gillen 2016 -0.4021 [-1.3117; 0.5075] 1.6 1.9 SIT
## Gorostiaga 1991 1.4458 [ 0.1749; 2.7166] 0.8 1.2 SIT
## Grieco 2013 0.6057 [-0.2523; 1.4638] 1.7 2.1 HIIT
## Helgerud 2007 1.0281 [ 0.0955; 1.9607] 1.5 1.9 HIIT
## Helgerud 2007 0.9016 [-0.0184; 1.8216] 1.5 1.9 SIT
## Henriksson 1976 -0.5694 [-1.9102; 0.7715] 0.7 1.1 HIIT
## Honkala 2017 (Healthy) 0.8299 [ 0.0579; 1.6019] 2.2 2.3 SIT
## Honkala 2017 (T2D) 1.7112 [ 0.5592; 2.8633] 1.0 1.4 SIT
## Keating 2014 0.3091 [-0.5316; 1.1498] 1.8 2.1 HIIT
## Keteyian 2014 0.6606 [-0.1020; 1.4232] 2.2 2.3 HIIT
## Kim 2015 0.9018 [ 0.1242; 1.6793] 2.1 2.3 HIIT
## Klonizakis 2014 0.1765 [-0.7729; 1.1259] 1.4 1.8 HIIT
## Lunt 2014 0.9567 [ 0.0748; 1.8385] 1.7 2.0 HIIT
## Lunt 2014 0.5858 [-0.2686; 1.4401] 1.8 2.1 SIT
## Macpherson 2011 -0.0240 [-0.9005; 0.8526] 1.7 2.0 SIT
## Madssen 2014 0.5664 [-0.1090; 1.2418] 2.8 2.6 HIIT
## Martins 2016 -0.0365 [-0.7538; 0.6809] 2.5 2.5 SIT
## Matsuo 2014 0.6957 [-0.0960; 1.4874] 2.0 2.3 HIIT
## Matsuo 2015 0.8715 [ 0.0342; 1.7088] 1.8 2.1 HIIT
## Mitranun 2014 0.9929 [ 0.2078; 1.7781] 2.1 2.3 HIIT
## Molmen-Hansen 2011 0.6999 [ 0.1724; 1.2275] 4.6 3.2 HIIT
## Motiani 2017 0.4668 [-0.3123; 1.2460] 2.1 2.3 SIT
## Nalcakan 2014 -0.2565 [-1.2750; 0.7620] 1.2 1.7 SIT
## Nie 2017 0.1324 [-0.5857; 0.8505] 2.5 2.5 HIIT
## O’Leary 2018 -0.0213 [-0.8979; 0.8552] 1.7 2.0 HIIT
## Ramos 2016a 0.7144 [ 0.0977; 1.3311] 3.4 2.8 HIIT
## Ramos 2016b 0.8823 [ 0.1552; 1.6095] 2.4 2.5 HIIT
## Robinson 2015 0.0000 [-0.6279; 0.6279] 3.3 2.8 HIIT
## Rognmo 2004 0.6529 [-0.3245; 1.6302] 1.3 1.8 HIIT
## Sandvei 2012 0.2446 [-0.5765; 1.0658] 1.9 2.2 SIT
## Sawyer 2016 0.3610 [-0.5704; 1.2925] 1.5 1.9 HIIT
## Scribbans 2014 -0.1028 [-1.0039; 0.7984] 1.6 2.0 SIT
## Shepherd 2013 -0.5676 [-1.5671; 0.4320] 1.3 1.7 SIT
## Sjöros 2018 0.7485 [-0.1373; 1.6343] 1.6 2.0 SIT
## Skleryk 2013 -0.1275 [-1.1085; 0.8535] 1.3 1.8 SIT
## Tjønna 2008 1.0772 [ 0.1042; 2.0502] 1.4 1.8 HIIT
## Trapp 2008 0.3351 [-0.3856; 1.0558] 2.5 2.5 SIT
## Winn 2018 -0.2185 [-1.2014; 0.7644] 1.3 1.8 HIIT
## Wisløff 2007 4.5911 [ 2.8296; 6.3526] 0.4 0.7 HIIT
##
## Number of studies combined: k = 48
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3794 [0.2661; 0.4927] 6.56 < 0.0001
## Random effects model 0.4017 [0.2381; 0.5653] 4.81 < 0.0001
##
## Quantifying heterogeneity:
## tau^2 = 0.1456 [0.1246; 0.5265]; tau = 0.3816 [0.3529; 0.7256];
## I^2 = 47.1% [25.8%; 62.3%]; H = 1.38 [1.16; 1.63]
##
## Quantifying residual heterogeneity:
## I^2 = 37.6% [10.9%; 56.2%]; H = 1.27 [1.06; 1.51]
##
## Test of heterogeneity:
## Q d.f. p-value
## 88.86 47 0.0002
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 29 0.4500 [ 0.3131; 0.5869] 44.96 37.7%
## SIT 19 0.1760 [-0.0276; 0.3795] 28.71 37.3%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 4.79 1 0.0286
## Within groups 73.68 46 0.0059
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 29 0.4978 [ 0.3119; 0.6837] 0.0891 0.2986
## SIT 19 0.1794 [-0.0802; 0.4390] 0.1225 0.3500
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.82 1 0.0506
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 48; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1355 (SE = 0.0666)
## tau (square root of estimated tau^2 value): 0.3681
## I^2 (residual heterogeneity / unaccounted variability): 45.14%
## H^2 (unaccounted variability / sampling variability): 1.82
## R^2 (amount of heterogeneity accounted for): 6.92%
##
## Test for Residual Heterogeneity:
## QE(df = 46) = 83.8556, p-val = 0.0005
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 3.8516, p-val = 0.0497
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.5250 0.1036 5.0692 <.0001 0.3220 0.7280 ***
## HIIESIT -0.3336 0.1700 -1.9626 0.0497 -0.6668 -0.0004 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Bækkerud 2016 0.6282 [ 0.1385; 1.1178] 0.0119 0.3489 0.5907 76.2%
## Omitting Conraads 2015 0.5936 [ 0.0329; 1.1543] 0.0380 0.4683 0.6843 73.9%
## Omitting Jo 2020 0.4670 [-0.0521; 0.9861] 0.0779 0.3960 0.6293 77.3%
## Omitting Klonizakis 2014 0.5674 [ 0.0508; 1.0840] 0.0313 0.4023 0.6343 78.6%
## Omitting Madssen 2014 0.6192 [ 0.1033; 1.1352] 0.0187 0.3871 0.6222 76.5%
## Omitting Mitranun 2014 0.5564 [ 0.0233; 1.0894] 0.0408 0.4273 0.6537 78.8%
## Omitting Molmen-Hansen 2011 0.3851 [-0.0674; 0.8376] 0.0953 0.2594 0.5094 67.3%
## Omitting Sawyer 2016 0.4265 [-0.0574; 0.9104] 0.0841 0.3412 0.5841 76.0%
## Omitting Tjønna 2008 0.3951 [-0.0647; 0.8549] 0.0922 0.2976 0.5455 73.5%
##
## Pooled estimate 0.5370 [ 0.0485; 1.0255] 0.0312 0.3999 0.6324 77.7%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.5370 [ 0.0485; 1.0255] Overall
## Healthy 0.0619 [-0.8860; 1.0098] Population
## Overweight/obese 0.7341 [-0.4521; 1.9203] Population
## Cardiac Rehabilitation 0.0336 [-0.2378; 0.3051] Population
## Metabolic Syndrome 1.2483 [ 0.3728; 2.1239] Population
## T2D 0.2306 [-0.5131; 0.9742] Population
## 30 - 50 y 0.4118 [-1.5480; 2.3717] Age
## > 50 y 0.5410 [ 0.0365; 1.0454] Age
## < 5 weeks 0.0619 [-0.8860; 1.0098] Training Duration
## 5 - 10 weeks 0.4879 [-0.2648; 1.2405] Training Duration
## > 10 weeks 0.6571 [-0.1522; 1.4665] Training Duration
## < 0.5 0.5499 [-0.2552; 1.3550] Men Ratio
## > 0.5 0.4976 [-0.1690; 1.1642] Men Ratio
## Running 0.5593 [-0.1117; 1.2302] Type of Exercise
## Cycling 0.4101 [-0.3234; 1.1436] Type of Exercise
## < 6 % 0.7518 [-0.0275; 1.5311] Baseline Values
## > 6 % 0.3359 [-0.3868; 1.0587] Baseline Values
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999; tau = 0.6324; I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
## Population 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
## Age 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
## Training Duration 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
## Men Ratio 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
## Type of Exercise 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
## Baseline Values 9 0.5370 [0.0485; 1.0255] 0.3999 0.6324 35.88 77.7%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6 Overweight/obese
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7 Cardiac Rehabilitation
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7 Metabolic Syndrome
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8 Healthy
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1 Cardiac Rehabilitation
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4 T2D
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9 Overweight/obese
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1 Overweight/obese
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7 Metabolic Syndrome
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Quantifying residual heterogeneity:
## I^2 = 71.5% [28.0%; 88.7%]; H = 1.87 [1.18; 2.98]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 1 0.0619 [-0.8860; 1.0098] 0.00 --
## Overweight/obese 3 0.9260 [ 0.4812; 1.3709] 11.49 82.6%
## Cardiac Rehabilitation 2 0.0336 [-0.2378; 0.3051] 0.70 0.0%
## Metabolic Syndrome 2 1.1586 [ 0.5598; 1.7575] 1.85 45.9%
## T2D 1 0.2306 [-0.5131; 0.9742] 0.00 --
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 19.10 4 0.0008
## Within groups 14.05 4 0.0072
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 1 0.0619 [-0.8860; 1.0098] -- --
## Overweight/obese 3 0.7341 [-0.4521; 1.9203] 0.8979 0.9476
## Cardiac Rehabilitation 2 0.0336 [-0.2378; 0.3051] 0 0
## Metabolic Syndrome 2 1.2483 [ 0.3728; 2.1239] 0.1935 0.4398
## T2D 1 0.2306 [-0.5131; 0.9742] -- --
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 7.74 4 0.1016
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 9; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3798 (SE = 0.3944)
## tau (square root of estimated tau^2 value): 0.6163
## I^2 (residual heterogeneity / unaccounted variability): 73.88%
## H^2 (unaccounted variability / sampling variability): 3.83
## R^2 (amount of heterogeneity accounted for): 5.02%
##
## Test for Residual Heterogeneity:
## QE(df = 4) = 15.3125, p-val = 0.0041
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 4.5928, p-val = 0.3317
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0650 0.7834 0.0829 0.9339 -1.4705 1.6004
## .byvarOverweight/obese 0.7148 0.8965 0.7973 0.4253 -1.0424 2.4719
## .byvarCardiac Rehabilitation -0.1214 0.9142 -0.1327 0.8944 -1.9132 1.6705
## .byvarMetabolic Syndrome 1.2685 0.9524 1.3319 0.1829 -0.5981 3.1351
## .byvarT2D 0.1725 1.0665 0.1618 0.8715 -1.9178 2.2629
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6 30 - 50 y
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7 > 50 y
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7 > 50 y
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8 > 50 y
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1 > 50 y
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4 > 50 y
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9 > 50 y
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1 30 - 50 y
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7 > 50 y
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Quantifying residual heterogeneity:
## I^2 = 78.9% [58.6%; 89.2%]; H = 2.18 [1.55; 3.04]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## 30 - 50 y 2 0.3396 [-0.3801; 1.0592] 7.37 86.4%
## > 50 y 7 0.3659 [ 0.1546; 0.5772] 25.77 76.7%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.00 1 0.9452
## Within groups 33.14 7 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## 30 - 50 y 2 0.4118 [-1.5480; 2.3717] 1.7285 1.3147
## > 50 y 7 0.5410 [ 0.0365; 1.0454] 0.3295 0.5740
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.02 1 0.9005
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 9; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3793 (SE = 0.3034)
## tau (square root of estimated tau^2 value): 0.6158
## I^2 (residual heterogeneity / unaccounted variability): 77.00%
## H^2 (unaccounted variability / sampling variability): 4.35
## R^2 (amount of heterogeneity accounted for): 5.16%
##
## Test for Residual Heterogeneity:
## QE(df = 7) = 30.4306, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.7035, p-val = 0.4016
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 1.8217 1.5525 1.1734 0.2406 -1.2211 4.8644
## age -0.0241 0.0287 -0.8388 0.4016 -0.0803 0.0322
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6 5 - 10 weeks
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7 > 10 weeks
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7 5 - 10 weeks
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8 < 5 weeks
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1 > 10 weeks
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4 5 - 10 weeks
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9 > 10 weeks
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1 5 - 10 weeks
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7 > 10 weeks
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Quantifying residual heterogeneity:
## I^2 = 81.4% [62.7%; 90.8%]; H = 2.32 [1.64; 3.29]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 1 0.0619 [-0.8860; 1.0098] 0.00 --
## 5 - 10 weeks 4 0.4979 [ 0.0800; 0.9158] 9.25 67.6%
## > 10 weeks 4 0.3391 [ 0.1000; 0.5782] 23.07 87.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.83 2 0.6615
## Within groups 32.32 6 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 1 0.0619 [-0.8860; 1.0098] -- --
## 5 - 10 weeks 4 0.4879 [-0.2648; 1.2405] 0.3933 0.6271
## > 10 weeks 4 0.6571 [-0.1522; 1.4665] 0.5619 0.7496
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.90 2 0.6366
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 9; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.4532 (SE = 0.3554)
## tau (square root of estimated tau^2 value): 0.6732
## I^2 (residual heterogeneity / unaccounted variability): 79.93%
## H^2 (unaccounted variability / sampling variability): 4.98
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 7) = 34.8759, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.4855, p-val = 0.2229
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.3034 0.7395 -0.4102 0.6816 -1.7528 1.1461
## duration 0.0868 0.0712 1.2188 0.2229 -0.0528 0.2264
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6 < 0.5
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7 > 0.5
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7 > 0.5
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8 < 0.5
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1 > 0.5
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4 < 0.5
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9 > 0.5
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1 < 0.5
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7 < 0.5
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Quantifying residual heterogeneity:
## I^2 = 78.7% [58.3%; 89.1%]; H = 2.17 [1.55; 3.03]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 5 0.4588 [0.0382; 0.8794] 14.15 71.7%
## > 0.5 4 0.3351 [0.1037; 0.5664] 18.74 84.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.26 1 0.6135
## Within groups 32.89 7 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 5 0.5499 [-0.2552; 1.3550] 0.5991 0.7740
## > 0.5 4 0.4976 [-0.1690; 1.1642] 0.3784 0.6152
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.01 1 0.9219
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 9; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.4713 (SE = 0.3532)
## tau (square root of estimated tau^2 value): 0.6865
## I^2 (residual heterogeneity / unaccounted variability): 77.56%
## H^2 (unaccounted variability / sampling variability): 4.46
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 7) = 31.1980, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0857, p-val = 0.7698
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.7020 0.6113 1.1483 0.2508 -0.4962 1.9002
## men_ratio -0.3077 1.0514 -0.2927 0.7698 -2.3684 1.7529
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6 Running
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7 Cycling
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7 Running
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8 Cycling
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1 Running
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4 Running
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9 Running
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1 Cycling
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7 Running
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Quantifying residual heterogeneity:
## I^2 = 75.9% [51.7%; 88.0%]; H = 2.04 [1.44; 2.88]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 6 0.5946 [ 0.2934; 0.8957] 23.32 78.6%
## Cycling 3 0.1725 [-0.1016; 0.4467] 5.70 64.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 4.13 1 0.0422
## Within groups 29.02 7 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 6 0.5593 [-0.1117; 1.2302] 0.5379 0.7334
## Cycling 3 0.4101 [-0.3234; 1.1436] 0.2716 0.5211
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.09 1 0.7687
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 9; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.5099 (SE = 0.3668)
## tau (square root of estimated tau^2 value): 0.7141
## I^2 (residual heterogeneity / unaccounted variability): 77.82%
## H^2 (unaccounted variability / sampling variability): 4.51
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 7) = 31.5548, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0302, p-val = 0.8620
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4755 0.4724 1.0065 0.3142 -0.4505 1.4015
## type_exerciseRunning 0.1007 0.5791 0.1738 0.8620 -1.0343 1.2356
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Bækkerud 2016 -0.6077 [-1.5818; 0.3663] 4.3 9.6 > 6 %
## Conraads 2015 0.0860 [-0.2114; 0.3833] 46.2 14.7 < 6 %
## Jo 2020 0.9166 [ 0.2099; 1.6233] 8.2 11.7 > 6 %
## Klonizakis 2014 0.0650 [-0.8829; 1.0128] 4.6 9.8 > 6 %
## Madssen 2014 -0.2313 [-0.8960; 0.4335] 9.3 12.1 > 6 %
## Mitranun 2014 0.2375 [-0.5059; 0.9809] 7.4 11.4 < 6 %
## Molmen-Hansen 2011 1.3059 [ 0.7421; 1.8697] 12.9 12.9 > 6 %
## Sawyer 2016 1.4943 [ 0.4494; 2.5393] 3.7 9.1 < 6 %
## Tjønna 2008 1.8981 [ 0.8055; 2.9906] 3.4 8.7 < 6 %
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model 0.3768 [0.1746; 0.5791] 3.65 0.0003
## Random effects model 0.5370 [0.0485; 1.0255] 2.15 0.0312
##
## Quantifying heterogeneity:
## tau^2 = 0.3999 [0.1350; 2.2069]; tau = 0.6324 [0.3675; 1.4856];
## I^2 = 77.7% [57.7%; 88.2%]; H = 2.12 [1.54; 2.92]
##
## Quantifying residual heterogeneity:
## I^2 = 78.2% [57.0%; 88.9%]; H = 2.14 [1.52; 3.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 35.88 8 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 6 % 4 0.2767 [0.0168; 0.5367] 13.33 77.5%
## > 6 % 5 0.4991 [0.1751; 0.8230] 18.71 78.6%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.10 1 0.2941
## Within groups 32.04 7 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 6 % 4 0.7518 [-0.0275; 1.5311] 0.4600 0.6782
## > 6 % 5 0.3359 [-0.3868; 1.0587] 0.5238 0.7237
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.59 1 0.4432
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 9; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.4646 (SE = 0.3631)
## tau (square root of estimated tau^2 value): 0.6816
## I^2 (residual heterogeneity / unaccounted variability): 79.25%
## H^2 (unaccounted variability / sampling variability): 4.82
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 7) = 33.7369, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 2.2409, p-val = 0.1344
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 1.9301 0.9650 2.0001 0.0455 0.0387 3.8214 *
## bsln_adjusted -0.2105 0.1406 -1.4970 0.1344 -0.4861 0.0651
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 -0.0160 [-0.1546; 0.1226] 0.8213 0.0000 0.0000 0.0%
## Omitting Cocks 2013 -0.0190 [-0.1564; 0.1183] 0.7858 0.0000 0.0000 0.0%
## Omitting Conraads 2015 0.0227 [-0.1302; 0.1755] 0.7712 0.0000 0.0000 0.0%
## Omitting Currie 2015 -0.0200 [-0.1576; 0.1176] 0.7756 0.0000 0.0000 0.0%
## Omitting Eguchi 2012 -0.0203 [-0.1579; 0.1174] 0.7726 0.0000 0.0000 0.0%
## Omitting Fisher 2015 -0.0162 [-0.1540; 0.1217] 0.8184 0.0000 0.0000 0.0%
## Omitting Gillen 2016 -0.0263 [-0.1639; 0.1112] 0.7076 0.0000 0.0000 0.0%
## Omitting Grieco 2013 -0.0174 [-0.1552; 0.1204] 0.8043 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) -0.0243 [-0.1626; 0.1140] 0.7305 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) -0.0204 [-0.1577; 0.1168] 0.7704 0.0000 0.0000 0.0%
## Omitting Jo 2020 -0.0143 [-0.1532; 0.1245] 0.8396 0.0000 0.0000 0.0%
## Omitting Lunt 2014 -0.0177 [-0.1556; 0.1201] 0.8007 0.0000 0.0000 0.0%
## Omitting Lunt 2014 -0.0192 [-0.1570; 0.1186] 0.7850 0.0000 0.0000 0.0%
## Omitting Madssen 2014 -0.0175 [-0.1564; 0.1215] 0.8053 0.0000 0.0000 0.0%
## Omitting Maillard 2016 -0.0223 [-0.1596; 0.1150] 0.7505 0.0000 0.0000 0.0%
## Omitting Matsuo 2014 -0.0077 [-0.1458; 0.1304] 0.9129 0.0000 0.0000 0.0%
## Omitting Mitranun 2014 -0.0421 [-0.1803; 0.0961] 0.5506 0.0000 0.0000 0.0%
## Omitting Moreira 2008 -0.0190 [-0.1564; 0.1183] 0.7858 0.0000 0.0000 0.0%
## Omitting Motiani 2017 -0.0243 [-0.1625; 0.1138] 0.7301 0.0000 0.0000 0.0%
## Omitting Nalcakan 2014 -0.0175 [-0.1547; 0.1197] 0.8024 0.0000 0.0000 0.0%
## Omitting Nie 2017 -0.0153 [-0.1538; 0.1232] 0.8290 0.0000 0.0000 0.0%
## Omitting Ramos 2016b -0.0322 [-0.1708; 0.1065] 0.6494 0.0000 0.0000 0.0%
## Omitting Robinson 2015 -0.0228 [-0.1621; 0.1165] 0.7487 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 -0.0209 [-0.1588; 0.1170] 0.7660 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 -0.0191 [-0.1566; 0.1184] 0.7855 0.0000 0.0000 0.0%
## Omitting Shepherd 2013 -0.0190 [-0.1564; 0.1183] 0.7858 0.0000 0.0000 0.0%
## Omitting Sjöros 2018 -0.0192 [-0.1569; 0.1186] 0.7852 0.0000 0.0000 0.0%
## Omitting Skleryk 2013 -0.0190 [-0.1564; 0.1183] 0.7858 0.0000 0.0000 0.0%
## Omitting Tjønna 2008 -0.0152 [-0.1527; 0.1223] 0.8282 0.0000 0.0000 0.0%
## Omitting Winn 2018 -0.0111 [-0.1483; 0.1262] 0.8745 0.0000 0.0000 0.0%
##
## Pooled estimate -0.0183 [-0.1543; 0.1176] 0.7919 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.0183 [-0.1543; 0.1176] Overall
## Healthy 0.0043 [-0.2490; 0.2576] Population
## Overweight/obese -0.0766 [-0.4179; 0.2647] Population
## Cardiac Rehabilitation -0.1378 [-0.3979; 0.1223] Population
## Metabolic Syndrome 0.0446 [-0.3093; 0.3984] Population
## T2D 0.1769 [-0.1974; 0.5512] Population
## < 30 y -0.0554 [-0.3412; 0.2303] Age
## 30 - 50 y 0.0078 [-0.2694; 0.2851] Age
## > 50 y -0.0150 [-0.2013; 0.1713] Age
## < 5 weeks 0.0208 [-0.2691; 0.3108] Training Duration
## 5 - 10 weeks -0.0003 [-0.2605; 0.2600] Training Duration
## > 10 weeks -0.0457 [-0.2367; 0.1453] Training Duration
## < 0.5 0.0352 [-0.2045; 0.2749] Men Ratio
## > 0.5 -0.0442 [-0.2093; 0.1209] Men Ratio
## Cycling -0.0480 [-0.2075; 0.1115] Type of Exercise
## Running 0.0592 [-0.2008; 0.3193] Type of Exercise
## BMI < 25 kg/m² -0.1022 [-0.4470; 0.2425] Baseline Values
## BMI 25 - 30 kg/m² -0.0185 [-0.2024; 0.1654] Baseline Values
## BMI > 30 kg/m² 0.0247 [-0.2246; 0.2740] Baseline Values
## HIIT -0.0479 [-0.2091; 0.1133] Type of HIIE
## SIT 0.0535 [-0.1998; 0.3067] Type of HIIE
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0; tau = 0; I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Population 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Age 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Training Duration 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Men Ratio 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Type of Exercise 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Baseline Values 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
## Type of HIIE 30 -0.0183 [-0.1543; 0.1176] 0 0 8.91 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 T2D
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 Healthy
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 Cardiac Rehabilitation
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 Cardiac Rehabilitation
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 Healthy
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 Overweight/obese
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 Healthy
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 Healthy
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 Healthy
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 T2D
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 Metabolic Syndrome
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 Overweight/obese
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 Overweight/obese
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 Cardiac Rehabilitation
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 T2D
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 Healthy
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 T2D
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 Overweight/obese
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 Healthy
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 Healthy
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 Healthy
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 Metabolic Syndrome
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 Metabolic Syndrome
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 Healthy
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 Overweight/obese
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 Healthy
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 T2D
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 Overweight/obese
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 Metabolic Syndrome
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 Overweight/obese
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 11 0.0043 [-0.2490; 0.2576] 1.78 0.0%
## Overweight/obese 7 -0.0766 [-0.4179; 0.2647] 0.57 0.0%
## Cardiac Rehabilitation 3 -0.1378 [-0.3979; 0.1223] 0.28 0.0%
## Metabolic Syndrome 4 0.0446 [-0.3093; 0.3984] 1.06 0.0%
## T2D 5 0.1769 [-0.1974; 0.5512] 2.56 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 2.12 4 0.7136
## Within groups 6.25 25 0.9999
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 11 0.0043 [-0.2490; 0.2576] 0 0
## Overweight/obese 7 -0.0766 [-0.4179; 0.2647] 0 0
## Cardiac Rehabilitation 3 -0.1378 [-0.3979; 0.1223] 0 0
## Metabolic Syndrome 4 0.0446 [-0.3093; 0.3984] 0 0
## T2D 5 0.1769 [-0.1974; 0.5512] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.12 4 0.7136
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0476)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 6.6874, p-val = 0.9999
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 2.2274, p-val = 0.6940
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0047 0.1292 0.0361 0.9712 -0.2486 0.2579
## .byvarOverweight/obese -0.0853 0.2168 -0.3936 0.6938 -0.5102 0.3396
## .byvarCardiac Rehabilitation -0.1431 0.1852 -0.7726 0.4398 -0.5061 0.2199
## .byvarMetabolic Syndrome 0.0405 0.2220 0.1826 0.8551 -0.3945 0.4756
## .byvarT2D 0.1793 0.2305 0.7782 0.4364 -0.2723 0.6310
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 > 50 y
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 < 30 y
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 > 50 y
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 > 50 y
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 > 50 y
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 < 30 y
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 < 30 y
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 < 30 y
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 30 - 50 y
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 30 - 50 y
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 > 50 y
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 30 - 50 y
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 30 - 50 y
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 > 50 y
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 > 50 y
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 < 30 y
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 > 50 y
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 30 - 50 y
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 30 - 50 y
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 < 30 y
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 < 30 y
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 > 50 y
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 > 50 y
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 < 30 y
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 30 - 50 y
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 < 30 y
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 30 - 50 y
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 30 - 50 y
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 > 50 y
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 30 - 50 y
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 9 -0.0554 [-0.3412; 0.2303] 1.39 0.0%
## 30 - 50 y 10 0.0078 [-0.2694; 0.2851] 1.01 0.0%
## > 50 y 11 -0.0150 [-0.2013; 0.1713] 5.87 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.10 2 0.9512
## Within groups 8.27 27 0.9998
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 9 -0.0554 [-0.3412; 0.2303] 0 0
## 30 - 50 y 10 0.0078 [-0.2694; 0.2851] 0 0
## > 50 y 11 -0.0150 [-0.2013; 0.1713] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.10 2 0.9512
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0409)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 28) = 8.7767, p-val = 0.9998
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1380, p-val = 0.7103
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1037 0.2401 -0.4319 0.6658 -0.5742 0.3669
## age 0.0018 0.0049 0.3715 0.7103 -0.0078 0.0115
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 5 - 10 weeks
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 5 - 10 weeks
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 > 10 weeks
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 > 10 weeks
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 > 10 weeks
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 5 - 10 weeks
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 > 10 weeks
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 < 5 weeks
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 < 5 weeks
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 < 5 weeks
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 5 - 10 weeks
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 > 10 weeks
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 > 10 weeks
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 > 10 weeks
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 > 10 weeks
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 5 - 10 weeks
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 5 - 10 weeks
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 > 10 weeks
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 < 5 weeks
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 5 - 10 weeks
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 > 10 weeks
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 > 10 weeks
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 < 5 weeks
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 5 - 10 weeks
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 5 - 10 weeks
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 5 - 10 weeks
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 < 5 weeks
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 < 5 weeks
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 > 10 weeks
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 < 5 weeks
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 8 0.0208 [-0.2691; 0.3108] 1.05 0.0%
## 5 - 10 weeks 10 -0.0003 [-0.2605; 0.2600] 4.37 0.0%
## > 10 weeks 12 -0.0457 [-0.2367; 0.1453] 2.79 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.17 2 0.9195
## Within groups 8.20 27 0.9998
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 8 0.0208 [-0.2691; 0.3108] 0 0
## 5 - 10 weeks 10 -0.0003 [-0.2605; 0.2600] 0 0
## > 10 weeks 12 -0.0457 [-0.2367; 0.1453] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.17 2 0.9195
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0407)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 28) = 8.9111, p-val = 0.9998
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0037, p-val = 0.9518
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0095 0.1621 -0.0583 0.9535 -0.3271 0.3082
## duration -0.0010 0.0162 -0.0604 0.9518 -0.0328 0.0308
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 > 0.5
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 > 0.5
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 > 0.5
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 > 0.5
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 > 0.5
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 > 0.5
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 > 0.5
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 < 0.5
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 > 0.5
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 > 0.5
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 > 0.5
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 < 0.5
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 < 0.5
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 > 0.5
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 < 0.5
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 > 0.5
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 < 0.5
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 < 0.5
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 > 0.5
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 > 0.5
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 < 0.5
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 > 0.5
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 < 0.5
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 < 0.5
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 < 0.5
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 > 0.5
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 > 0.5
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 > 0.5
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 < 0.5
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 < 0.5
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 12 0.0352 [-0.2045; 0.2749] 4.25 0.0%
## > 0.5 18 -0.0442 [-0.2093; 0.1209] 3.83 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.29 1 0.5929
## Within groups 8.09 28 0.9999
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 12 0.0352 [-0.2045; 0.2749] 0 0
## > 0.5 18 -0.0442 [-0.2093; 0.1209] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.29 1 0.5929
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0406)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 28) = 8.6288, p-val = 0.9998
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.2860, p-val = 0.5928
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0663 0.1728 0.3839 0.7010 -0.2724 0.4051
## men_ratio -0.1218 0.2277 -0.5348 0.5928 -0.5681 0.3246
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 Cycling
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 Cycling
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 Cycling
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 Cycling
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 Cycling
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 Cycling
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 Cycling
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 Cycling
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 Cycling
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 Cycling
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 Running
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 Running
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 Running
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 Running
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 Cycling
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 Cycling
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 Running
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 Cycling
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 Cycling
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 Cycling
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 Cycling
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 Running
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 Cycling
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 Running
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 Cycling
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 Cycling
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 Cycling
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 Cycling
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 Running
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 Running
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 21 -0.0480 [-0.2075; 0.1115] 3.06 0.0%
## Running 9 0.0592 [-0.2008; 0.3193] 4.84 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.47 1 0.4910
## Within groups 7.90 28 0.9999
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 21 -0.0480 [-0.2075; 0.1115] 0 0
## Running 9 0.0592 [-0.2008; 0.3193] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.47 1 0.4910
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0406)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 28) = 8.4313, p-val = 0.9999
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.4834, p-val = 0.4869
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0479 0.0814 -0.5886 0.5562 -0.2074 0.1116
## type_exerciseRunning 0.1082 0.1556 0.6953 0.4869 -0.1968 0.4131
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 BMI > 30 kg/m²
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 BMI < 25 kg/m²
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 BMI 25 - 30 kg/m²
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 BMI 25 - 30 kg/m²
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 BMI 25 - 30 kg/m²
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 BMI 25 - 30 kg/m²
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 BMI 25 - 30 kg/m²
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 BMI 25 - 30 kg/m²
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 BMI 25 - 30 kg/m²
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 BMI > 30 kg/m²
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 BMI < 25 kg/m²
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 BMI > 30 kg/m²
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 BMI > 30 kg/m²
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 BMI 25 - 30 kg/m²
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 BMI > 30 kg/m²
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 BMI < 25 kg/m²
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 BMI 25 - 30 kg/m²
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 BMI 25 - 30 kg/m²
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 BMI 25 - 30 kg/m²
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 BMI < 25 kg/m²
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 BMI 25 - 30 kg/m²
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 BMI > 30 kg/m²
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 BMI > 30 kg/m²
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 BMI < 25 kg/m²
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 BMI > 30 kg/m²
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 BMI < 25 kg/m²
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 BMI > 30 kg/m²
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 BMI > 30 kg/m²
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 BMI 25 - 30 kg/m²
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 BMI > 30 kg/m²
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## BMI < 25 kg/m² 6 -0.1022 [-0.4470; 0.2425] 0.68 0.0%
## BMI 25 - 30 kg/m² 13 -0.0185 [-0.2024; 0.1654] 5.63 0.0%
## BMI > 30 kg/m² 11 0.0247 [-0.2246; 0.2740] 1.71 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.34 2 0.8429
## Within groups 8.03 27 0.9998
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## BMI < 25 kg/m² 6 -0.1022 [-0.4470; 0.2425] 0 0
## BMI 25 - 30 kg/m² 13 -0.0185 [-0.2024; 0.1654] 0 0
## BMI > 30 kg/m² 11 0.0247 [-0.2246; 0.2740] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.34 2 0.8429
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0398)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 28) = 8.8474, p-val = 0.9998
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0674, p-val = 0.7952
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1614 0.5558 -0.2905 0.7715 -1.2508 0.9279
## bsln_adjusted 0.0050 0.0192 0.2596 0.7952 -0.0327 0.0427
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 -0.0910 [-0.7957; 0.6138] 3.7 3.7 HIIT
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 SIT
## Conraads 2015 -0.1764 [-0.4743; 0.1214] 20.8 20.8 HIIT
## Currie 2015 0.0405 [-0.8602; 0.9411] 2.3 2.3 HIIT
## Eguchi 2012 0.0492 [-0.8275; 0.9259] 2.4 2.4 HIIT
## Fisher 2015 -0.1130 [-0.9380; 0.7121] 2.7 2.7 SIT
## Gillen 2016 0.3289 [-0.5777; 1.2354] 2.2 2.2 SIT
## Grieco 2013 -0.0678 [-0.9073; 0.7716] 2.6 2.6 HIIT
## Honkala 2017 (Healthy) 0.1477 [-0.5941; 0.8895] 3.4 3.4 SIT
## Honkala 2017 (T2D) 0.0775 [-0.9106; 1.0656] 1.9 1.9 SIT
## Jo 2020 -0.1235 [-0.7964; 0.5494] 4.1 4.1 HIIT
## Lunt 2014 -0.0548 [-0.8923; 0.7827] 2.6 2.6 HIIT
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.6 2.6 SIT
## Madssen 2014 -0.0471 [-0.7098; 0.6156] 4.2 4.2 HIIT
## Maillard 2016 0.1751 [-0.8067; 1.1570] 1.9 1.9 HIIT
## Matsuo 2014 -0.3770 [-1.1526; 0.3985] 3.1 3.1 HIIT
## Mitranun 2014 0.7236 [-0.0411; 1.4883] 3.2 3.2 HIIT
## Moreira 2008 0.0000 [-0.9800; 0.9800] 1.9 1.9 HIIT
## Motiani 2017 0.1618 [-0.6082; 0.9318] 3.1 3.1 SIT
## Nalcakan 2014 -0.0869 [-1.1018; 0.9279] 1.8 1.8 SIT
## Nie 2017 -0.1134 [-0.8313; 0.6044] 3.6 3.6 HIIT
## Ramos 2016b 0.3328 [-0.3662; 1.0319] 3.8 3.8 HIIT
## Robinson 2015 0.0659 [-0.5622; 0.6939] 4.7 4.7 HIIT
## Sandvei 2012 0.0636 [-0.7547; 0.8819] 2.8 2.8 SIT
## Sawyer 2016 0.0000 [-0.9239; 0.9239] 2.2 2.2 HIIT
## Shepherd 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 SIT
## Sjöros 2018 0.0000 [-0.8564; 0.8564] 2.5 2.5 SIT
## Skleryk 2013 0.0000 [-0.9800; 0.9800] 1.9 1.9 SIT
## Tjønna 2008 -0.1783 [-1.0908; 0.7341] 2.2 2.2 HIIT
## Winn 2018 -0.4417 [-1.4336; 0.5501] 1.9 1.9 HIIT
##
## Number of studies combined: k = 30
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
## Random effects model -0.0183 [-0.1543; 0.1176] -0.26 0.7919
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 8.91 29 0.9999
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 18 -0.0479 [-0.2091; 0.1133] 7.21 0.0%
## SIT 12 0.0535 [-0.1998; 0.3067] 0.73 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.44 1 0.5082
## Within groups 7.93 28 0.9999
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 18 -0.0479 [-0.2091; 0.1133] 0 0
## SIT 12 0.0535 [-0.1998; 0.3067] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.44 1 0.5082
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 30; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0404)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 28) = 8.4565, p-val = 0.9999
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.4583, p-val = 0.4984
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0482 0.0822 -0.5860 0.5579 -0.2093 0.1130
## HIIESIT 0.1037 0.1532 0.6770 0.4984 -0.1965 0.4038
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Bækkerud 2016 -0.0496 [-0.1685; 0.0693] 0.4135 0.0000 0.0000 0.0%
## Omitting Beetham 2019 -0.0408 [-0.1595; 0.0778] 0.5000 0.0000 0.0000 0.0%
## Omitting Burgomaster 2008 -0.0514 [-0.1705; 0.0677] 0.3977 0.0000 0.0000 0.0%
## Omitting Cocks 2013 -0.0483 [-0.1672; 0.0705] 0.4254 0.0000 0.0000 0.0%
## Omitting Conraads 2015 -0.0323 [-0.1609; 0.0962] 0.6221 0.0000 0.0000 0.0%
## Omitting Currie 2015 -0.0481 [-0.1671; 0.0709] 0.4283 0.0000 0.0000 0.0%
## Omitting Earnest 2013 -0.0529 [-0.1729; 0.0671] 0.3874 0.0000 0.0000 0.0%
## Omitting Eguchi 2012 -0.0498 [-0.1689; 0.0693] 0.4127 0.0000 0.0000 0.0%
## Omitting Fisher 2015 -0.0465 [-0.1657; 0.0728] 0.4450 0.0000 0.0000 0.0%
## Omitting Gillen 2016 -0.0470 [-0.1661; 0.0720] 0.4386 0.0000 0.0000 0.0%
## Omitting Gorostiaga 1991 -0.0509 [-0.1696; 0.0677] 0.4000 0.0000 0.0000 0.0%
## Omitting Granata 2015 -0.0472 [-0.1663; 0.0719] 0.4370 0.0000 0.0000 0.0%
## Omitting Granata 2015 -0.0466 [-0.1655; 0.0724] 0.4431 0.0000 0.0000 0.0%
## Omitting Grieco 2013 -0.0465 [-0.1657; 0.0727] 0.4447 0.0000 0.0000 0.0%
## Omitting Helgerud 2007 -0.0461 [-0.1652; 0.0729] 0.4476 0.0000 0.0000 0.0%
## Omitting Helgerud 2007 -0.0435 [-0.1626; 0.0756] 0.4738 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) -0.0512 [-0.1707; 0.0683] 0.4011 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) -0.0486 [-0.1675; 0.0702] 0.4228 0.0000 0.0000 0.0%
## Omitting Jo 2020 -0.0477 [-0.1676; 0.0721] 0.4350 0.0000 0.0000 0.0%
## Omitting Keating 2014 -0.0444 [-0.1636; 0.0748] 0.4651 0.0000 0.0000 0.0%
## Omitting Klonizakis 2014 -0.0492 [-0.1682; 0.0697] 0.4170 0.0000 0.0000 0.0%
## Omitting Macpherson 2011 -0.0506 [-0.1697; 0.0685] 0.4047 0.0000 0.0000 0.0%
## Omitting Maillard 2016 -0.0498 [-0.1686; 0.0691] 0.4119 0.0000 0.0000 0.0%
## Omitting Martins 2016 -0.0540 [-0.1736; 0.0656] 0.3762 0.0000 0.0000 0.0%
## Omitting Matsuo 2014 -0.0415 [-0.1609; 0.0779] 0.4958 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 -0.0487 [-0.1680; 0.0706] 0.4237 0.0000 0.0000 0.0%
## Omitting Mitranun 2014 -0.0546 [-0.1741; 0.0649] 0.3708 0.0000 0.0000 0.0%
## Omitting Moreira 2008 -0.0481 [-0.1670; 0.0707] 0.4273 0.0000 0.0000 0.0%
## Omitting Nalcakan 2014 -0.0470 [-0.1658; 0.0718] 0.4380 0.0000 0.0000 0.0%
## Omitting Nie 2017 -0.0476 [-0.1672; 0.0721] 0.4359 0.0000 0.0000 0.0%
## Omitting Ramos 2016a -0.0496 [-0.1699; 0.0708] 0.4196 0.0000 0.0000 0.0%
## Omitting Ramos 2016b -0.0577 [-0.1775; 0.0620] 0.3445 0.0000 0.0000 0.0%
## Omitting Robinson 2015 -0.0471 [-0.1673; 0.0730] 0.4418 0.0000 0.0000 0.0%
## Omitting Rognmo 2004 -0.0459 [-0.1648; 0.0730] 0.4492 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 -0.0480 [-0.1673; 0.0712] 0.4300 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 -0.0486 [-0.1675; 0.0704] 0.4236 0.0000 0.0000 0.0%
## Omitting Scribbans 2014 -0.0485 [-0.1675; 0.0706] 0.4248 0.0000 0.0000 0.0%
## Omitting Shepherd 2013 -0.0481 [-0.1670; 0.0708] 0.4277 0.0000 0.0000 0.0%
## Omitting Sjöros 2018 -0.0489 [-0.1680; 0.0703] 0.4215 0.0000 0.0000 0.0%
## Omitting Tjønna 2008 -0.0463 [-0.1653; 0.0727] 0.4458 0.0000 0.0000 0.0%
## Omitting Trapp 2008 -0.0547 [-0.1743; 0.0649] 0.3702 0.0000 0.0000 0.0%
## Omitting Winn 2018 -0.0406 [-0.1594; 0.0782] 0.5030 0.0000 0.0000 0.0%
## Omitting Zapata-Lamana 2018 -0.0319 [-0.1513; 0.0876] 0.6010 0.0000 0.0000 0.0%
##
## Pooled estimate -0.0494 [-0.1674; 0.0686] 0.4117 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.0494 [-0.1674; 0.0686] Overall
## Healthy -0.0184 [-0.2123; 0.1754] Population
## Overweight/obese -0.1437 [-0.4112; 0.1238] Population
## Cardiac Rehabilitation -0.1222 [-0.3931; 0.1487] Population
## Metabolic Syndrome 0.0164 [-0.2681; 0.3008] Population
## T2D 0.1033 [-0.3337; 0.5402] Population
## < 30 y -0.0838 [-0.2816; 0.1140] Age
## 30 - 50 y 0.0035 [-0.2481; 0.2552] Age
## > 50 y -0.0438 [-0.2250; 0.1374] Age
## < 5 weeks -0.0635 [-0.3438; 0.2169] Training Duration
## 5 - 10 weeks -0.0117 [-0.2071; 0.1837] Training Duration
## > 10 weeks -0.0701 [-0.2444; 0.1042] Training Duration
## < 0.5 -0.0370 [-0.2247; 0.1507] Men Ratio
## > 0.5 -0.0546 [-0.2063; 0.0971] Men Ratio
## Running -0.0345 [-0.2554; 0.1865] Type of Exercise
## Cycling -0.0529 [-0.1925; 0.0867] Type of Exercise
## BMI < 25 kg/m² -0.0233 [-0.2409; 0.1943] Baseline Values
## BMI 25 - 30 kg/m² -0.0662 [-0.2492; 0.1169] Baseline Values
## BMI > 30 kg/m² -0.0457 [-0.2647; 0.1733] Baseline Values
## HIIT -0.0817 [-0.2239; 0.0605] Type of HIIE
## SIT 0.0276 [-0.1838; 0.2389] Type of HIIE
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0; tau = 0; I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Population 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Age 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Training Duration 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Men Ratio 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Type of Exercise 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Baseline Values 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
## Type of HIIE 43 -0.0494 [-0.1674; 0.0686] 0 0 10.66 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 Overweight/obese
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 Overweight/obese
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 Healthy
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 Healthy
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 Cardiac Rehabilitation
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 Cardiac Rehabilitation
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 Overweight/obese
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 Healthy
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 Overweight/obese
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 Healthy
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 Healthy
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 Healthy
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 Healthy
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 Healthy
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 Healthy
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 Healthy
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 Healthy
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 T2D
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 Metabolic Syndrome
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 Overweight/obese
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 Healthy
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 Healthy
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 T2D
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 Overweight/obese
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 Healthy
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 Metabolic Syndrome
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 T2D
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 Overweight/obese
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 Healthy
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 Healthy
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 Metabolic Syndrome
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 Metabolic Syndrome
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 Metabolic Syndrome
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 Cardiac Rehabilitation
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 Healthy
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 Overweight/obese
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 Healthy
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 Healthy
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 T2D
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 Metabolic Syndrome
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 Healthy
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 Overweight/obese
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 Overweight/obese
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 20 -0.0184 [-0.2123; 0.1754] 2.04 0.0%
## Overweight/obese 10 -0.1437 [-0.4112; 0.1238] 5.23 0.0%
## Cardiac Rehabilitation 3 -0.1222 [-0.3931; 0.1487] 0.06 0.0%
## Metabolic Syndrome 6 0.0164 [-0.2681; 0.3008] 0.81 0.0%
## T2D 4 0.1033 [-0.3337; 0.5402] 0.16 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.53 4 0.8219
## Within groups 8.30 38 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 20 -0.0184 [-0.2123; 0.1754] 0 0
## Overweight/obese 10 -0.1437 [-0.4112; 0.1238] 0 0
## Cardiac Rehabilitation 3 -0.1222 [-0.3931; 0.1487] 0 0
## Metabolic Syndrome 6 0.0164 [-0.2681; 0.3008] 0 0
## T2D 4 0.1033 [-0.3337; 0.5402] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.53 4 0.8219
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0407)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 38) = 9.0142, p-val = 1.0000
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 1.6460, p-val = 0.8005
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0191 0.0989 -0.1931 0.8469 -0.2129 0.1747
## .byvarOverweight/obese -0.1328 0.1684 -0.7884 0.4305 -0.4629 0.1973
## .byvarCardiac Rehabilitation -0.1044 0.1699 -0.6142 0.5391 -0.4374 0.2287
## .byvarMetabolic Syndrome 0.0357 0.1756 0.2036 0.8387 -0.3084 0.3799
## .byvarT2D 0.1262 0.2439 0.5175 0.6048 -0.3517 0.6041
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 30 - 50 y
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 > 50 y
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 < 30 y
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 < 30 y
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 > 50 y
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 > 50 y
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 30 - 50 y
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 > 50 y
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 < 30 y
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 < 30 y
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 < 30 y
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 < 30 y
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 < 30 y
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 < 30 y
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 < 30 y
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 < 30 y
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 30 - 50 y
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 30 - 50 y
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 > 50 y
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 30 - 50 y
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 > 50 y
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 < 30 y
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 > 50 y
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 30 - 50 y
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 < 30 y
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 30 - 50 y
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 > 50 y
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 30 - 50 y
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 < 30 y
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 < 30 y
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 > 50 y
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 > 50 y
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 > 50 y
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 > 50 y
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 < 30 y
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 30 - 50 y
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 < 30 y
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 < 30 y
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 30 - 50 y
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 > 50 y
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 < 30 y
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 30 - 50 y
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 < 30 y
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 19 -0.0838 [-0.2816; 0.1140] 4.54 0.0%
## 30 - 50 y 11 0.0035 [-0.2481; 0.2552] 1.82 0.0%
## > 50 y 13 -0.0438 [-0.2250; 0.1374] 3.18 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.29 2 0.8653
## Within groups 9.54 40 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 19 -0.0838 [-0.2816; 0.1140] 0 0
## 30 - 50 y 11 0.0035 [-0.2481; 0.2552] 0 0
## > 50 y 13 -0.0438 [-0.2250; 0.1374] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.29 2 0.8653
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0359)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 41) = 10.6031, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0571, p-val = 0.8112
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0880 0.1723 -0.5106 0.6096 -0.4257 0.2497
## age 0.0009 0.0038 0.2389 0.8112 -0.0066 0.0084
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 5 - 10 weeks
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 > 10 weeks
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 5 - 10 weeks
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 5 - 10 weeks
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 > 10 weeks
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 > 10 weeks
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 5 - 10 weeks
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 > 10 weeks
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 5 - 10 weeks
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 > 10 weeks
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 5 - 10 weeks
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 < 5 weeks
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 < 5 weeks
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 < 5 weeks
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 5 - 10 weeks
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 5 - 10 weeks
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 < 5 weeks
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 < 5 weeks
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 5 - 10 weeks
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 > 10 weeks
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 < 5 weeks
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 5 - 10 weeks
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 > 10 weeks
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 > 10 weeks
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 5 - 10 weeks
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 5 - 10 weeks
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 5 - 10 weeks
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 > 10 weeks
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 5 - 10 weeks
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 > 10 weeks
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 > 10 weeks
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 > 10 weeks
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 < 5 weeks
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 5 - 10 weeks
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 5 - 10 weeks
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 5 - 10 weeks
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 5 - 10 weeks
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 5 - 10 weeks
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 < 5 weeks
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 > 10 weeks
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 > 10 weeks
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 < 5 weeks
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 > 10 weeks
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 9 -0.0635 [-0.3438; 0.2169] 1.20 0.0%
## 5 - 10 weeks 19 -0.0117 [-0.2071; 0.1837] 2.12 0.0%
## > 10 weeks 15 -0.0701 [-0.2444; 0.1042] 6.30 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.21 2 0.9021
## Within groups 9.62 40 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 9 -0.0635 [-0.3438; 0.2169] 0 0
## 5 - 10 weeks 19 -0.0117 [-0.2071; 0.1837] 0 0
## > 10 weeks 15 -0.0701 [-0.2444; 0.1042] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.21 2 0.9021
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0356)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 41) = 10.6587, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0016, p-val = 0.9685
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0546 0.1449 -0.3769 0.7062 -0.3386 0.2294
## duration 0.0006 0.0144 0.0395 0.9685 -0.0277 0.0288
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 < 0.5
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 > 0.5
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 < 0.5
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 > 0.5
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 > 0.5
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 > 0.5
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 > 0.5
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 > 0.5
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 > 0.5
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 > 0.5
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 < 0.5
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 < 0.5
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 < 0.5
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 < 0.5
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 > 0.5
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 > 0.5
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 > 0.5
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 > 0.5
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 > 0.5
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 < 0.5
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 < 0.5
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 > 0.5
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 < 0.5
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 < 0.5
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 > 0.5
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 > 0.5
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 < 0.5
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 < 0.5
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 > 0.5
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 < 0.5
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 > 0.5
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 > 0.5
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 < 0.5
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 > 0.5
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 < 0.5
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 < 0.5
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 > 0.5
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 > 0.5
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 > 0.5
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 < 0.5
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 < 0.5
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 < 0.5
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 < 0.5
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 20 -0.0370 [-0.2247; 0.1507] 5.99 0.0%
## > 0.5 23 -0.0546 [-0.2063; 0.0971] 3.82 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.02 1 0.8863
## Within groups 9.81 41 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 20 -0.0370 [-0.2247; 0.1507] 0 0
## > 0.5 23 -0.0546 [-0.2063; 0.0971] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.02 1 0.8863
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0356)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 41) = 10.6419, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0183, p-val = 0.8923
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0339 0.1297 -0.2610 0.7941 -0.2880 0.2203
## men_ratio -0.0244 0.1801 -0.1354 0.8923 -0.3775 0.3287
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 Running
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 Running
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 Cycling
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 Cycling
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 Cycling
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 Cycling
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 Running
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 Cycling
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 Cycling
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 Cycling
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 Cycling
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 Cycling
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 Cycling
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 Cycling
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 Running
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 Running
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 Cycling
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 Cycling
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 Running
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 Cycling
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 Cycling
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 Cycling
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 Cycling
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 Cycling
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 Cycling
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 Cycling
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 Running
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 Cycling
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 Cycling
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 Cycling
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 Running
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 Running
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 Cycling
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 Running
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 Running
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 Cycling
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 Cycling
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 Cycling
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 Cycling
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 Running
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 Cycling
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 Running
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 Cycling
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 13 -0.0345 [-0.2554; 0.1865] 4.21 0.0%
## Cycling 30 -0.0529 [-0.1925; 0.0867] 5.60 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.02 1 0.8900
## Within groups 9.81 41 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 13 -0.0345 [-0.2554; 0.1865] 0 0
## Cycling 30 -0.0529 [-0.1925; 0.0867] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.02 1 0.8900
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0355)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 41) = 10.6471, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0132, p-val = 0.9087
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0538 0.0712 -0.7552 0.4501 -0.1933 0.0858
## type_exerciseRunning 0.0153 0.1333 0.1147 0.9087 -0.2459 0.2765
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 BMI > 30 kg/m²
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 BMI > 30 kg/m²
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 BMI < 25 kg/m²
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 BMI < 25 kg/m²
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 BMI 25 - 30 kg/m²
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 BMI 25 - 30 kg/m²
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 BMI > 30 kg/m²
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 BMI 25 - 30 kg/m²
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 BMI 25 - 30 kg/m²
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 BMI 25 - 30 kg/m²
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 BMI < 25 kg/m²
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 BMI < 25 kg/m²
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 BMI < 25 kg/m²
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 BMI 25 - 30 kg/m²
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 BMI < 25 kg/m²
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 BMI < 25 kg/m²
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 BMI 25 - 30 kg/m²
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 BMI > 30 kg/m²
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 BMI < 25 kg/m²
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 BMI 25 - 30 kg/m²
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 BMI < 25 kg/m²
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 BMI < 25 kg/m²
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 BMI > 30 kg/m²
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 BMI > 30 kg/m²
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 BMI < 25 kg/m²
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 BMI 25 - 30 kg/m²
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 BMI 25 - 30 kg/m²
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 BMI 25 - 30 kg/m²
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 BMI < 25 kg/m²
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 BMI 25 - 30 kg/m²
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 BMI > 30 kg/m²
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 BMI > 30 kg/m²
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 BMI > 30 kg/m²
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 BMI 25 - 30 kg/m²
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 BMI < 25 kg/m²
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 BMI > 30 kg/m²
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 BMI < 25 kg/m²
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 BMI < 25 kg/m²
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 BMI > 30 kg/m²
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 BMI 25 - 30 kg/m²
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 BMI < 25 kg/m²
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 BMI > 30 kg/m²
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 BMI > 30 kg/m²
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## BMI < 25 kg/m² 16 -0.0233 [-0.2409; 0.1943] 1.86 0.0%
## BMI 25 - 30 kg/m² 14 -0.0662 [-0.2492; 0.1169] 1.24 0.0%
## BMI > 30 kg/m² 13 -0.0457 [-0.2647; 0.1733] 6.64 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.09 2 0.9571
## Within groups 9.74 40 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## BMI < 25 kg/m² 16 -0.0233 [-0.2409; 0.1943] 0 0
## BMI 25 - 30 kg/m² 14 -0.0662 [-0.2492; 0.1169] 0 0
## BMI > 30 kg/m² 13 -0.0457 [-0.2647; 0.1733] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.09 2 0.9571
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0351)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 41) = 10.5637, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0965, p-val = 0.7561
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1000 0.4849 0.2063 0.8365 -0.8503 1.0503
## bsln_adjusted -0.0054 0.0172 -0.3106 0.7561 -0.0392 0.0284
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Bækkerud 2016 0.0834 [-0.8694; 1.0362] 1.5 1.5 HIIT
## Beetham 2019 -0.7117 [-1.8362; 0.4129] 1.1 1.1 HIIT
## Burgomaster 2008 0.1633 [-0.7147; 1.0413] 1.8 1.8 SIT
## Cocks 2013 0.0000 [-0.9800; 0.9800] 1.4 1.4 SIT
## Conraads 2015 -0.1303 [-0.4278; 0.1673] 15.7 15.7 HIIT
## Currie 2015 -0.0220 [-0.9226; 0.8785] 1.7 1.7 HIIT
## Earnest 2013 0.1102 [-0.5407; 0.7611] 3.3 3.3 HIIT
## Eguchi 2012 0.0711 [-0.8057; 0.9479] 1.8 1.8 HIIT
## Fisher 2015 -0.1077 [-0.9327; 0.7173] 2.0 2.0 SIT
## Gillen 2016 -0.0859 [-0.9869; 0.8150] 1.7 1.7 SIT
## Gorostiaga 1991 0.2781 [-0.8590; 1.4151] 1.1 1.1 SIT
## Granata 2015 -0.0737 [-0.9549; 0.8075] 1.8 1.8 HIIT
## Granata 2015 -0.1189 [-1.0437; 0.8058] 1.6 1.6 SIT
## Grieco 2013 -0.1097 [-0.9495; 0.7302] 2.0 2.0 HIIT
## Helgerud 2007 -0.1347 [-1.0122; 0.7428] 1.8 1.8 HIIT
## Helgerud 2007 -0.2857 [-1.1667; 0.5953] 1.8 1.8 SIT
## Honkala 2017 (Healthy) 0.0925 [-0.6487; 0.8337] 2.5 2.5 SIT
## Honkala 2017 (T2D) 0.0204 [-0.9674; 1.0081] 1.4 1.4 SIT
## Jo 2020 -0.0456 [-0.7179; 0.6268] 3.1 3.1 HIIT
## Keating 2014 -0.2150 [-1.0532; 0.6231] 2.0 2.0 HIIT
## Klonizakis 2014 0.0572 [-0.8906; 1.0050] 1.5 1.5 HIIT
## Macpherson 2011 0.1198 [-0.7576; 0.9971] 1.8 1.8 SIT
## Maillard 2016 0.1024 [-0.8783; 1.0830] 1.4 1.4 HIIT
## Martins 2016 0.1874 [-0.5314; 0.9063] 2.7 2.7 SIT
## Matsuo 2014 -0.3160 [-1.0895; 0.4575] 2.3 2.3 HIIT
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 2.2 2.2 HIIT
## Mitranun 2014 0.2274 [-0.5158; 0.9705] 2.5 2.5 HIIT
## Moreira 2008 -0.0139 [-0.9939; 0.9661] 1.4 1.4 HIIT
## Nalcakan 2014 -0.0992 [-1.1142; 0.9158] 1.4 1.4 SIT
## Nie 2017 -0.0519 [-0.7693; 0.6655] 2.7 2.7 HIIT
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 3.9 3.9 HIIT
## Ramos 2016b 0.3042 [-0.3941; 1.0025] 2.9 2.9 HIIT
## Robinson 2015 -0.0622 [-0.6903; 0.5658] 3.5 3.5 HIIT
## Rognmo 2004 -0.1673 [-1.1213; 0.7867] 1.5 1.5 HIIT
## Sandvei 2012 -0.0307 [-0.8489; 0.7875] 2.1 2.1 SIT
## Sawyer 2016 0.0090 [-0.9149; 0.9330] 1.6 1.6 HIIT
## Scribbans 2014 0.0000 [-0.9005; 0.9005] 1.7 1.7 SIT
## Shepherd 2013 -0.0169 [-0.9969; 0.9631] 1.4 1.4 SIT
## Sjöros 2018 0.0162 [-0.8401; 0.8726] 1.9 1.9 SIT
## Tjønna 2008 -0.1325 [-1.0442; 0.7792] 1.7 1.7 HIIT
## Trapp 2008 0.2121 [-0.5056; 0.9298] 2.7 2.7 SIT
## Winn 2018 -0.5813 [-1.5818; 0.4191] 1.4 1.4 HIIT
## Zapata-Lamana 2018 -0.7184 [-1.4827; 0.0459] 2.4 2.4 HIIT
##
## Number of studies combined: k = 43
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
## Random effects model -0.0494 [-0.1674; 0.0686] -0.82 0.4117
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 10.66 42 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 26 -0.0817 [-0.2239; 0.0605] 7.62 0.0%
## SIT 17 0.0276 [-0.1838; 0.2389] 1.50 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.71 1 0.4004
## Within groups 9.12 41 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 26 -0.0817 [-0.2239; 0.0605] 0 0
## SIT 17 0.0276 [-0.1838; 0.2389] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.71 1 0.4004
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 43; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0354)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 41) = 9.9026, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.7576, p-val = 0.3841
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0847 0.0725 -1.1670 0.2432 -0.2268 0.0575
## HIIESIT 0.1131 0.1299 0.8704 0.3841 -0.1416 0.3678
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Beetham 2019 0.0382 [-0.1162; 0.1926] 0.6275 0.0000 0.0000 0.0%
## Omitting Burgomaster 2008 0.0481 [-0.1071; 0.2033] 0.5434 0.0000 0.0000 0.0%
## Omitting Earnest 2013 0.0274 [-0.1298; 0.1846] 0.7326 0.0000 0.0000 0.0%
## Omitting Eguchi 2012 0.0377 [-0.1176; 0.1929] 0.6342 0.0000 0.0000 0.0%
## Omitting Fisher 2015 0.0473 [-0.1082; 0.2029] 0.5509 0.0000 0.0000 0.0%
## Omitting Gillen 2016 0.0395 [-0.1156; 0.1946] 0.6176 0.0000 0.0000 0.0%
## Omitting Grieco 2013 0.0512 [-0.1042; 0.2066] 0.5183 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) 0.0364 [-0.1198; 0.1926] 0.6482 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) 0.0331 [-0.1216; 0.1878] 0.6752 0.0000 0.0000 0.0%
## Omitting Keating 2014 0.0441 [-0.1114; 0.1996] 0.5782 0.0000 0.0000 0.0%
## Omitting Lunt 2014 0.0397 [-0.1158; 0.1952] 0.6168 0.0000 0.0000 0.0%
## Omitting Lunt 2014 0.0327 [-0.1228; 0.1881] 0.6802 0.0000 0.0000 0.0%
## Omitting Macpherson 2011 0.0350 [-0.1202; 0.1902] 0.6587 0.0000 0.0000 0.0%
## Omitting Maillard 2016 0.0414 [-0.1134; 0.1961] 0.6002 0.0000 0.0000 0.0%
## Omitting Matsuo 2014 0.0501 [-0.1059; 0.2060] 0.5291 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 0.0370 [-0.1188; 0.1927] 0.6418 0.0000 0.0000 0.0%
## Omitting Mitranun 2014 0.0441 [-0.1121; 0.2003] 0.5801 0.0000 0.0000 0.0%
## Omitting Moreira 2008 0.0415 [-0.1133; 0.1962] 0.5994 0.0000 0.0000 0.0%
## Omitting Motiani 2017 0.0363 [-0.1197; 0.1923] 0.6484 0.0000 0.0000 0.0%
## Omitting Nalcakan 2014 0.0355 [-0.1191; 0.1901] 0.6527 0.0000 0.0000 0.0%
## Omitting Nie 2017 0.0342 [-0.1222; 0.1907] 0.6678 0.0000 0.0000 0.0%
## Omitting Ramos 2016a 0.0395 [-0.1186; 0.1976] 0.6246 0.0000 0.0000 0.0%
## Omitting Ramos 2016b 0.0338 [-0.1228; 0.1905] 0.6720 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 0.0432 [-0.1124; 0.1988] 0.5863 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 0.0357 [-0.1193; 0.1907] 0.6516 0.0000 0.0000 0.0%
## Omitting Sjöros 2018 0.0384 [-0.1169; 0.1938] 0.6278 0.0000 0.0000 0.0%
## Omitting Skleryk 2013 0.0294 [-0.1253; 0.1841] 0.7092 0.0000 0.0000 0.0%
## Omitting Trapp 2008 0.0152 [-0.1411; 0.1715] 0.8485 0.0000 0.0000 0.0%
## Omitting Winn 2018 0.0466 [-0.1081; 0.2013] 0.5552 0.0000 0.0000 0.0%
##
## Pooled estimate 0.0395 [-0.1133; 0.1923] 0.6121 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.0395 [-0.1133; 0.1923] Overall
## Healthy 0.0332 [-0.2027; 0.2691] Population
## Overweight/obese 0.0410 [-0.2346; 0.3166] Population
## Metabolic Syndrome 0.0692 [-0.3252; 0.4637] Population
## T2D 0.0114 [-0.4255; 0.4484] Population
## < 30 y -0.0067 [-0.2683; 0.2548] Age
## 30 - 50 y 0.0845 [-0.1492; 0.3181] Age
## > 50 y 0.0197 [-0.2987; 0.3381] Age
## < 5 weeks 0.0261 [-0.3014; 0.3536] Training Duration
## 5 - 10 weeks -0.0158 [-0.2733; 0.2417] Training Duration
## > 10 weeks 0.0890 [-0.1441; 0.3221] Training Duration
## < 0.5 -0.0052 [-0.2386; 0.2283] Men Ratio
## > 0.5 0.0711 [-0.1312; 0.2733] Men Ratio
## Running 0.0380 [-0.2182; 0.2942] Type of Exercise
## Cycling 0.0386 [-0.1519; 0.2290] Type of Exercise
## BMI < 25 kg/m² 0.0526 [-0.2886; 0.3937] Baseline Values
## BMI 25 - 30 kg/m² -0.0292 [-0.2740; 0.2156] Baseline Values
## BMI > 30 kg/m² 0.0958 [-0.1431; 0.3347] Baseline Values
## HIIT -0.0091 [-0.2096; 0.1914] Type of HIIE
## SIT 0.1042 [-0.1319; 0.3404] Type of HIIE
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0; tau = 0; I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Population 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Age 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Training Duration 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Men Ratio 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Type of Exercise 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Baseline Values 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
## Type of HIIE 29 0.0395 [-0.1133; 0.1923] 0 0 6.97 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 Overweight/obese
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 Healthy
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 Overweight/obese
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 Healthy
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 Overweight/obese
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 Healthy
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 Healthy
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 Healthy
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 T2D
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 Overweight/obese
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 Overweight/obese
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 Overweight/obese
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 Healthy
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 T2D
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 Healthy
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 Metabolic Syndrome
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 T2D
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 Overweight/obese
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 Healthy
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 Healthy
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 Healthy
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 Metabolic Syndrome
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 Metabolic Syndrome
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 Healthy
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 Overweight/obese
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 T2D
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 Overweight/obese
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 Healthy
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 Overweight/obese
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 12 0.0332 [-0.2027; 0.2691] 3.95 0.0%
## Overweight/obese 10 0.0410 [-0.2346; 0.3166] 2.06 0.0%
## Metabolic Syndrome 3 0.0692 [-0.3252; 0.4637] 0.05 0.0%
## T2D 4 0.0114 [-0.4255; 0.4484] 0.35 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.04 3 0.9979
## Within groups 6.41 25 0.9999
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 12 0.0332 [-0.2027; 0.2691] 0 0
## Overweight/obese 10 0.0410 [-0.2346; 0.3166] 0 0
## Metabolic Syndrome 3 0.0692 [-0.3252; 0.4637] 0 0
## T2D 4 0.0114 [-0.4255; 0.4484] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.04 3 0.9979
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0509)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 6.9254, p-val = 0.9999
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 0.0414, p-val = 0.9978
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0340 0.1203 0.2827 0.7774 -0.2018 0.2698
## .byvarOverweight/obese 0.0082 0.1850 0.0446 0.9644 -0.3544 0.3709
## .byvarMetabolic Syndrome 0.0371 0.2345 0.1584 0.8742 -0.4224 0.4967
## .byvarT2D -0.0211 0.2533 -0.0834 0.9336 -0.5176 0.4753
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 > 50 y
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 < 30 y
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 30 - 50 y
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 > 50 y
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 < 30 y
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 < 30 y
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 < 30 y
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 30 - 50 y
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 30 - 50 y
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 30 - 50 y
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 30 - 50 y
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 30 - 50 y
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 < 30 y
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 > 50 y
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 < 30 y
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 30 - 50 y
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 > 50 y
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 30 - 50 y
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 30 - 50 y
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 < 30 y
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 < 30 y
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 > 50 y
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 > 50 y
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 < 30 y
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 30 - 50 y
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 30 - 50 y
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 30 - 50 y
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 < 30 y
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 30 - 50 y
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 10 -0.0067 [-0.2683; 0.2548] 4.17 0.0%
## 30 - 50 y 13 0.0845 [-0.1492; 0.3181] 1.78 0.0%
## > 50 y 6 0.0197 [-0.2987; 0.3381] 0.23 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.28 2 0.8707
## Within groups 6.18 26 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 10 -0.0067 [-0.2683; 0.2548] 0 0
## 30 - 50 y 13 0.0845 [-0.1492; 0.3181] 0 0
## > 50 y 6 0.0197 [-0.2987; 0.3381] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.28 2 0.8707
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0483)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 6.9425, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0244, p-val = 0.8759
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0042 0.2395 0.0174 0.9861 -0.4652 0.4736
## age 0.0009 0.0055 0.1562 0.8759 -0.0100 0.0117
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 > 10 weeks
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 5 - 10 weeks
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 5 - 10 weeks
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 > 10 weeks
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 5 - 10 weeks
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 > 10 weeks
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 < 5 weeks
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 < 5 weeks
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 < 5 weeks
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 > 10 weeks
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 > 10 weeks
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 > 10 weeks
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 5 - 10 weeks
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 > 10 weeks
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 5 - 10 weeks
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 5 - 10 weeks
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 5 - 10 weeks
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 > 10 weeks
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 < 5 weeks
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 5 - 10 weeks
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 > 10 weeks
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 > 10 weeks
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 > 10 weeks
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 5 - 10 weeks
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 5 - 10 weeks
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 < 5 weeks
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 < 5 weeks
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 > 10 weeks
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 < 5 weeks
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 7 0.0261 [-0.3014; 0.3536] 1.96 0.0%
## 5 - 10 weeks 10 -0.0158 [-0.2733; 0.2417] 1.92 0.0%
## > 10 weeks 12 0.0890 [-0.1441; 0.3221] 2.22 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.36 2 0.8367
## Within groups 6.10 26 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 7 0.0261 [-0.3014; 0.3536] 0 0
## 5 - 10 weeks 10 -0.0158 [-0.2733; 0.2417] 0 0
## > 10 weeks 12 0.0890 [-0.1441; 0.3221] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.36 2 0.8367
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0484)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 6.8437, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1232, p-val = 0.7256
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0134 0.1698 -0.0789 0.9371 -0.3462 0.3194
## duration 0.0059 0.0168 0.3510 0.7256 -0.0271 0.0389
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 > 0.5
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 < 0.5
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 > 0.5
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 > 0.5
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 > 0.5
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 > 0.5
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 < 0.5
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 > 0.5
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 > 0.5
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 < 0.5
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 < 0.5
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 < 0.5
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 > 0.5
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 < 0.5
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 > 0.5
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 > 0.5
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 < 0.5
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 < 0.5
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 > 0.5
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 > 0.5
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 < 0.5
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 > 0.5
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 > 0.5
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 < 0.5
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 < 0.5
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 > 0.5
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 > 0.5
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 < 0.5
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 < 0.5
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 13 -0.0052 [-0.2386; 0.2283] 4.16 0.0%
## > 0.5 16 0.0711 [-0.1312; 0.2733] 2.06 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.23 1 0.6285
## Within groups 6.22 27 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 13 -0.0052 [-0.2386; 0.2283] 0 0
## > 0.5 16 0.0711 [-0.1312; 0.2733] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.23 1 0.6285
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0483)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 6.9652, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0017, p-val = 0.9676
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0455 0.1653 0.2750 0.7833 -0.2786 0.3695
## men_ratio -0.0094 0.2307 -0.0407 0.9676 -0.4616 0.4429
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 Running
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 Cycling
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 Running
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 Cycling
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 Cycling
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 Cycling
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 Cycling
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 Cycling
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 Cycling
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 Cycling
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 Running
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 Running
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 Cycling
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 Cycling
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 Cycling
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 Cycling
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 Running
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 Cycling
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 Cycling
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 Cycling
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 Cycling
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 Running
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 Running
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 Running
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 Cycling
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 Cycling
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 Cycling
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 Cycling
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 Running
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 9 0.0380 [-0.2182; 0.2942] 1.20 0.0%
## Cycling 20 0.0386 [-0.1519; 0.2290] 5.25 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.00 1 0.9972
## Within groups 6.45 27 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 9 0.0380 [-0.2182; 0.2942] 0 0
## Cycling 20 0.0386 [-0.1519; 0.2290] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.00 1 0.9972
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0484)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 6.9667, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0001, p-val = 0.9909
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0402 0.0971 0.4139 0.6790 -0.1502 0.2306
## type_exerciseRunning -0.0019 0.1628 -0.0114 0.9909 -0.3210 0.3173
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 BMI > 30 kg/m²
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 BMI < 25 kg/m²
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 BMI > 30 kg/m²
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 BMI 25 - 30 kg/m²
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 BMI 25 - 30 kg/m²
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 BMI 25 - 30 kg/m²
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 BMI 25 - 30 kg/m²
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 BMI 25 - 30 kg/m²
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 BMI > 30 kg/m²
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 BMI 25 - 30 kg/m²
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 BMI > 30 kg/m²
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 BMI > 30 kg/m²
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 BMI < 25 kg/m²
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 BMI > 30 kg/m²
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 BMI < 25 kg/m²
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 BMI 25 - 30 kg/m²
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 BMI 25 - 30 kg/m²
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 BMI 25 - 30 kg/m²
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 BMI 25 - 30 kg/m²
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 BMI < 25 kg/m²
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 BMI 25 - 30 kg/m²
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 BMI > 30 kg/m²
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 BMI > 30 kg/m²
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 BMI < 25 kg/m²
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 BMI > 30 kg/m²
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 BMI > 30 kg/m²
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 BMI > 30 kg/m²
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 BMI < 25 kg/m²
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 BMI > 30 kg/m²
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## BMI < 25 kg/m² 6 0.0526 [-0.2886; 0.3937] 3.07 0.0%
## BMI 25 - 30 kg/m² 11 -0.0292 [-0.2740; 0.2156] 1.28 0.0%
## BMI > 30 kg/m² 12 0.0958 [-0.1431; 0.3347] 1.58 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.52 2 0.7705
## Within groups 5.93 26 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## BMI < 25 kg/m² 6 0.0526 [-0.2886; 0.3937] 0 0
## BMI 25 - 30 kg/m² 11 -0.0292 [-0.2740; 0.2156] 0 0
## BMI > 30 kg/m² 12 0.0958 [-0.1431; 0.3347] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.52 2 0.7705
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0482)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 6.9094, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0574, p-val = 0.8106
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1011 0.5920 -0.1708 0.8644 -1.2613 1.0591
## bsln_adjusted 0.0049 0.0205 0.2397 0.8106 -0.0353 0.0452
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Beetham 2019 0.0493 [-1.0441; 1.1427] 2.0 2.0 HIIT
## Burgomaster 2008 -0.2887 [-1.1698; 0.5924] 3.0 3.0 SIT
## Earnest 2013 0.2324 [-0.4202; 0.8849] 5.5 5.5 HIIT
## Eguchi 2012 0.0631 [-0.8137; 0.9398] 3.0 3.0 HIIT
## Fisher 2015 -0.2232 [-1.0502; 0.6037] 3.4 3.4 SIT
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.9 2.9 SIT
## Grieco 2013 -0.3567 [-1.2024; 0.4891] 3.3 3.3 HIIT
## Honkala 2017 (Healthy) 0.0861 [-0.6551; 0.8272] 4.3 4.3 SIT
## Honkala 2017 (T2D) 0.2716 [-0.7206; 1.2638] 2.4 2.4 SIT
## Keating 2014 -0.1327 [-0.9694; 0.7039] 3.3 3.3 HIIT
## Lunt 2014 0.0000 [-0.8374; 0.8374] 3.3 3.3 HIIT
## Lunt 2014 0.2120 [-0.6277; 1.0516] 3.3 3.3 SIT
## Macpherson 2011 0.1534 [-0.7244; 1.0312] 3.0 3.0 SIT
## Maillard 2016 -0.0873 [-1.0678; 0.8931] 2.4 2.4 HIIT
## Matsuo 2014 -0.2568 [-1.0287; 0.5152] 3.9 3.9 HIIT
## Matsuo 2015 0.0783 [-0.7222; 0.8788] 3.6 3.6 HIIT
## Mitranun 2014 -0.0931 [-0.8343; 0.6481] 4.3 4.3 HIIT
## Moreira 2008 -0.0912 [-1.0717; 0.8893] 2.4 2.4 HIIT
## Motiani 2017 0.0919 [-0.6772; 0.8611] 3.9 3.9 SIT
## Nalcakan 2014 0.1726 [-0.8437; 1.1888] 2.3 2.3 SIT
## Nie 2017 0.1287 [-0.5893; 0.8467] 4.5 4.5 HIIT
## Ramos 2016a 0.0230 [-0.5749; 0.6210] 6.5 6.5 HIIT
## Ramos 2016b 0.1307 [-0.5643; 0.8258] 4.8 4.8 HIIT
## Sandvei 2012 -0.0990 [-0.9176; 0.7197] 3.5 3.5 SIT
## Sawyer 2016 0.1401 [-0.7849; 1.0652] 2.7 2.7 HIIT
## Sjöros 2018 0.0381 [-0.8184; 0.8945] 3.2 3.2 SIT
## Skleryk 2013 0.4302 [-0.5610; 1.4215] 2.4 2.4 SIT
## Trapp 2008 0.5592 [-0.1703; 1.2888] 4.4 4.4 SIT
## Winn 2018 -0.3125 [-1.2984; 0.6734] 2.4 2.4 HIIT
##
## Number of studies combined: k = 29
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
## Random effects model 0.0395 [-0.1133; 0.1923] 0.51 0.6121
##
## Quantifying heterogeneity:
## tau^2 = 0 [<0.0000; <0.0000]; tau = 0 [<0.0000; <0.0000];
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 0.0%]; H = 1.00 [1.00; 1.00]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.97 28 1.0000
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 16 -0.0091 [-0.2096; 0.1914] 2.43 0.0%
## SIT 13 0.1042 [-0.1319; 0.3404] 3.51 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.51 1 0.4733
## Within groups 5.94 27 1.0000
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 16 -0.0091 [-0.2096; 0.1914] 0 0
## SIT 13 0.1042 [-0.1319; 0.3404] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.51 1 0.4733
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 29; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0482)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 27) = 6.4006, p-val = 1.0000
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.5663, p-val = 0.4517
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0103 0.1023 -0.1006 0.9199 -0.2108 0.1902
## HIIESIT 0.1189 0.1580 0.7525 0.4517 -0.1908 0.4286
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Beetham 2019 -0.0180 [-0.2896; 0.2537] 0.8969 0.2967 0.5447 68.8%
## Omitting Ciolac 2010 -0.0282 [-0.3063; 0.2500] 0.8426 0.3114 0.5580 69.2%
## Omitting Cocks 2013 -0.0461 [-0.3207; 0.2284] 0.7419 0.3041 0.5514 69.2%
## Omitting Conraads 2015 0.0061 [-0.2519; 0.2641] 0.9632 0.2387 0.4886 59.3%
## Omitting Currie 2015 -0.0228 [-0.2974; 0.2517] 0.8705 0.3030 0.5504 69.0%
## Omitting Eguchi 2012 -0.0394 [-0.3154; 0.2367] 0.7797 0.3074 0.5545 69.3%
## Omitting Fisher 2015 -0.0260 [-0.3019; 0.2499] 0.8534 0.3063 0.5534 69.1%
## Omitting Honkala 2017 (Healthy) -0.0623 [-0.3356; 0.2109] 0.6547 0.2959 0.5439 68.2%
## Omitting Honkala 2017 (T2D) 0.0109 [-0.2479; 0.2698] 0.9340 0.2563 0.5063 65.6%
## Omitting Jo 2020 -0.0337 [-0.3127; 0.2453] 0.8131 0.3139 0.5603 69.3%
## Omitting Keating 2014 -0.0477 [-0.3235; 0.2282] 0.7348 0.3060 0.5532 69.1%
## Omitting Keteyian 2014 -0.0783 [-0.3437; 0.1871] 0.5631 0.2709 0.5205 66.4%
## Omitting Klonizakis 2014 -0.0610 [-0.3327; 0.2107] 0.6598 0.2944 0.5426 68.5%
## Omitting Lunt 2014 -0.0321 [-0.3085; 0.2443] 0.8198 0.3080 0.5549 69.3%
## Omitting Lunt 2014 -0.0461 [-0.3221; 0.2299] 0.7434 0.3067 0.5538 69.2%
## Omitting Matsuo 2014 -0.0483 [-0.3249; 0.2282] 0.7319 0.3073 0.5544 69.1%
## Omitting Matsuo 2015 -0.0467 [-0.3231; 0.2296] 0.7403 0.3073 0.5543 69.1%
## Omitting Mitranun 2014 -0.0698 [-0.3398; 0.2003] 0.6125 0.2856 0.5345 67.5%
## Omitting Molmen-Hansen 2011 -0.1035 [-0.3427; 0.1358] 0.3967 0.1871 0.4326 56.8%
## Omitting Ramos 2016a -0.0041 [-0.2765; 0.2683] 0.9764 0.2907 0.5392 67.4%
## Omitting Ramos 2016b 0.0057 [-0.2609; 0.2722] 0.9668 0.2738 0.5233 66.5%
## Omitting Rognmo 2004 -0.0456 [-0.3204; 0.2293] 0.7452 0.3047 0.5520 69.2%
## Omitting Skleryk 2013 -0.0442 [-0.3190; 0.2305] 0.7525 0.3047 0.5520 69.2%
## Omitting Tjønna 2008 -0.0369 [-0.3127; 0.2388] 0.7928 0.3069 0.5540 69.3%
## Omitting Wegmann 2018 -0.0611 [-0.3371; 0.2148] 0.6642 0.3016 0.5492 68.0%
##
## Pooled estimate -0.0441 [-0.3174; 0.2291] 0.7515 0.3170 0.5630 69.7%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.0441 [-0.3174; 0.2291] Overall
## Healthy 0.2051 [-0.0834; 0.4936] Population
## Overweight/obese 0.0992 [-0.4309; 0.6293] Population
## Cardiac Rehabilitation -0.0747 [-0.8639; 0.7146] Population
## Metabolic Syndrome -0.4178 [-0.8400; 0.0044] Population
## T2D -0.5561 [-3.0617; 1.9495] Population
## < 30 y -0.1103 [-0.5111; 0.2906] Age
## 30 - 50 y 0.0355 [-0.3531; 0.4241] Age
## > 50 y -0.0435 [-0.4766; 0.3897] Age
## < 5 weeks -0.1006 [-1.0594; 0.8581] Training Duration
## 5 - 10 weeks 0.2030 [-0.0924; 0.4985] Training Duration
## > 10 weeks -0.1791 [-0.5602; 0.2019] Training Duration
## < 0.5 0.1745 [-0.0986; 0.4476] Men Ratio
## > 0.5 -0.1396 [-0.4987; 0.2195] Men Ratio
## Running 0.0300 [-0.3581; 0.4180] Type of Exercise
## Cycling -0.1261 [-0.4753; 0.2231] Type of Exercise
## < 120 mmHg 0.0128 [-0.3886; 0.4142] Baseline Values
## 120 - 140 mmHg -0.1525 [-0.4535; 0.1484] Baseline Values
## > 140 mmHg 0.5533 [-0.2326; 1.3392] Baseline Values
## HIIT -0.0103 [-0.3188; 0.2982] Type of HIIE
## SIT -0.1406 [-0.7051; 0.4240] Type of HIIE
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170; tau = 0.5630; I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Population 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Age 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Training Duration 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Men Ratio 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Type of Exercise 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Baseline Values 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
## Type of HIIE 25 -0.0441 [-0.3174; 0.2291] 0.3170 0.5630 79.32 69.7%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 Overweight/obese
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 Healthy
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 Healthy
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 Cardiac Rehabilitation
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 Cardiac Rehabilitation
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 Healthy
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 Overweight/obese
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 Healthy
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 T2D
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 Metabolic Syndrome
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 Overweight/obese
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 Cardiac Rehabilitation
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 Healthy
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 Overweight/obese
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 Overweight/obese
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 Healthy
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 Metabolic Syndrome
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 T2D
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 Overweight/obese
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 Metabolic Syndrome
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 Metabolic Syndrome
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 Cardiac Rehabilitation
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 Overweight/obese
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 Metabolic Syndrome
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 Healthy
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 63.2% [41.2%; 77.0%]; H = 1.65 [1.30; 2.08]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 7 0.2051 [-0.0834; 0.4936] 3.74 0.0%
## Overweight/obese 7 0.2675 [-0.0376; 0.5727] 16.96 64.6%
## Cardiac Rehabilitation 4 -0.4409 [-0.7029; -0.1788] 15.32 80.4%
## Metabolic Syndrome 5 -0.4371 [-0.7639; -0.1103] 6.52 38.7%
## T2D 2 -0.0296 [-0.6808; 0.6216] 11.83 91.5%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 20.49 4 0.0004
## Within groups 54.38 20 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 7 0.2051 [-0.0834; 0.4936] 0 0
## Overweight/obese 7 0.0992 [-0.4309; 0.6293] 0.3222 0.5676
## Cardiac Rehabilitation 4 -0.0747 [-0.8639; 0.7146] 0.5003 0.7073
## Metabolic Syndrome 5 -0.4178 [-0.8400; 0.0044] 0.0893 0.2988
## T2D 2 -0.5561 [-3.0617; 1.9495] 2.9966 1.7311
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 6.05 4 0.1954
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.2959 (SE = 0.1480)
## tau (square root of estimated tau^2 value): 0.5439
## I^2 (residual heterogeneity / unaccounted variability): 65.73%
## H^2 (unaccounted variability / sampling variability): 2.92
## R^2 (amount of heterogeneity accounted for): 6.66%
##
## Test for Residual Heterogeneity:
## QE(df = 20) = 58.3624, p-val < .0001
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 3.2489, p-val = 0.5171
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2096 0.2567 0.8164 0.4143 -0.2935 0.7126
## .byvarOverweight/obese -0.1105 0.3676 -0.3007 0.7637 -0.8309 0.6099
## .byvarCardiac Rehabilitation -0.3052 0.4186 -0.7290 0.4660 -1.1256 0.5152
## .byvarMetabolic Syndrome -0.6221 0.3926 -1.5848 0.1130 -1.3915 0.1473
## .byvarT2D -0.5870 0.5786 -1.0145 0.3103 -1.7209 0.5470
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 > 50 y
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 < 30 y
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 < 30 y
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 > 50 y
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 > 50 y
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 > 50 y
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 < 30 y
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 30 - 50 y
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 30 - 50 y
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 > 50 y
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 30 - 50 y
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 > 50 y
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 > 50 y
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 30 - 50 y
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 30 - 50 y
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 < 30 y
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 30 - 50 y
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 > 50 y
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 > 50 y
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 > 50 y
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 > 50 y
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 > 50 y
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 30 - 50 y
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 > 50 y
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 30 - 50 y
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 69.4% [53.2%; 80.1%]; H = 1.81 [1.46; 2.24]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 4 -0.1103 [-0.5111; 0.2906] 1.39 0.0%
## 30 - 50 y 8 0.1005 [-0.1836; 0.3847] 12.41 43.6%
## > 50 y 13 -0.1907 [-0.3720; -0.0094] 58.21 79.4%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 2.87 2 0.2383
## Within groups 72.01 22 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 4 -0.1103 [-0.5111; 0.2906] 0 0
## 30 - 50 y 8 0.0355 [-0.3531; 0.4241] 0.1335 0.3654
## > 50 y 13 -0.0435 [-0.4766; 0.3897] 0.4727 0.6876
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.26 2 0.8769
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3372 (SE = 0.1593)
## tau (square root of estimated tau^2 value): 0.5807
## I^2 (residual heterogeneity / unaccounted variability): 70.74%
## H^2 (unaccounted variability / sampling variability): 3.42
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 78.6179, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0130, p-val = 0.9092
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1085 0.5773 -0.1880 0.8509 -1.2400 1.0229
## age 0.0013 0.0115 0.1141 0.9092 -0.0211 0.0237
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 > 10 weeks
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 > 10 weeks
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 5 - 10 weeks
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 > 10 weeks
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 > 10 weeks
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 > 10 weeks
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 5 - 10 weeks
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 < 5 weeks
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 < 5 weeks
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 5 - 10 weeks
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 > 10 weeks
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 5 - 10 weeks
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 < 5 weeks
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 > 10 weeks
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 > 10 weeks
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 5 - 10 weeks
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 5 - 10 weeks
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 5 - 10 weeks
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 > 10 weeks
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 > 10 weeks
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 > 10 weeks
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 5 - 10 weeks
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 < 5 weeks
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 > 10 weeks
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 > 10 weeks
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 67.2% [49.4%; 78.8%]; H = 1.75 [1.41; 2.17]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 4 0.0782 [-0.3928; 0.5491] 11.76 74.5%
## 5 - 10 weeks 8 0.2024 [-0.0820; 0.4869] 7.52 7.0%
## > 10 weeks 13 -0.2517 [-0.4280; -0.0754] 47.86 74.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 7.73 2 0.0210
## Within groups 67.15 22 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 4 -0.1006 [-1.0594; 0.8581] 0.7041 0.8391
## 5 - 10 weeks 8 0.2030 [-0.0924; 0.4985] 0.0127 0.1127
## > 10 weeks 13 -0.1791 [-0.5602; 0.2019] 0.3428 0.5855
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.51 2 0.2845
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3355 (SE = 0.1623)
## tau (square root of estimated tau^2 value): 0.5792
## I^2 (residual heterogeneity / unaccounted variability): 70.80%
## H^2 (unaccounted variability / sampling variability): 3.42
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 78.7742, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0899, p-val = 0.7643
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0429 0.3249 0.1321 0.8949 -0.5939 0.6797
## duration -0.0082 0.0274 -0.2999 0.7643 -0.0618 0.0454
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 > 0.5
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 < 0.5
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 > 0.5
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 > 0.5
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 > 0.5
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 > 0.5
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 > 0.5
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 > 0.5
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 > 0.5
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 > 0.5
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 < 0.5
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 > 0.5
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 < 0.5
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 < 0.5
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 < 0.5
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 > 0.5
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 > 0.5
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 < 0.5
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 > 0.5
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 > 0.5
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 > 0.5
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 > 0.5
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 > 0.5
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 < 0.5
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 < 0.5
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 66.8% [49.1%; 78.3%]; H = 1.74 [1.40; 2.15]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 8 0.1745 [-0.0986; 0.4476] 5.75 0.0%
## > 0.5 17 -0.2129 [-0.3804; -0.0453] 63.51 74.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 5.62 1 0.0178
## Within groups 69.26 23 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 8 0.1745 [-0.0986; 0.4476] 0 0
## > 0.5 17 -0.1396 [-0.4987; 0.2195] 0.3969 0.6300
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.86 1 0.1724
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.2990 (SE = 0.1450)
## tau (square root of estimated tau^2 value): 0.5468
## I^2 (residual heterogeneity / unaccounted variability): 68.08%
## H^2 (unaccounted variability / sampling variability): 3.13
## R^2 (amount of heterogeneity accounted for): 5.67%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 72.0471, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.0888, p-val = 0.2967
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2588 0.3205 0.8076 0.4193 -0.3694 0.8870
## men_ratio -0.4537 0.4349 -1.0434 0.2967 -1.3060 0.3986
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 Running
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 Running
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 Cycling
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 Cycling
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 Cycling
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 Cycling
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 Cycling
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 Cycling
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 Cycling
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 Running
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 Cycling
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 Running
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 Cycling
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 Running
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 Running
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 Cycling
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 Cycling
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 Running
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 Running
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 Running
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 Running
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 Running
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 Cycling
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 Running
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 Running
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 66.1% [48.0%; 77.9%]; H = 1.72 [1.39; 2.13]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 13 0.0880 [-0.1151; 0.2911] 42.07 71.5%
## Cycling 12 -0.2975 [-0.4983; -0.0967] 25.81 57.4%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 7.00 1 0.0082
## Within groups 67.88 23 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 13 0.0300 [-0.3581; 0.4180] 0.3542 0.5952
## Cycling 12 -0.1261 [-0.4753; 0.2231] 0.1983 0.4453
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.34 1 0.5578
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3067 (SE = 0.1456)
## tau (square root of estimated tau^2 value): 0.5538
## I^2 (residual heterogeneity / unaccounted variability): 68.12%
## H^2 (unaccounted variability / sampling variability): 3.14
## R^2 (amount of heterogeneity accounted for): 3.23%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 72.1374, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3359, p-val = 0.5622
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1299 0.2027 -0.6410 0.5215 -0.5271 0.2673
## type_exerciseRunning 0.1603 0.2766 0.5795 0.5622 -0.3818 0.7025
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 120 - 140 mmHg
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 < 120 mmHg
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 < 120 mmHg
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 120 - 140 mmHg
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 120 - 140 mmHg
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 120 - 140 mmHg
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 120 - 140 mmHg
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 120 - 140 mmHg
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 120 - 140 mmHg
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 120 - 140 mmHg
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 < 120 mmHg
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 120 - 140 mmHg
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 120 - 140 mmHg
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 120 - 140 mmHg
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 120 - 140 mmHg
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 < 120 mmHg
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 120 - 140 mmHg
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 120 - 140 mmHg
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 > 140 mmHg
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 120 - 140 mmHg
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 120 - 140 mmHg
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 > 140 mmHg
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 > 140 mmHg
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 120 - 140 mmHg
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 120 - 140 mmHg
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 61.1% [38.7%; 75.3%]; H = 1.60 [1.28; 2.01]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 120 mmHg 4 0.0128 [-0.3886; 0.4142] 1.07 0.0%
## 120 - 140 mmHg 18 -0.2494 [-0.4128; -0.0861] 49.89 65.9%
## > 140 mmHg 3 0.7500 [ 0.3182; 1.1818] 5.53 63.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 18.39 2 0.0001
## Within groups 56.48 22 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 120 mmHg 4 0.0128 [-0.3886; 0.4142] 0 0
## 120 - 140 mmHg 18 -0.1525 [-0.4535; 0.1484] 0.2582 0.5082
## > 140 mmHg 3 0.5533 [-0.2326; 1.3392] 0.3064 0.5535
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.79 2 0.2475
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3001 (SE = 0.1486)
## tau (square root of estimated tau^2 value): 0.5478
## I^2 (residual heterogeneity / unaccounted variability): 68.21%
## H^2 (unaccounted variability / sampling variability): 3.15
## R^2 (amount of heterogeneity accounted for): 5.33%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 72.3477, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1857, p-val = 0.6665
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.8264 1.8215 -0.4537 0.6500 -4.3965 2.7436
## bsln_adjusted 0.0061 0.0140 0.4310 0.6665 -0.0215 0.0336
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Beetham 2019 -0.7906 [-1.9223; 0.3412] 1.6 3.0 HIIT
## Ciolac 2010 -0.2950 [-0.9917; 0.4017] 4.2 4.4 HIIT
## Cocks 2013 0.1605 [-0.8210; 1.1421] 2.1 3.4 SIT
## Conraads 2015 -0.7030 [-1.0092; -0.3967] 21.7 5.7 HIIT
## Currie 2015 -0.5007 [-1.4152; 0.4138] 2.4 3.6 HIIT
## Eguchi 2012 -0.0434 [-0.9201; 0.8332] 2.6 3.8 HIIT
## Fisher 2015 -0.3829 [-1.2147; 0.4489] 2.9 3.9 SIT
## Honkala 2017 (Healthy) 0.5052 [-0.2473; 1.2577] 3.6 4.2 SIT
## Honkala 2017 (T2D) -1.9928 [-3.1979; -0.7876] 1.4 2.8 SIT
## Jo 2020 -0.1714 [-0.8449; 0.5021] 4.5 4.5 HIIT
## Keating 2014 0.1702 [-0.6671; 1.0074] 2.9 3.9 HIIT
## Keteyian 2014 0.9259 [ 0.1446; 1.7072] 3.3 4.1 HIIT
## Klonizakis 2014 0.6056 [-0.3625; 1.5736] 2.2 3.5 HIIT
## Lunt 2014 -0.2297 [-1.0697; 0.6103] 2.9 3.9 HIIT
## Lunt 2014 0.1292 [-0.7090; 0.9674] 2.9 3.9 SIT
## Matsuo 2014 0.1719 [-0.5983; 0.9421] 3.4 4.1 HIIT
## Matsuo 2015 0.1389 [-0.6622; 0.9401] 3.2 4.0 HIIT
## Mitranun 2014 0.6948 [-0.0680; 1.4576] 3.5 4.2 HIIT
## Molmen-Hansen 2011 1.1876 [ 0.6324; 1.7428] 6.6 4.9 HIIT
## Ramos 2016a -0.7593 [-1.3784; -0.1402] 5.3 4.7 HIIT
## Ramos 2016b -1.0655 [-1.8073; -0.3237] 3.7 4.2 HIIT
## Rognmo 2004 0.1380 [-0.8155; 1.0915] 2.2 3.5 HIIT
## Skleryk 2013 0.1021 [-0.8786; 1.0827] 2.1 3.4 SIT
## Tjønna 2008 -0.1108 [-1.0222; 0.8006] 2.4 3.6 HIIT
## Wegmann 2018 0.3909 [-0.1755; 0.9572] 6.3 4.9 HIIT
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1092 [-0.2518; 0.0333] -1.50 0.1331
## Random effects model -0.0441 [-0.3174; 0.2291] -0.32 0.7515
##
## Quantifying heterogeneity:
## tau^2 = 0.3170 [0.1073; 0.7008]; tau = 0.5630 [0.3275; 0.8372];
## I^2 = 69.7% [54.5%; 79.9%]; H = 1.82 [1.48; 2.23]
##
## Quantifying residual heterogeneity:
## I^2 = 69.3% [53.3%; 79.8%]; H = 1.80 [1.46; 2.22]
##
## Test of heterogeneity:
## Q d.f. p-value
## 79.32 24 < 0.0001
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 19 -0.1149 [-0.2697; 0.0400] 63.47 71.6%
## SIT 6 -0.0621 [-0.4309; 0.3067] 11.34 55.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.07 1 0.7960
## Within groups 74.81 23 < 0.0001
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 19 -0.0103 [-0.3188; 0.2982] 0.3157 0.5619
## SIT 6 -0.1406 [-0.7051; 0.4240] 0.2739 0.5234
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.16 1 0.6915
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.3355 (SE = 0.1604)
## tau (square root of estimated tau^2 value): 0.5792
## I^2 (residual heterogeneity / unaccounted variability): 70.99%
## H^2 (unaccounted variability / sampling variability): 3.45
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 79.2913, p-val < .0001
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.2043, p-val = 0.6513
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0108 0.1607 -0.0674 0.9462 -0.3257 0.3040
## HIIESIT -0.1558 0.3447 -0.4520 0.6513 -0.8314 0.5198
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Beetham 2019 0.0570 [-0.1457; 0.2598] 0.5814 0.1036 0.3218 44.0%
## Omitting Ciolac 2010 0.0262 [-0.1900; 0.2423] 0.8126 0.1297 0.3601 48.8%
## Omitting Cocks 2013 0.0356 [-0.1773; 0.2486] 0.7428 0.1259 0.3548 48.7%
## Omitting Conraads 2015 0.0642 [-0.1459; 0.2743] 0.5490 0.1052 0.3244 39.5%
## Omitting Currie 2015 0.0693 [-0.1267; 0.2653] 0.4886 0.0867 0.2945 39.6%
## Omitting Eguchi 2012 0.0293 [-0.1849; 0.2435] 0.7884 0.1277 0.3573 48.9%
## Omitting Fisher 2015 0.0610 [-0.1445; 0.2665] 0.5607 0.1066 0.3265 44.4%
## Omitting Honkala 2017 (Healthy) 0.0156 [-0.1982; 0.2294] 0.8865 0.1247 0.3532 48.0%
## Omitting Honkala 2017 (T2D) 0.0197 [-0.1926; 0.2320] 0.8558 0.1245 0.3528 48.4%
## Omitting Jo 2020 0.0372 [-0.1788; 0.2533] 0.7355 0.1291 0.3593 48.6%
## Omitting Keating 2014 0.0342 [-0.1801; 0.2486] 0.7543 0.1275 0.3571 48.8%
## Omitting Keteyian 2014 -0.0121 [-0.2080; 0.1838] 0.9038 0.0841 0.2900 38.5%
## Omitting Klonizakis 2014 0.0386 [-0.1741; 0.2514] 0.7219 0.1251 0.3537 48.5%
## Omitting Lunt 2014 0.0211 [-0.1928; 0.2350] 0.8468 0.1264 0.3556 48.6%
## Omitting Lunt 2014 0.0120 [-0.1995; 0.2236] 0.9111 0.1208 0.3475 47.4%
## Omitting Matsuo 2014 0.0136 [-0.1993; 0.2265] 0.9004 0.1230 0.3506 47.7%
## Omitting Matsuo 2015 0.0112 [-0.2004; 0.2228] 0.9174 0.1205 0.3472 47.3%
## Omitting Mitranun 2014 0.0460 [-0.1673; 0.2592] 0.6728 0.1235 0.3514 47.8%
## Omitting Molmen-Hansen 2011 -0.0240 [-0.2152; 0.1671] 0.8053 0.0689 0.2625 32.9%
## Omitting Ramos 2016a 0.0382 [-0.1790; 0.2554] 0.7302 0.1304 0.3611 48.6%
## Omitting Ramos 2016b 0.0175 [-0.1974; 0.2324] 0.8731 0.1266 0.3558 48.2%
## Omitting Rognmo 2004 0.0338 [-0.1795; 0.2472] 0.7561 0.1266 0.3558 48.8%
## Omitting Skleryk 2013 0.0211 [-0.1916; 0.2337] 0.8460 0.1252 0.3538 48.5%
## Omitting Tjønna 2008 0.0293 [-0.1846; 0.2432] 0.7884 0.1274 0.3569 48.9%
## Omitting Wegmann 2018 0.0191 [-0.1984; 0.2366] 0.8632 0.1304 0.3612 48.4%
##
## Pooled estimate 0.0254 [-0.1884; 0.2391] 0.8161 0.1369 0.3700 50.4%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.0254 [-0.1884; 0.2391] Overall
## Healthy 0.1168 [-0.1703; 0.4039] Population
## Overweight/obese 0.0270 [-0.5167; 0.5707] Population
## Cardiac Rehabilitation -0.1620 [-0.9985; 0.6745] Population
## Metabolic Syndrome 0.0471 [-0.2729; 0.3671] Population
## T2D -0.1080 [-0.7572; 0.5412] Population
## < 30 y -0.1078 [-0.6101; 0.3945] Age
## 30 - 50 y 0.2543 [-0.0260; 0.5345] Age
## > 50 y -0.0763 [-0.4131; 0.2605] Age
## < 5 weeks 0.1733 [-0.2769; 0.6236] Training Duration
## 5 - 10 weeks 0.0438 [-0.3705; 0.4582] Training Duration
## > 10 weeks -0.0169 [-0.3126; 0.2789] Training Duration
## < 0.5 0.0397 [-0.2318; 0.3113] Men Ratio
## > 0.5 0.0211 [-0.2702; 0.3124] Men Ratio
## Running 0.1490 [-0.1282; 0.4262] Type of Exercise
## Cycling -0.1186 [-0.3988; 0.1617] Type of Exercise
## < 80 mmHg -0.1640 [-0.4587; 0.1306] Baseline Values
## 80 - 90 mmHg 0.1423 [-0.1203; 0.4049] Baseline Values
## > 90 mmHg 0.4612 [-0.0590; 0.9814] Baseline Values
## HIIT 0.0190 [-0.2230; 0.2611] Type of HIIE
## SIT 0.0624 [-0.3422; 0.4671] Type of HIIE
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369; tau = 0.3700; I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Population 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Age 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Training Duration 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Men Ratio 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Type of Exercise 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Baseline Values 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
## Type of HIIE 25 0.0254 [-0.1884; 0.2391] 0.1369 0.3700 48.37 50.4%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 Overweight/obese
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 Healthy
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 Healthy
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 Cardiac Rehabilitation
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 Cardiac Rehabilitation
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 Healthy
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 Overweight/obese
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 Healthy
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 T2D
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 Metabolic Syndrome
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 Overweight/obese
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 Cardiac Rehabilitation
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 Healthy
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 Overweight/obese
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 Overweight/obese
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 Healthy
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 Metabolic Syndrome
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 T2D
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 Overweight/obese
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 Metabolic Syndrome
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 Metabolic Syndrome
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 Cardiac Rehabilitation
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 Overweight/obese
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 Metabolic Syndrome
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 Healthy
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 48.6% [14.7%; 69.0%]; H = 1.39 [1.08; 1.80]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 7 0.1168 [-0.1703; 0.4039] 1.97 0.0%
## Overweight/obese 7 0.1966 [-0.1086; 0.5018] 17.52 65.8%
## Cardiac Rehabilitation 4 -0.2529 [-0.5135; 0.0076] 16.06 81.3%
## Metabolic Syndrome 5 0.0471 [-0.2729; 0.3671] 2.18 0.0%
## T2D 2 -0.1207 [-0.7188; 0.4774] 1.15 13.3%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 6.09 4 0.1926
## Within groups 38.89 20 0.0069
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 7 0.1168 [-0.1703; 0.4039] 0 0
## Overweight/obese 7 0.0270 [-0.5167; 0.5707] 0.3427 0.5854
## Cardiac Rehabilitation 4 -0.1620 [-0.9985; 0.6745] 0.5666 0.7527
## Metabolic Syndrome 5 0.0471 [-0.2729; 0.3671] 0 0
## T2D 2 -0.1080 [-0.7572; 0.5412] 0.0311 0.1763
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.69 4 0.9527
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1703 (SE = 0.1049)
## tau (square root of estimated tau^2 value): 0.4127
## I^2 (residual heterogeneity / unaccounted variability): 52.64%
## H^2 (unaccounted variability / sampling variability): 2.11
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 20) = 42.2257, p-val = 0.0026
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 0.6651, p-val = 0.9556
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0948 0.2177 0.4356 0.6631 -0.3318 0.5214
## .byvarOverweight/obese -0.0390 0.3141 -0.1242 0.9012 -0.6547 0.5766
## .byvarCardiac Rehabilitation -0.2574 0.3536 -0.7280 0.4666 -0.9503 0.4356
## .byvarMetabolic Syndrome -0.0233 0.3306 -0.0704 0.9438 -0.6713 0.6248
## .byvarT2D -0.1705 0.4786 -0.3563 0.7216 -1.1085 0.7675
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 > 50 y
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 < 30 y
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 < 30 y
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 > 50 y
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 > 50 y
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 > 50 y
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 < 30 y
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 30 - 50 y
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 30 - 50 y
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 > 50 y
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 30 - 50 y
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 > 50 y
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 > 50 y
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 30 - 50 y
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 30 - 50 y
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 < 30 y
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 30 - 50 y
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 > 50 y
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 > 50 y
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 > 50 y
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 > 50 y
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 > 50 y
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 30 - 50 y
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 > 50 y
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 30 - 50 y
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 45.9% [11.8%; 66.8%]; H = 1.36 [1.06; 1.74]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 4 -0.0882 [-0.4930; 0.3165] 4.52 33.6%
## 30 - 50 y 8 0.2543 [-0.0260; 0.5345] 1.42 0.0%
## > 50 y 13 -0.0886 [-0.2673; 0.0901] 34.75 65.5%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 4.29 2 0.1171
## Within groups 40.69 22 0.0090
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 4 -0.1078 [-0.6101; 0.3945] 0.0884 0.2972
## 30 - 50 y 8 0.2543 [-0.0260; 0.5345] 0 0
## > 50 y 13 -0.0763 [-0.4131; 0.2605] 0.2274 0.4769
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.85 2 0.2406
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1457 (SE = 0.0897)
## tau (square root of estimated tau^2 value): 0.3817
## I^2 (residual heterogeneity / unaccounted variability): 51.57%
## H^2 (unaccounted variability / sampling variability): 2.06
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 47.4925, p-val = 0.0019
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1318, p-val = 0.7166
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1870 0.4603 0.4061 0.6846 -0.7153 1.0892
## age -0.0033 0.0091 -0.3630 0.7166 -0.0212 0.0146
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 > 10 weeks
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 > 10 weeks
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 5 - 10 weeks
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 > 10 weeks
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 > 10 weeks
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 > 10 weeks
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 5 - 10 weeks
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 < 5 weeks
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 < 5 weeks
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 5 - 10 weeks
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 > 10 weeks
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 5 - 10 weeks
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 < 5 weeks
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 > 10 weeks
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 > 10 weeks
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 5 - 10 weeks
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 5 - 10 weeks
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 5 - 10 weeks
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 > 10 weeks
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 > 10 weeks
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 > 10 weeks
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 5 - 10 weeks
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 < 5 weeks
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 > 10 weeks
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 > 10 weeks
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 50.0% [19.2%; 69.1%]; H = 1.41 [1.11; 1.80]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 4 0.1733 [-0.2769; 0.6236] 1.15 0.0%
## 5 - 10 weeks 8 0.0481 [-0.2387; 0.3348] 14.36 51.3%
## > 10 weeks 13 -0.0458 [-0.2197; 0.1281] 28.52 57.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.94 2 0.6239
## Within groups 44.03 22 0.0035
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 4 0.1733 [-0.2769; 0.6236] 0 0
## 5 - 10 weeks 8 0.0438 [-0.3705; 0.4582] 0.1815 0.4260
## > 10 weeks 13 -0.0169 [-0.3126; 0.2789] 0.1546 0.3931
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.48 2 0.7869
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1496 (SE = 0.0923)
## tau (square root of estimated tau^2 value): 0.3868
## I^2 (residual heterogeneity / unaccounted variability): 52.44%
## H^2 (unaccounted variability / sampling variability): 2.10
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 48.3620, p-val = 0.0015
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0005, p-val = 0.9822
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0193 0.2556 0.0757 0.9397 -0.4816 0.5202
## duration 0.0005 0.0212 0.0223 0.9822 -0.0411 0.0420
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 > 0.5
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 < 0.5
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 > 0.5
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 > 0.5
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 > 0.5
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 > 0.5
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 > 0.5
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 > 0.5
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 > 0.5
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 > 0.5
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 < 0.5
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 > 0.5
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 < 0.5
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 < 0.5
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 < 0.5
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 > 0.5
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 > 0.5
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 < 0.5
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 > 0.5
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 > 0.5
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 > 0.5
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 > 0.5
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 > 0.5
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 < 0.5
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 < 0.5
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 48.7% [17.7%; 68.1%]; H = 1.40 [1.10; 1.77]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 8 0.0397 [-0.2318; 0.3113] 3.16 0.0%
## > 0.5 17 -0.0168 [-0.1821; 0.1485] 41.70 61.6%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.12 1 0.7275
## Within groups 44.86 23 0.0041
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 8 0.0397 [-0.2318; 0.3113] 0 0
## > 0.5 17 0.0211 [-0.2702; 0.3124] 0.2099 0.4582
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.01 1 0.9268
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1470 (SE = 0.0901)
## tau (square root of estimated tau^2 value): 0.3834
## I^2 (residual heterogeneity / unaccounted variability): 51.63%
## H^2 (unaccounted variability / sampling variability): 2.07
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 47.5541, p-val = 0.0019
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0167, p-val = 0.8972
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0551 0.2607 0.2115 0.8325 -0.4559 0.5662
## men_ratio -0.0459 0.3554 -0.1292 0.8972 -0.7425 0.6506
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 Running
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 Running
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 Cycling
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 Cycling
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 Cycling
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 Cycling
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 Cycling
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 Cycling
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 Cycling
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 Running
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 Cycling
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 Running
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 Cycling
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 Running
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 Running
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 Cycling
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 Cycling
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 Running
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 Running
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 Running
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 Running
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 Running
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 Cycling
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 Running
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 Running
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 40.5% [3.0%; 63.5%]; H = 1.30 [1.02; 1.65]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 13 0.1813 [-0.0192; 0.3819] 21.81 45.0%
## Cycling 12 -0.1812 [-0.3801; 0.0176] 16.83 34.7%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 6.33 1 0.0119
## Within groups 38.65 23 0.0217
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 13 0.1490 [-0.1282; 0.4262] 0.1129 0.3360
## Cycling 12 -0.1186 [-0.3988; 0.1617] 0.0773 0.2781
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.77 1 0.1833
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1156 (SE = 0.0791)
## tau (square root of estimated tau^2 value): 0.3400
## I^2 (residual heterogeneity / unaccounted variability): 45.00%
## H^2 (unaccounted variability / sampling variability): 1.82
## R^2 (amount of heterogeneity accounted for): 15.60%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 41.8198, p-val = 0.0095
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.6173, p-val = 0.2035
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1187 0.1551 -0.7652 0.4441 -0.4228 0.1853
## type_exerciseRunning 0.2675 0.2103 1.2717 0.2035 -0.1448 0.6797
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 < 80 mmHg
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 < 80 mmHg
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 < 80 mmHg
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 < 80 mmHg
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 < 80 mmHg
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 < 80 mmHg
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 < 80 mmHg
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 < 80 mmHg
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 80 - 90 mmHg
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 80 - 90 mmHg
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 < 80 mmHg
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 < 80 mmHg
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 < 80 mmHg
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 80 - 90 mmHg
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 80 - 90 mmHg
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 < 80 mmHg
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 80 - 90 mmHg
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 < 80 mmHg
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 > 90 mmHg
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 80 - 90 mmHg
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 > 90 mmHg
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 < 80 mmHg
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 80 - 90 mmHg
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 > 90 mmHg
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 80 - 90 mmHg
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 32.4% [0.0%; 59.3%]; H = 1.22 [1.00; 1.57]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 80 mmHg 14 -0.1956 [-0.3816; -0.0097] 26.04 50.1%
## 80 - 90 mmHg 8 0.1423 [-0.1203; 0.4049] 3.12 0.0%
## > 90 mmHg 3 0.5230 [ 0.1375; 0.9084] 3.36 40.5%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 12.45 2 0.0020
## Within groups 32.53 22 0.0688
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 80 mmHg 14 -0.1640 [-0.4587; 0.1306] 0.1431 0.3783
## 80 - 90 mmHg 8 0.1423 [-0.1203; 0.4049] 0 0
## > 90 mmHg 3 0.4612 [-0.0590; 0.9814] 0.0864 0.2939
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 4.88 2 0.0871
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0746 (SE = 0.0648)
## tau (square root of estimated tau^2 value): 0.2732
## I^2 (residual heterogeneity / unaccounted variability): 35.30%
## H^2 (unaccounted variability / sampling variability): 1.55
## R^2 (amount of heterogeneity accounted for): 45.50%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 35.5466, p-val = 0.0459
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 6.8330, p-val = 0.0089
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -1.9416 0.7599 -2.5552 0.0106 -3.4310 -0.4523 *
## bsln_adjusted 0.0242 0.0093 2.6140 0.0089 0.0061 0.0423 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Beetham 2019 -1.2992 [-2.4937; -0.1048] 1.4 2.3 HIIT
## Ciolac 2010 0.0721 [-0.6211; 0.7653] 4.1 4.5 HIIT
## Cocks 2013 -0.2152 [-1.1980; 0.7676] 2.1 3.1 SIT
## Conraads 2015 -0.3593 [-0.6589; -0.0597] 22.1 7.4 HIIT
## Currie 2015 -1.4264 [-2.4347; -0.4181] 2.0 3.0 HIIT
## Eguchi 2012 0.0000 [-0.8765; 0.8765] 2.6 3.5 HIIT
## Fisher 2015 -0.8645 [-1.7259; -0.0031] 2.7 3.6 SIT
## Honkala 2017 (Healthy) 0.3306 [-0.4152; 1.0764] 3.6 4.2 SIT
## Honkala 2017 (T2D) 0.3339 [-0.6606; 1.3283] 2.0 3.0 SIT
## Jo 2020 -0.1592 [-0.8325; 0.5141] 4.4 4.7 HIIT
## Keating 2014 -0.1303 [-0.9669; 0.7063] 2.8 3.7 HIIT
## Keteyian 2014 1.1469 [ 0.3457; 1.9480] 3.1 3.9 HIIT
## Klonizakis 2014 -0.2983 [-1.2509; 0.6543] 2.2 3.2 HIIT
## Lunt 2014 0.2262 [-0.6137; 1.0662] 2.8 3.7 HIIT
## Lunt 2014 0.4890 [-0.3602; 1.3382] 2.8 3.7 SIT
## Matsuo 2014 0.3972 [-0.3791; 1.1735] 3.3 4.0 HIIT
## Matsuo 2015 0.4857 [-0.3262; 1.2976] 3.0 3.9 HIIT
## Mitranun 2014 -0.3780 [-1.1253; 0.3694] 3.6 4.2 HIIT
## Molmen-Hansen 2011 0.8739 [ 0.3380; 1.4098] 6.9 5.6 HIIT
## Ramos 2016a -0.1587 [-0.7576; 0.4402] 5.5 5.2 HIIT
## Ramos 2016b 0.2636 [-0.4337; 0.9609] 4.1 4.5 HIIT
## Rognmo 2004 -0.1462 [-1.0998; 0.8075] 2.2 3.2 HIIT
## Skleryk 2013 0.2806 [-0.7042; 1.2654] 2.1 3.1 SIT
## Tjønna 2008 0.0000 [-0.9107; 0.9107] 2.4 3.4 HIIT
## Wegmann 2018 0.1864 [-0.3759; 0.7486] 6.3 5.4 HIIT
##
## Number of studies combined: k = 25
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0024 [-0.1434; 0.1386] -0.03 0.9732
## Random effects model 0.0254 [-0.1884; 0.2391] 0.23 0.8161
##
## Quantifying heterogeneity:
## tau^2 = 0.1369 [0.0236; 0.4283]; tau = 0.3700 [0.1536; 0.6544];
## I^2 = 50.4% [21.3%; 68.7%]; H = 1.42 [1.13; 1.79]
##
## Quantifying residual heterogeneity:
## I^2 = 48.7% [17.6%; 68.1%]; H = 1.40 [1.10; 1.77]
##
## Test of heterogeneity:
## Q d.f. p-value
## 48.37 24 0.0023
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 19 -0.0134 [-0.1667; 0.1398] 38.67 53.5%
## SIT 6 0.0655 [-0.2976; 0.4287] 6.15 18.7%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.15 1 0.6945
## Within groups 44.82 23 0.0042
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 19 0.0190 [-0.2230; 0.2611] 0.1411 0.3756
## SIT 6 0.0624 [-0.3422; 0.4671] 0.0479 0.2189
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.03 1 0.8568
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 25; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.1473 (SE = 0.0905)
## tau (square root of estimated tau^2 value): 0.3838
## I^2 (residual heterogeneity / unaccounted variability): 52.28%
## H^2 (unaccounted variability / sampling variability): 2.10
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 48.2004, p-val = 0.0016
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0293, p-val = 0.8641
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0149 0.1248 0.1195 0.9049 -0.2296 0.2595
## HIIESIT 0.0469 0.2739 0.1711 0.8641 -0.4899 0.5837
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 -0.0513 [-0.1918; 0.0891] 0.4737 0.0000 0.0000 0.0%
## Omitting Ciolac 2010 -0.0499 [-0.1895; 0.0898] 0.4838 0.0000 0.0000 0.0%
## Omitting Conraads 2015 -0.0502 [-0.2056; 0.1053] 0.5270 0.0000 0.0000 0.0%
## Omitting Currie 2015 -0.0737 [-0.2129; 0.0655] 0.2992 0.0000 0.0000 0.0%
## Omitting Eguchi 2012 -0.0567 [-0.1962; 0.0827] 0.4253 0.0000 0.0000 0.0%
## Omitting Fisher 2015 -0.0571 [-0.1968; 0.0826] 0.4230 0.0000 0.0000 0.0%
## Omitting Grieco 2013 -0.0434 [-0.1830; 0.0962] 0.5421 0.0000 0.0000 0.0%
## Omitting Helgerud 2007 -0.0386 [-0.1780; 0.1008] 0.5874 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) -0.0372 [-0.1773; 0.1029] 0.6029 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) -0.0419 [-0.1810; 0.0971] 0.5543 0.0000 0.0000 0.0%
## Omitting Jo 2020 -0.0434 [-0.1841; 0.0973] 0.5455 0.0000 0.0000 0.0%
## Omitting Keating 2014 -0.0547 [-0.1943; 0.0850] 0.4431 0.0000 0.0000 0.0%
## Omitting Kim 2015 -0.0557 [-0.1959; 0.0845] 0.4364 0.0000 0.0000 0.0%
## Omitting Lunt 2014 -0.0595 [-0.1991; 0.0802] 0.4039 0.0000 0.0000 0.0%
## Omitting Lunt 2014 -0.0546 [-0.1943; 0.0850] 0.4431 0.0000 0.0000 0.0%
## Omitting Madssen 2014 -0.0457 [-0.1865; 0.0951] 0.5248 0.0000 0.0000 0.0%
## Omitting Maillard 2016 -0.0542 [-0.1934; 0.0849] 0.4448 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 -0.0548 [-0.1946; 0.0850] 0.4425 0.0000 0.0000 0.0%
## Omitting Mitranun 2014 -0.0559 [-0.1961; 0.0843] 0.4347 0.0000 0.0000 0.0%
## Omitting Motiani 2017 -0.0375 [-0.1775; 0.1024] 0.5990 0.0000 0.0000 0.0%
## Omitting Nalcakan 2014 -0.0621 [-0.2011; 0.0769] 0.3814 0.0000 0.0000 0.0%
## Omitting Ramos 2016a -0.0561 [-0.1977; 0.0854] 0.4369 0.0000 0.0000 0.0%
## Omitting Ramos 2016b -0.0498 [-0.1903; 0.0908] 0.4875 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 -0.0692 [-0.2088; 0.0705] 0.3317 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 -0.0607 [-0.1999; 0.0786] 0.3934 0.0000 0.0000 0.0%
## Omitting Tjønna 2008 -0.0661 [-0.2054; 0.0732] 0.3521 0.0000 0.0000 0.0%
## Omitting Winn 2018 -0.0716 [-0.2105; 0.0673] 0.3123 0.0000 0.0000 0.0%
## Omitting Zapata-Lamana 2018 -0.0355 [-0.1756; 0.1045] 0.6189 0.0000 0.0000 0.0%
##
## Pooled estimate -0.0529 [-0.1905; 0.0847] 0.4512 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.0529 [-0.1905; 0.0847] Overall
## Healthy -0.1927 [-0.5024; 0.1171] Population
## Overweight/obese 0.0662 [-0.2618; 0.3942] Population
## Cardiac Rehabilitation 0.0282 [-0.3156; 0.3721] Population
## Metabolic Syndrome -0.0291 [-0.3490; 0.2908] Population
## T2D -0.1355 [-0.5495; 0.2786] Population
## < 30 y -0.1368 [-0.4814; 0.2079] Age
## 30 - 50 y -0.0716 [-0.3771; 0.2339] Age
## > 50 y -0.0167 [-0.1967; 0.1632] Age
## < 5 weeks -0.2789 [-0.8082; 0.2505] Training Duration
## 5 - 10 weeks 0.0033 [-0.2497; 0.2563] Training Duration
## > 10 weeks -0.0251 [-0.2063; 0.1560] Training Duration
## < 0.5 0.0653 [-0.1822; 0.3128] Men Ratio
## > 0.5 -0.1063 [-0.2721; 0.0595] Men Ratio
## Cycling -0.0954 [-0.2756; 0.0849] Type of Exercise
## Running 0.0060 [-0.2075; 0.2196] Type of Exercise
## < 1.3 mmol/L -0.0015 [-0.1605; 0.1574] Baseline Values
## > 1.3 mmol/L -0.2087 [-0.4846; 0.0673] Baseline Values
## HIIT -0.0385 [-0.1908; 0.1139] Type of HIIE
## SIT -0.1155 [-0.4638; 0.2327] Type of HIIE
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0; tau = 0; I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Population 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Age 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Training Duration 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Men Ratio 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Type of Exercise 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Baseline Values 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
## Type of HIIE 28 -0.0529 [-0.1905; 0.0847] 0 0 24.91 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 T2D
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 Healthy
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 Cardiac Rehabilitation
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 Cardiac Rehabilitation
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 Healthy
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 Overweight/obese
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 Healthy
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 Healthy
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 Healthy
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 T2D
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 Metabolic Syndrome
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 Overweight/obese
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 Cardiac Rehabilitation
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 Overweight/obese
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 Overweight/obese
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 Cardiac Rehabilitation
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 T2D
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 Metabolic Syndrome
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 T2D
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 Healthy
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 Healthy
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 Metabolic Syndrome
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 Metabolic Syndrome
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 Healthy
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 Overweight/obese
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 Metabolic Syndrome
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 Overweight/obese
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 Overweight/obese
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 39.3%]; H = 1.00 [1.00; 1.28]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 8 -0.1945 [-0.4949; 0.1059] 7.43 5.8%
## Overweight/obese 7 0.0646 [-0.2593; 0.3885] 6.15 2.4%
## Cardiac Rehabilitation 4 -0.0114 [-0.2577; 0.2349] 4.15 27.7%
## Metabolic Syndrome 5 -0.0291 [-0.3490; 0.2908] 1.99 0.0%
## T2D 4 -0.1355 [-0.5495; 0.2786] 1.27 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.64 4 0.8013
## Within groups 20.99 23 0.5819
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 8 -0.1927 [-0.5024; 0.1171] 0.0115 0.1075
## Overweight/obese 7 0.0662 [-0.2618; 0.3942] 0.0047 0.0689
## Cardiac Rehabilitation 4 0.0282 [-0.3156; 0.3721] 0.0368 0.1918
## Metabolic Syndrome 5 -0.0291 [-0.3490; 0.2908] 0 0
## T2D 4 -0.1355 [-0.5495; 0.2786] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.68 4 0.7952
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0005 (SE = 0.0467)
## tau (square root of estimated tau^2 value): 0.0224
## I^2 (residual heterogeneity / unaccounted variability): 0.32%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 23) = 23.0729, p-val = 0.4565
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 1.8360, p-val = 0.7659
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.2006 0.1532 -1.3088 0.1906 -0.5009 0.0998
## .byvarOverweight/obese 0.2727 0.2253 1.2100 0.2263 -0.1690 0.7143
## .byvarCardiac Rehabilitation 0.1930 0.1988 0.9709 0.3316 -0.1966 0.5826
## .byvarMetabolic Syndrome 0.1726 0.2241 0.7701 0.4412 -0.2666 0.6117
## .byvarT2D 0.0571 0.2611 0.2186 0.8270 -0.4547 0.5688
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 > 50 y
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 < 30 y
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 > 50 y
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 > 50 y
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 > 50 y
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 < 30 y
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 < 30 y
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 < 30 y
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 30 - 50 y
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 30 - 50 y
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 > 50 y
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 30 - 50 y
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 > 50 y
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 30 - 50 y
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 30 - 50 y
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 > 50 y
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 > 50 y
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 30 - 50 y
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 > 50 y
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 30 - 50 y
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 < 30 y
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 > 50 y
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 > 50 y
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 < 30 y
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 30 - 50 y
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 > 50 y
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 30 - 50 y
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 < 30 y
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 35.9%]; H = 1.00 [1.00; 1.25]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 7 -0.1397 [-0.4623; 0.1828] 6.83 12.1%
## 30 - 50 y 9 -0.0771 [-0.3632; 0.2090] 9.07 11.8%
## > 50 y 12 -0.0167 [-0.1967; 0.1632] 6.27 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.46 2 0.7941
## Within groups 22.17 25 0.6260
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 7 -0.1368 [-0.4814; 0.2079] 0.0263 0.1620
## 30 - 50 y 9 -0.0716 [-0.3771; 0.2339] 0.0259 0.1609
## > 50 y 12 -0.0167 [-0.1967; 0.1632] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.39 2 0.8214
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0404)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 24.4829, p-val = 0.5484
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.4269, p-val = 0.5135
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.2195 0.2645 -0.8300 0.4066 -0.7379 0.2989
## age 0.0034 0.0052 0.6534 0.5135 -0.0069 0.0137
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 5 - 10 weeks
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 > 10 weeks
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 > 10 weeks
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 > 10 weeks
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 > 10 weeks
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 5 - 10 weeks
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 < 5 weeks
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 5 - 10 weeks
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 < 5 weeks
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 < 5 weeks
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 5 - 10 weeks
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 > 10 weeks
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 5 - 10 weeks
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 > 10 weeks
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 > 10 weeks
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 > 10 weeks
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 > 10 weeks
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 5 - 10 weeks
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 5 - 10 weeks
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 < 5 weeks
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 5 - 10 weeks
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 > 10 weeks
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 > 10 weeks
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 5 - 10 weeks
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 5 - 10 weeks
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 > 10 weeks
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 < 5 weeks
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 > 10 weeks
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 31.0%]; H = 1.00 [1.00; 1.20]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 5 -0.3162 [-0.7054; 0.0729] 7.21 44.6%
## 5 - 10 weeks 10 0.0033 [-0.2497; 0.2563] 5.39 0.0%
## > 10 weeks 13 -0.0251 [-0.2063; 0.1560] 7.98 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 2.04 2 0.3608
## Within groups 20.59 25 0.7152
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 5 -0.2789 [-0.8082; 0.2505] 0.1612 0.4015
## 5 - 10 weeks 10 0.0033 [-0.2497; 0.2563] 0 0
## > 10 weeks 13 -0.0251 [-0.2063; 0.1560] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.91 2 0.6330
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0399)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 23.6623, p-val = 0.5953
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.2475, p-val = 0.2640
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.2522 0.1918 -1.3152 0.1884 -0.6281 0.1236
## duration 0.0195 0.0175 1.1169 0.2640 -0.0147 0.0538
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 > 0.5
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 < 0.5
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 > 0.5
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 > 0.5
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 > 0.5
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 > 0.5
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 < 0.5
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 > 0.5
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 > 0.5
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 > 0.5
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 > 0.5
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 < 0.5
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 > 0.5
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 < 0.5
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 < 0.5
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 > 0.5
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 < 0.5
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 > 0.5
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 < 0.5
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 > 0.5
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 > 0.5
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 > 0.5
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 > 0.5
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 < 0.5
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 < 0.5
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 < 0.5
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 < 0.5
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 < 0.5
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 30.0%]; H = 1.00 [1.00; 1.20]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 12 0.0653 [-0.1822; 0.3128] 9.78 0.0%
## > 0.5 16 -0.1063 [-0.2721; 0.0595] 11.58 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.28 1 0.2588
## Within groups 21.35 26 0.7235
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 12 0.0653 [-0.1822; 0.3128] 0 0
## > 0.5 16 -0.1063 [-0.2721; 0.0595] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.28 1 0.2588
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0404)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 24.7473, p-val = 0.5333
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1625, p-val = 0.6868
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0107 0.1728 0.0622 0.9504 -0.3279 0.3494
## men_ratio -0.0937 0.2324 -0.4032 0.6868 -0.5492 0.3618
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 Cycling
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 Running
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 Cycling
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 Cycling
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 Cycling
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 Cycling
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 Cycling
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 Running
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 Cycling
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 Cycling
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 Running
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 Cycling
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 Running
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 Running
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 Running
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 Running
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 Cycling
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 Cycling
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 Running
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 Cycling
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 Cycling
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 Running
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 Running
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 Running
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 Cycling
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 Running
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 Running
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 Cycling
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 32.5%]; H = 1.00 [1.00; 1.22]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 15 -0.0954 [-0.2756; 0.0849] 12.19 0.0%
## Running 13 0.0060 [-0.2075; 0.2196] 9.93 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.51 1 0.4770
## Within groups 22.12 26 0.6820
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 15 -0.0954 [-0.2756; 0.0849] 0 0
## Running 13 0.0060 [-0.2075; 0.2196] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.51 1 0.4770
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0409)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 24.3574, p-val = 0.5555
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.5524, p-val = 0.4573
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0970 0.0919 -1.0552 0.2913 -0.2771 0.0831
## type_exerciseRunning 0.1059 0.1424 0.7433 0.4573 -0.1733 0.3850
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 < 1.3 mmol/L
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 > 1.3 mmol/L
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 < 1.3 mmol/L
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 < 1.3 mmol/L
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 > 1.3 mmol/L
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 < 1.3 mmol/L
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 > 1.3 mmol/L
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 < 1.3 mmol/L
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 > 1.3 mmol/L
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 < 1.3 mmol/L
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 < 1.3 mmol/L
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 > 1.3 mmol/L
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 < 1.3 mmol/L
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 < 1.3 mmol/L
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 < 1.3 mmol/L
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 < 1.3 mmol/L
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 > 1.3 mmol/L
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 < 1.3 mmol/L
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 < 1.3 mmol/L
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 > 1.3 mmol/L
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 < 1.3 mmol/L
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 < 1.3 mmol/L
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 < 1.3 mmol/L
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 > 1.3 mmol/L
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 < 1.3 mmol/L
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 < 1.3 mmol/L
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 < 1.3 mmol/L
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 > 1.3 mmol/L
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 28.9%]; H = 1.00 [1.00; 1.19]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 1.3 mmol/L 19 -0.0015 [-0.1605; 0.1574] 14.79 0.0%
## > 1.3 mmol/L 9 -0.2087 [-0.4846; 0.0673] 6.22 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.63 1 0.2024
## Within groups 21.00 26 0.7418
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 1.3 mmol/L 19 -0.0015 [-0.1605; 0.1574] 0 0
## > 1.3 mmol/L 9 -0.2087 [-0.4846; 0.0673] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.63 1 0.2024
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0400)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 22.0064, p-val = 0.6883
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 2.9034, p-val = 0.0884
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.8125 0.5127 1.5847 0.1130 -0.1924 1.8173
## bsln_adjusted -0.7112 0.4174 -1.7039 0.0884 -1.5293 0.1069 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 -0.1018 [-0.8067; 0.6031] 3.8 3.8 HIIT
## Ciolac 2010 -0.1776 [-1.0150; 0.6597] 2.7 2.7 HIIT
## Conraads 2015 -0.0644 [-0.3617; 0.2329] 21.4 21.4 HIIT
## Currie 2015 0.9662 [ 0.0147; 1.9177] 2.1 2.1 HIIT
## Eguchi 2012 0.0917 [-0.7852; 0.9687] 2.5 2.5 HIIT
## Fisher 2015 0.0877 [-0.7371; 0.9125] 2.8 2.8 SIT
## Grieco 2013 -0.4309 [-1.2797; 0.4179] 2.6 2.6 HIIT
## Helgerud 2007 -0.6997 [-1.6026; 0.2032] 2.3 2.3 HIIT
## Honkala 2017 (Healthy) -0.5327 [-1.2865; 0.2212] 3.3 3.3 SIT
## Honkala 2017 (T2D) -0.6981 [-1.7151; 0.3188] 1.8 1.8 SIT
## Jo 2020 -0.2853 [-0.9610; 0.3904] 4.1 4.1 HIIT
## Keating 2014 0.0000 [-0.8357; 0.8357] 2.7 2.7 HIIT
## Kim 2015 0.0174 [-0.7234; 0.7582] 3.5 3.5 HIIT
## Lunt 2014 0.1810 [-0.6580; 1.0201] 2.7 2.7 HIIT
## Lunt 2014 0.0000 [-0.8374; 0.8374] 2.7 2.7 SIT
## Madssen 2014 -0.2247 [-0.8893; 0.4399] 4.3 4.3 HIIT
## Maillard 2016 0.0000 [-0.9800; 0.9800] 2.0 2.0 HIIT
## Matsuo 2015 0.0000 [-0.8002; 0.8002] 3.0 3.0 HIIT
## Mitranun 2014 0.0232 [-0.7176; 0.7641] 3.5 3.5 HIIT
## Motiani 2017 -0.5635 [-1.3474; 0.2204] 3.1 3.1 SIT
## Nalcakan 2014 0.4637 [-0.5642; 1.4915] 1.8 1.8 SIT
## Ramos 2016a 0.0000 [-0.5979; 0.5979] 5.3 5.3 HIIT
## Ramos 2016b -0.1396 [-0.8347; 0.5556] 3.9 3.9 HIIT
## Sandvei 2012 0.5378 [-0.2949; 1.3706] 2.7 2.7 SIT
## Sawyer 2016 0.2947 [-0.6343; 1.2236] 2.2 2.2 HIIT
## Tjønna 2008 0.5492 [-0.3781; 1.4765] 2.2 2.2 HIIT
## Winn 2018 1.0842 [ 0.0347; 2.1337] 1.7 1.7 HIIT
## Zapata-Lamana 2018 -0.5861 [-1.3427; 0.1704] 3.3 3.3 HIIT
##
## Number of studies combined: k = 28
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
## Random effects model -0.0529 [-0.1905; 0.0847] -0.75 0.4512
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1473]; tau = 0 [0.0000; 0.3838];
## I^2 = 0.0% [0.0%; 37.1%]; H = 1.00 [1.00; 1.26]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 33.4%]; H = 1.00 [1.00; 1.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 24.91 27 0.5795
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 21 -0.0385 [-0.1908; 0.1139] 15.49 0.0%
## SIT 7 -0.1191 [-0.4417; 0.2036] 6.95 13.6%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.20 1 0.6579
## Within groups 22.43 26 0.6648
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 21 -0.0385 [-0.1908; 0.1139] 0 0
## SIT 7 -0.1155 [-0.4638; 0.2327] 0.0301 0.1736
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.16 1 0.6912
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 28; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0398)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 26) = 24.6868, p-val = 0.5368
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.2230, p-val = 0.6368
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0372 0.0777 -0.4795 0.6316 -0.1894 0.1150
## HIIESIT -0.0858 0.1818 -0.4722 0.6368 -0.4421 0.2704
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 0.1049 [-0.0903; 0.3001] 0.2920 0.0574 0.2396 28.5%
## Omitting Ciolac 2010 0.0670 [-0.1299; 0.2639] 0.5047 0.0630 0.2509 30.8%
## Omitting Conraads 2015 0.0983 [-0.1126; 0.3093] 0.3609 0.0768 0.2770 30.5%
## Omitting Currie 2015 0.1063 [-0.0816; 0.2941] 0.2675 0.0470 0.2169 25.0%
## Omitting Eguchi 2012 0.0745 [-0.1239; 0.2729] 0.4616 0.0663 0.2575 31.9%
## Omitting Fisher 2015 0.0912 [-0.1074; 0.2897] 0.3682 0.0659 0.2567 31.7%
## Omitting Helgerud 2007 0.0919 [-0.1058; 0.2896] 0.3622 0.0650 0.2550 31.5%
## Omitting Honkala 2017 (Healthy) 0.0359 [-0.1435; 0.2154] 0.6946 0.0312 0.1767 18.0%
## Omitting Honkala 2017 (T2D) 0.0835 [-0.1146; 0.2816] 0.4088 0.0669 0.2587 32.3%
## Omitting Jo 2020 0.0775 [-0.1238; 0.2788] 0.4504 0.0687 0.2621 32.2%
## Omitting Keating 2014 0.0588 [-0.1347; 0.2522] 0.5516 0.0564 0.2374 28.5%
## Omitting Kim 2015 0.0480 [-0.1411; 0.2371] 0.6189 0.0471 0.2171 24.8%
## Omitting Madssen 2014 0.0766 [-0.1248; 0.2779] 0.4562 0.0686 0.2620 32.1%
## Omitting Maillard 2016 0.1001 [-0.0920; 0.2923] 0.3071 0.0557 0.2359 28.4%
## Omitting Matsuo 2015 0.0987 [-0.0977; 0.2951] 0.3247 0.0614 0.2477 30.1%
## Omitting Mitranun 2014 0.0848 [-0.1157; 0.2853] 0.4070 0.0683 0.2614 32.3%
## Omitting Motiani 2017 0.0371 [-0.1420; 0.2161] 0.6849 0.0310 0.1762 17.9%
## Omitting Nalcakan 2014 0.0950 [-0.1000; 0.2900] 0.3398 0.0613 0.2475 30.4%
## Omitting Ramos 2016b 0.1095 [-0.0828; 0.3018] 0.2644 0.0519 0.2279 26.5%
## Omitting Sandvei 2012 0.0577 [-0.1355; 0.2509] 0.5580 0.0557 0.2361 28.2%
## Omitting Sawyer 2016 0.0877 [-0.1104; 0.2859] 0.3855 0.0664 0.2577 32.0%
## Omitting Winn 2018 0.0629 [-0.1305; 0.2563] 0.5239 0.0580 0.2408 29.3%
## Omitting Zapata-Lamana 2018 0.0903 [-0.1095; 0.2902] 0.3757 0.0671 0.2590 31.9%
##
## Pooled estimate 0.0846 [-0.1141; 0.2832] 0.4041 0.0751 0.2741 34.5%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.0846 [-0.1141; 0.2832] Overall
## Healthy 0.4247 [ 0.0269; 0.8225] Population
## Overweight/obese 0.1317 [-0.2523; 0.5157] Population
## Cardiac Rehabilitation 0.0425 [-0.4124; 0.4973] Population
## Metabolic Syndrome -0.2085 [-0.6257; 0.2087] Population
## T2D -0.2364 [-0.6516; 0.1789] Population
## < 30 y 0.0413 [-0.3052; 0.3878] Age
## 30 - 50 y 0.4161 [-0.0086; 0.8408] Age
## > 50 y -0.0661 [-0.2982; 0.1660] Age
## < 5 weeks 0.7312 [ 0.2867; 1.1756] Training Duration
## 5 - 10 weeks 0.0059 [-0.2480; 0.2599] Training Duration
## > 10 weeks -0.0517 [-0.2919; 0.1885] Training Duration
## < 0.5 0.1835 [-0.1191; 0.4860] Men Ratio
## > 0.5 0.0360 [-0.2102; 0.2822] Men Ratio
## Cycling 0.0073 [-0.2563; 0.2708] Type of Exercise
## Running 0.1857 [-0.0833; 0.4547] Type of Exercise
## < 3 mmol/L -0.0719 [-0.2451; 0.1012] Baseline Values
## > 3 mmol/L 0.4630 [ 0.0777; 0.8483] Baseline Values
## HIIT -0.0184 [-0.1936; 0.1569] Type of HIIE
## SIT 0.3846 [-0.1053; 0.8746] Type of HIIE
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751; tau = 0.2741; I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Population 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Age 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Training Duration 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Men Ratio 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Type of Exercise 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Baseline Values 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
## Type of HIIE 23 0.0846 [-0.1141; 0.2832] 0.0751 0.2741 33.59 34.5%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 T2D
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 Healthy
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 Cardiac Rehabilitation
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 Cardiac Rehabilitation
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 Healthy
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 Overweight/obese
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 Healthy
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 Healthy
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 T2D
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 Metabolic Syndrome
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 Overweight/obese
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 Cardiac Rehabilitation
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 Cardiac Rehabilitation
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 T2D
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 Metabolic Syndrome
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 T2D
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 Healthy
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 Healthy
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 Metabolic Syndrome
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 Healthy
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 Overweight/obese
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 Overweight/obese
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 Overweight/obese
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 17.5% [0.0%; 52.3%]; H = 1.10 [1.00; 1.45]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 7 0.4438 [ 0.1176; 0.7700] 8.87 32.4%
## Overweight/obese 5 0.1317 [-0.2523; 0.5157] 3.39 0.0%
## Cardiac Rehabilitation 4 0.0032 [-0.2437; 0.2501] 6.43 53.4%
## Metabolic Syndrome 3 -0.2085 [-0.6257; 0.2087] 1.79 0.0%
## T2D 4 -0.2364 [-0.6516; 0.1789] 1.34 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 9.20 4 0.0562
## Within groups 21.83 18 0.2398
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 7 0.4247 [ 0.0269; 0.8225] 0.0932 0.3053
## Overweight/obese 5 0.1317 [-0.2523; 0.5157] 0 0
## Cardiac Rehabilitation 4 0.0425 [-0.4124; 0.4973] 0.1113 0.3336
## Metabolic Syndrome 3 -0.2085 [-0.6257; 0.2087] 0 0
## T2D 4 -0.2364 [-0.6516; 0.1789] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 6.88 4 0.1426
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0498 (SE = 0.0700)
## tau (square root of estimated tau^2 value): 0.2232
## I^2 (residual heterogeneity / unaccounted variability): 23.91%
## H^2 (unaccounted variability / sampling variability): 1.31
## R^2 (amount of heterogeneity accounted for): 33.65%
##
## Test for Residual Heterogeneity:
## QE(df = 18) = 23.6548, p-val = 0.1667
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 7.3362, p-val = 0.1192
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4465 0.1865 2.3945 0.0166 0.0810 0.8120 *
## .byvarOverweight/obese -0.2974 0.2887 -1.0302 0.3029 -0.8634 0.2685
## .byvarCardiac Rehabilitation -0.4110 0.2647 -1.5528 0.1205 -0.9299 0.1078
## .byvarMetabolic Syndrome -0.6679 0.3113 -2.1458 0.0319 -1.2780 -0.0578 *
## .byvarT2D -0.6952 0.3049 -2.2801 0.0226 -1.2929 -0.0976 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 > 50 y
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 < 30 y
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 > 50 y
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 > 50 y
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 > 50 y
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 < 30 y
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 < 30 y
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 30 - 50 y
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 30 - 50 y
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 > 50 y
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 30 - 50 y
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 > 50 y
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 > 50 y
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 > 50 y
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 30 - 50 y
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 > 50 y
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 30 - 50 y
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 < 30 y
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 > 50 y
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 < 30 y
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 30 - 50 y
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 30 - 50 y
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 < 30 y
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 19.4% [0.0%; 52.5%]; H = 1.11 [1.00; 1.45]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 6 0.0413 [-0.3052; 0.3878] 4.05 0.0%
## 30 - 50 y 7 0.4251 [ 0.0940; 0.7563] 9.78 38.6%
## > 50 y 10 -0.0628 [-0.2564; 0.1309] 10.98 18.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 6.23 2 0.0445
## Within groups 24.80 20 0.2091
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 6 0.0413 [-0.3052; 0.3878] 0 0
## 30 - 50 y 7 0.4161 [-0.0086; 0.8408] 0.1264 0.3555
## > 50 y 10 -0.0661 [-0.2982; 0.1660] 0.0247 0.1572
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.81 2 0.1486
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0818 (SE = 0.0729)
## tau (square root of estimated tau^2 value): 0.2860
## I^2 (residual heterogeneity / unaccounted variability): 35.90%
## H^2 (unaccounted variability / sampling variability): 1.56
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 32.7590, p-val = 0.0490
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3736, p-val = 0.5411
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2877 0.3472 0.8287 0.4073 -0.3928 0.9683
## age -0.0044 0.0072 -0.6112 0.5411 -0.0184 0.0097
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 5 - 10 weeks
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 > 10 weeks
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 > 10 weeks
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 > 10 weeks
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 > 10 weeks
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 5 - 10 weeks
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 5 - 10 weeks
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 < 5 weeks
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 < 5 weeks
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 5 - 10 weeks
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 > 10 weeks
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 5 - 10 weeks
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 > 10 weeks
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 > 10 weeks
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 5 - 10 weeks
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 5 - 10 weeks
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 < 5 weeks
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 5 - 10 weeks
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 > 10 weeks
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 5 - 10 weeks
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 5 - 10 weeks
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 < 5 weeks
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 > 10 weeks
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 4.5% [0.0%; 49.4%]; H = 1.02 [1.00; 1.41]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 4 0.7312 [ 0.2867; 1.1756] 3.00 0.0%
## 5 - 10 weeks 10 0.0059 [-0.2480; 0.2599] 8.75 0.0%
## > 10 weeks 9 -0.0529 [-0.2589; 0.1531] 9.20 13.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 10.09 2 0.0065
## Within groups 20.94 20 0.4006
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 4 0.7312 [ 0.2867; 1.1756] 0 0
## 5 - 10 weeks 10 0.0059 [-0.2480; 0.2599] 0 0
## > 10 weeks 9 -0.0517 [-0.2919; 0.1885] 0.0181 0.1344
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 9.73 2 0.0077
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0269 (SE = 0.0533)
## tau (square root of estimated tau^2 value): 0.1641
## I^2 (residual heterogeneity / unaccounted variability): 15.71%
## H^2 (unaccounted variability / sampling variability): 1.19
## R^2 (amount of heterogeneity accounted for): 64.14%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 24.9145, p-val = 0.2509
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 7.1406, p-val = 0.0075
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.6429 0.2295 2.8020 0.0051 0.1932 1.0926 **
## duration -0.0597 0.0223 -2.6722 0.0075 -0.1035 -0.0159 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 > 0.5
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 < 0.5
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 > 0.5
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 > 0.5
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 > 0.5
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 > 0.5
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 > 0.5
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 > 0.5
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 > 0.5
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 > 0.5
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 < 0.5
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 > 0.5
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 > 0.5
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 < 0.5
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 > 0.5
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 < 0.5
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 > 0.5
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 > 0.5
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 > 0.5
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 < 0.5
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 < 0.5
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 < 0.5
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 < 0.5
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 30.3% [0.0%; 58.6%]; H = 1.20 [1.00; 1.55]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 8 0.1835 [-0.1191; 0.4860] 6.66 0.0%
## > 0.5 15 0.0163 [-0.1572; 0.1899] 23.48 40.4%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.88 1 0.3477
## Within groups 30.15 21 0.0891
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 8 0.1835 [-0.1191; 0.4860] 0 0
## > 0.5 15 0.0360 [-0.2102; 0.2822] 0.0874 0.2956
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.55 1 0.4588
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0864 (SE = 0.0743)
## tau (square root of estimated tau^2 value): 0.2939
## I^2 (residual heterogeneity / unaccounted variability): 37.38%
## H^2 (unaccounted variability / sampling variability): 1.60
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 33.5333, p-val = 0.0406
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0066, p-val = 0.9354
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1020 0.2298 0.4438 0.6572 -0.3484 0.5524
## men_ratio -0.0248 0.3056 -0.0811 0.9354 -0.6238 0.5742
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 Cycling
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 Running
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 Cycling
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 Cycling
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 Cycling
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 Cycling
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 Running
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 Cycling
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 Cycling
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 Running
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 Cycling
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 Running
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 Running
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 Cycling
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 Cycling
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 Running
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 Cycling
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 Cycling
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 Running
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 Running
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 Cycling
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 Running
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 Cycling
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 29.2% [0.0%; 57.9%]; H = 1.19 [1.00; 1.54]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 14 -0.0071 [-0.1926; 0.1784] 20.98 38.0%
## Running 9 0.1827 [-0.0749; 0.4404] 8.68 7.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.37 1 0.2412
## Within groups 29.65 21 0.0991
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 14 0.0073 [-0.2563; 0.2708] 0.0873 0.2955
## Running 9 0.1857 [-0.0833; 0.4547] 0.0132 0.1151
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.86 1 0.3531
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0777 (SE = 0.0716)
## tau (square root of estimated tau^2 value): 0.2787
## I^2 (residual heterogeneity / unaccounted variability): 34.57%
## H^2 (unaccounted variability / sampling variability): 1.53
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 32.0959, p-val = 0.0573
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.8963, p-val = 0.3438
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0065 0.1313 0.0496 0.9604 -0.2508 0.2638
## type_exerciseRunning 0.1973 0.2084 0.9467 0.3438 -0.2112 0.6059
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 < 3 mmol/L
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 < 3 mmol/L
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 < 3 mmol/L
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 < 3 mmol/L
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 > 3 mmol/L
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 < 3 mmol/L
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 < 3 mmol/L
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 > 3 mmol/L
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 < 3 mmol/L
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 < 3 mmol/L
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 > 3 mmol/L
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 > 3 mmol/L
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 < 3 mmol/L
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 < 3 mmol/L
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 > 3 mmol/L
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 > 3 mmol/L
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 > 3 mmol/L
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 < 3 mmol/L
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 < 3 mmol/L
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 < 3 mmol/L
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 < 3 mmol/L
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 < 3 mmol/L
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 < 3 mmol/L
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 5.3% [0.0%; 37.6%]; H = 1.03 [1.00; 1.27]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 3 mmol/L 16 -0.0719 [-0.2451; 0.1012] 12.64 0.0%
## > 3 mmol/L 7 0.4601 [ 0.1552; 0.7651] 9.54 37.1%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 8.84 1 0.0029
## Within groups 22.18 21 0.3890
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 3 mmol/L 16 -0.0719 [-0.2451; 0.1012] 0 0
## > 3 mmol/L 7 0.4630 [ 0.0777; 0.8483] 0.1002 0.3166
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 6.16 1 0.0131
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0351 (SE = 0.0601)
## tau (square root of estimated tau^2 value): 0.1874
## I^2 (residual heterogeneity / unaccounted variability): 18.11%
## H^2 (unaccounted variability / sampling variability): 1.22
## R^2 (amount of heterogeneity accounted for): 53.24%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 25.6426, p-val = 0.2204
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 7.1423, p-val = 0.0075
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -1.3340 0.5365 -2.4867 0.0129 -2.3854 -0.2826 *
## bsln_adjusted 0.5284 0.1977 2.6725 0.0075 0.1409 0.9160 **
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 -0.4098 [-1.1216; 0.3019] 4.5 5.0 HIIT
## Ciolac 2010 0.4300 [-0.4153; 1.2754] 3.2 3.9 HIIT
## Conraads 2015 -0.0612 [-0.3586; 0.2361] 25.6 10.5 HIIT
## Currie 2015 -0.8003 [-1.7361; 0.1355] 2.6 3.4 HIIT
## Eguchi 2012 0.2575 [-0.6227; 1.1376] 2.9 3.7 HIIT
## Fisher 2015 -0.1711 [-0.9970; 0.6548] 3.3 4.1 SIT
## Helgerud 2007 -0.2220 [-1.1012; 0.6573] 2.9 3.7 HIIT
## Honkala 2017 (Healthy) 1.0104 [ 0.2237; 1.7970] 3.7 4.3 SIT
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.3 3.1 SIT
## Jo 2020 0.1476 [-0.5256; 0.8208] 5.0 5.3 HIIT
## Keating 2014 0.6396 [-0.2172; 1.4964] 3.1 3.9 HIIT
## Kim 2015 0.7581 [-0.0089; 1.5250] 3.8 4.5 HIIT
## Madssen 2014 0.1632 [-0.5005; 0.8268] 5.1 5.4 HIIT
## Maillard 2016 -0.6396 [-1.6443; 0.3651] 2.2 3.0 HIIT
## Matsuo 2015 -0.3539 [-1.1603; 0.4525] 3.5 4.2 HIIT
## Mitranun 2014 0.0053 [-0.7355; 0.7461] 4.1 4.7 HIIT
## Motiani 2017 1.0575 [ 0.2367; 1.8782] 3.4 4.1 SIT
## Nalcakan 2014 -0.4452 [-1.4721; 0.5816] 2.1 2.9 SIT
## Ramos 2016b -0.5073 [-1.2127; 0.1980] 4.5 5.0 HIIT
## Sandvei 2012 0.6442 [-0.1948; 1.4833] 3.2 4.0 SIT
## Sawyer 2016 -0.1191 [-1.0439; 0.8056] 2.6 3.5 HIIT
## Winn 2018 0.6875 [-0.3211; 1.6960] 2.2 3.0 HIIT
## Zapata-Lamana 2018 -0.1122 [-0.8536; 0.6292] 4.1 4.7 HIIT
##
## Number of studies combined: k = 23
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0605 [-0.0898; 0.2108] 0.79 0.4303
## Random effects model 0.0846 [-0.1141; 0.2832] 0.83 0.4041
##
## Quantifying heterogeneity:
## tau^2 = 0.0751 [0.0000; 0.3441]; tau = 0.2741 [0.0000; 0.5866];
## I^2 = 34.5% [0.0%; 60.5%]; H = 1.24 [1.00; 1.59]
##
## Quantifying residual heterogeneity:
## I^2 = 19.9% [0.0%; 52.3%]; H = 1.12 [1.00; 1.45]
##
## Test of heterogeneity:
## Q d.f. p-value
## 33.59 22 0.0540
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 17 -0.0210 [-0.1872; 0.1451] 16.84 5.0%
## SIT 6 0.4182 [ 0.0627; 0.7738] 9.38 46.7%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 4.81 1 0.0283
## Within groups 26.22 21 0.1983
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 17 -0.0184 [-0.1936; 0.1569] 0.0069 0.0831
## SIT 6 0.3846 [-0.1053; 0.8746] 0.1741 0.4173
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.30 1 0.1291
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 23; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0506 (SE = 0.0611)
## tau (square root of estimated tau^2 value): 0.2249
## I^2 (residual heterogeneity / unaccounted variability): 26.12%
## H^2 (unaccounted variability / sampling variability): 1.35
## R^2 (amount of heterogeneity accounted for): 32.65%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 28.4236, p-val = 0.1285
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 3.4823, p-val = 0.0620
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0120 0.1076 -0.1119 0.9109 -0.2230 0.1989
## HIIESIT 0.4295 0.2301 1.8661 0.0620 -0.0216 0.8805 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 0.0212 [-0.1212; 0.1637] 0.7701 0.0000 0.0000 0.0%
## Omitting Ciolac 2010 0.0250 [-0.1166; 0.1666] 0.7294 0.0000 0.0000 0.0%
## Omitting Conraads 2015 0.0444 [-0.1138; 0.2025] 0.5826 0.0000 0.0000 0.0%
## Omitting Currie 2015 0.0224 [-0.1189; 0.1637] 0.7561 0.0000 0.0000 0.0%
## Omitting Eguchi 2012 0.0452 [-0.0962; 0.1865] 0.5313 0.0000 0.0000 0.0%
## Omitting Fisher 2015 0.0303 [-0.1114; 0.1720] 0.6747 0.0000 0.0000 0.0%
## Omitting Helgerud 2007 0.0331 [-0.1083; 0.1746] 0.6463 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) 0.0469 [-0.0952; 0.1890] 0.5178 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) 0.0298 [-0.1112; 0.1709] 0.6785 0.0000 0.0000 0.0%
## Omitting Jo 2020 0.0109 [-0.1318; 0.1536] 0.8810 0.0000 0.0000 0.0%
## Omitting Keating 2014 0.0366 [-0.1050; 0.1782] 0.6125 0.0000 0.0000 0.0%
## Omitting Kim 2015 0.0140 [-0.1281; 0.1561] 0.8467 0.0000 0.0000 0.0%
## Omitting Lunt 2014 0.0358 [-0.1058; 0.1774] 0.6204 0.0000 0.0000 0.0%
## Omitting Lunt 2014 0.0490 [-0.0925; 0.1905] 0.4977 0.0000 0.0000 0.0%
## Omitting Madssen 2014 0.0128 [-0.1300; 0.1556] 0.8609 0.0000 0.0000 0.0%
## Omitting Maillard 2016 0.0331 [-0.1080; 0.1742] 0.6453 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 0.0118 [-0.1299; 0.1535] 0.8707 0.0000 0.0000 0.0%
## Omitting Mitranun 2014 0.0302 [-0.1120; 0.1724] 0.6773 0.0000 0.0000 0.0%
## Omitting Motiani 2017 0.0514 [-0.0904; 0.1933] 0.4774 0.0000 0.0000 0.0%
## Omitting Nalcakan 2014 0.0216 [-0.1194; 0.1625] 0.7640 0.0000 0.0000 0.0%
## Omitting Ramos 2016a 0.0290 [-0.1147; 0.1726] 0.6927 0.0000 0.0000 0.0%
## Omitting Ramos 2016b 0.0189 [-0.1237; 0.1614] 0.7952 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 0.0128 [-0.1288; 0.1544] 0.8592 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 0.0171 [-0.1240; 0.1583] 0.8119 0.0000 0.0000 0.0%
## Omitting Tjønna 2008 0.0232 [-0.1181; 0.1645] 0.7471 0.0000 0.0000 0.0%
## Omitting Winn 2018 0.0385 [-0.1026; 0.1795] 0.5929 0.0000 0.0000 0.0%
## Omitting Zapata-Lamana 2018 0.0469 [-0.0953; 0.1890] 0.5182 0.0000 0.0000 0.0%
##
## Pooled estimate 0.0300 [-0.1095; 0.1695] 0.6736 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.0300 [-0.1095; 0.1695] Overall
## Healthy -0.1211 [-0.5006; 0.2583] Population
## Overweight/obese -0.2294 [-0.5533; 0.0946] Population
## Cardiac Rehabilitation 0.1078 [-0.1381; 0.3538] Population
## Metabolic Syndrome 0.2977 [-0.0239; 0.6193] Population
## T2D 0.0499 [-0.3623; 0.4621] Population
## < 30 y 0.0645 [-0.2822; 0.4112] Age
## 30 - 50 y -0.1862 [-0.5057; 0.1332] Age
## > 50 y 0.1065 [-0.0737; 0.2866] Age
## < 5 weeks -0.4292 [-0.8599; 0.0016] Training Duration
## 5 - 10 weeks 0.3160 [ 0.0616; 0.5703] Training Duration
## > 10 weeks -0.0352 [-0.2165; 0.1460] Training Duration
## < 0.5 -0.0592 [-0.3178; 0.1995] Men Ratio
## > 0.5 0.0656 [-0.1003; 0.2315] Men Ratio
## Cycling -0.0491 [-0.2336; 0.1355] Type of Exercise
## Running 0.1342 [-0.0795; 0.3478] Type of Exercise
## < 1.7 mmol/L -0.0191 [-0.1802; 0.1420] Baseline Values
## > 1.7 mmol/L 0.1755 [-0.1047; 0.4558] Baseline Values
## HIIT 0.0734 [-0.0814; 0.2282] Type of HIIE
## SIT -0.1506 [-0.5374; 0.2361] Type of HIIE
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0; tau = 0; I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Population 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Age 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Training Duration 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Men Ratio 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Type of Exercise 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Baseline Values 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
## Type of HIIE 27 0.0300 [-0.1095; 0.1695] 0 0 25.83 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 T2D
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 Healthy
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 Cardiac Rehabilitation
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 Cardiac Rehabilitation
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 Healthy
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 Overweight/obese
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 Healthy
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 Healthy
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 T2D
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 Metabolic Syndrome
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 Overweight/obese
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 Cardiac Rehabilitation
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 Overweight/obese
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 Overweight/obese
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 Cardiac Rehabilitation
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 T2D
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 Metabolic Syndrome
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 T2D
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 Healthy
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 Healthy
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 Metabolic Syndrome
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 Metabolic Syndrome
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 Healthy
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 Overweight/obese
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 Metabolic Syndrome
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 Overweight/obese
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 Overweight/obese
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 31.2%]; H = 1.00 [1.00; 1.21]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 7 -0.1314 [-0.4531; 0.1903] 8.28 27.6%
## Overweight/obese 7 -0.2294 [-0.5533; 0.0946] 4.76 0.0%
## Cardiac Rehabilitation 4 0.1078 [-0.1381; 0.3538] 2.46 0.0%
## Metabolic Syndrome 5 0.2977 [-0.0239; 0.6193] 1.52 0.0%
## T2D 4 0.0499 [-0.3623; 0.4621] 0.44 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 6.48 4 0.1658
## Within groups 17.46 22 0.7373
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 7 -0.1211 [-0.5006; 0.2583] 0.0721 0.2685
## Overweight/obese 7 -0.2294 [-0.5533; 0.0946] 0 0
## Cardiac Rehabilitation 4 0.1078 [-0.1381; 0.3538] 0 0
## Metabolic Syndrome 5 0.2977 [-0.0239; 0.6193] 0 0
## T2D 4 0.0499 [-0.3623; 0.4621] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 6.11 4 0.1912
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0473)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 22) = 18.9030, p-val = 0.6513
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 6.9308, p-val = 0.1396
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1348 0.1638 -0.8231 0.4105 -0.4559 0.1862
## .byvarOverweight/obese -0.1027 0.2325 -0.4417 0.6587 -0.5585 0.3531
## .byvarCardiac Rehabilitation 0.2465 0.2063 1.1948 0.2322 -0.1579 0.6509
## .byvarMetabolic Syndrome 0.4419 0.2318 1.9069 0.0565 -0.0123 0.8962 .
## .byvarT2D 0.1852 0.2666 0.6948 0.4872 -0.3373 0.7077
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 > 50 y
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 < 30 y
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 > 50 y
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 > 50 y
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 > 50 y
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 < 30 y
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 < 30 y
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 30 - 50 y
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 30 - 50 y
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 > 50 y
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 30 - 50 y
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 > 50 y
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 30 - 50 y
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 30 - 50 y
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 > 50 y
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 > 50 y
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 30 - 50 y
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 > 50 y
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 30 - 50 y
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 < 30 y
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 > 50 y
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 > 50 y
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 < 30 y
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 30 - 50 y
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 > 50 y
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 30 - 50 y
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 < 30 y
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 35.7%]; H = 1.00 [1.00; 1.25]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 6 0.0645 [-0.2822; 0.4112] 4.28 0.0%
## 30 - 50 y 9 -0.1908 [-0.4777; 0.0961] 9.86 18.9%
## > 50 y 12 0.1065 [-0.0737; 0.2866] 6.80 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 3.01 2 0.2225
## Within groups 20.94 24 0.6422
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 6 0.0645 [-0.2822; 0.4112] 0 0
## 30 - 50 y 9 -0.1862 [-0.5057; 0.1332] 0.0451 0.2123
## > 50 y 12 0.1065 [-0.0737; 0.2866] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.47 2 0.2911
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0047 (SE = 0.0422)
## tau (square root of estimated tau^2 value): 0.0683
## I^2 (residual heterogeneity / unaccounted variability): 3.13%
## H^2 (unaccounted variability / sampling variability): 1.03
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 25.8076, p-val = 0.4179
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0285, p-val = 0.8659
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0154 0.2863 -0.0538 0.9571 -0.5765 0.5457
## age 0.0010 0.0057 0.1689 0.8659 -0.0101 0.0120
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 5 - 10 weeks
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 > 10 weeks
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 > 10 weeks
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 > 10 weeks
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 > 10 weeks
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 5 - 10 weeks
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 5 - 10 weeks
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 < 5 weeks
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 < 5 weeks
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 5 - 10 weeks
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 > 10 weeks
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 5 - 10 weeks
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 > 10 weeks
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 > 10 weeks
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 > 10 weeks
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 > 10 weeks
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 5 - 10 weeks
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 5 - 10 weeks
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 < 5 weeks
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 5 - 10 weeks
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 > 10 weeks
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 > 10 weeks
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 5 - 10 weeks
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 5 - 10 weeks
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 > 10 weeks
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 < 5 weeks
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 > 10 weeks
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 5.3%]; H = 1.00 [1.00; 1.03]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 4 -0.4292 [-0.8599; 0.0016] 1.07 0.0%
## 5 - 10 weeks 10 0.3160 [ 0.0616; 0.5703] 3.89 0.0%
## > 10 weeks 13 -0.0352 [-0.2165; 0.1460] 9.27 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 9.72 2 0.0078
## Within groups 14.23 24 0.9414
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 4 -0.4292 [-0.8599; 0.0016] 0 0
## 5 - 10 weeks 10 0.3160 [ 0.0616; 0.5703] 0 0
## > 10 weeks 13 -0.0352 [-0.2165; 0.1460] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 9.72 2 0.0078
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0031 (SE = 0.0413)
## tau (square root of estimated tau^2 value): 0.0558
## I^2 (residual heterogeneity / unaccounted variability): 2.13%
## H^2 (unaccounted variability / sampling variability): 1.02
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 25.5452, p-val = 0.4322
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.2906, p-val = 0.5898
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0705 0.2017 -0.3495 0.7267 -0.4657 0.3248
## duration 0.0098 0.0182 0.5391 0.5898 -0.0259 0.0455
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 > 0.5
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 < 0.5
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 > 0.5
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 > 0.5
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 > 0.5
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 > 0.5
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 > 0.5
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 > 0.5
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 > 0.5
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 > 0.5
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 < 0.5
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 > 0.5
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 < 0.5
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 < 0.5
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 > 0.5
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 < 0.5
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 > 0.5
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 < 0.5
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 > 0.5
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 > 0.5
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 > 0.5
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 > 0.5
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 < 0.5
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 < 0.5
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 < 0.5
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 < 0.5
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 < 0.5
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 39.1%]; H = 1.00 [1.00; 1.28]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 11 -0.0592 [-0.3178; 0.1995] 9.13 0.0%
## > 0.5 16 0.0656 [-0.1003; 0.2315] 14.18 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.63 1 0.4261
## Within groups 23.31 25 0.5593
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 11 -0.0592 [-0.3178; 0.1995] 0 0
## > 0.5 16 0.0656 [-0.1003; 0.2315] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.63 1 0.4261
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0048 (SE = 0.0422)
## tau (square root of estimated tau^2 value): 0.0690
## I^2 (residual heterogeneity / unaccounted variability): 3.19%
## H^2 (unaccounted variability / sampling variability): 1.03
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 25.8228, p-val = 0.4171
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0150, p-val = 0.9024
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0115 0.1774 0.0650 0.9482 -0.3362 0.3593
## men_ratio 0.0292 0.2385 0.1226 0.9024 -0.4381 0.4966
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 Cycling
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 Running
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 Cycling
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 Cycling
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 Cycling
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 Cycling
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 Running
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 Cycling
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 Cycling
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 Running
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 Cycling
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 Running
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 Running
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 Running
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 Running
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 Cycling
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 Cycling
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 Running
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 Cycling
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 Cycling
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 Running
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 Running
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 Running
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 Cycling
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 Running
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 Running
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 Cycling
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 36.4%]; H = 1.00 [1.00; 1.25]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 14 -0.0491 [-0.2336; 0.1355] 12.70 0.0%
## Running 13 0.1342 [-0.0795; 0.3478] 9.63 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.62 1 0.2033
## Within groups 22.33 25 0.6168
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 14 -0.0491 [-0.2336; 0.1355] 0 0
## Running 13 0.1342 [-0.0795; 0.3478] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.62 1 0.2033
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0416)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 24.1499, p-val = 0.5107
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.6839, p-val = 0.1944
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0498 0.0941 -0.5294 0.5965 -0.2342 0.1346
## type_exerciseRunning 0.1867 0.1439 1.2976 0.1944 -0.0953 0.4688
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 > 1.7 mmol/L
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 < 1.7 mmol/L
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 < 1.7 mmol/L
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 < 1.7 mmol/L
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 > 1.7 mmol/L
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 < 1.7 mmol/L
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 < 1.7 mmol/L
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 < 1.7 mmol/L
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 > 1.7 mmol/L
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 > 1.7 mmol/L
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 < 1.7 mmol/L
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 < 1.7 mmol/L
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 < 1.7 mmol/L
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 < 1.7 mmol/L
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 < 1.7 mmol/L
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 < 1.7 mmol/L
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 > 1.7 mmol/L
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 < 1.7 mmol/L
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 < 1.7 mmol/L
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 < 1.7 mmol/L
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 > 1.7 mmol/L
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 > 1.7 mmol/L
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 < 1.7 mmol/L
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 < 1.7 mmol/L
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 < 1.7 mmol/L
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 < 1.7 mmol/L
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 < 1.7 mmol/L
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 37.0%]; H = 1.00 [1.00; 1.26]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 1.7 mmol/L 20 -0.0191 [-0.1802; 0.1420] 17.41 0.0%
## > 1.7 mmol/L 7 0.1755 [-0.1047; 0.4558] 5.14 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.39 1 0.2380
## Within groups 22.55 25 0.6036
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 1.7 mmol/L 20 -0.0191 [-0.1802; 0.1420] 0 0
## > 1.7 mmol/L 7 0.1755 [-0.1047; 0.4558] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.39 1 0.2380
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0402)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 24.2709, p-val = 0.5038
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.5629, p-val = 0.2112
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.2945 0.2692 -1.0943 0.2738 -0.8221 0.2330
## bsln_adjusted 0.2311 0.1849 1.2502 0.2112 -0.1312 0.5934
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 0.2323 [-0.4745; 0.9391] 3.9 3.9 HIIT
## Ciolac 2010 0.1845 [-0.6530; 1.0220] 2.8 2.8 HIIT
## Conraads 2015 -0.0242 [-0.3215; 0.2730] 22.0 22.0 HIIT
## Currie 2015 0.3256 [-0.5809; 1.2321] 2.4 2.4 HIIT
## Eguchi 2012 -0.6465 [-1.5457; 0.2526] 2.4 2.4 HIIT
## Fisher 2015 -0.0086 [-0.8330; 0.8159] 2.9 2.9 SIT
## Helgerud 2007 -0.1255 [-1.0029; 0.7519] 2.5 2.5 HIIT
## Honkala 2017 (Healthy) -0.4795 [-1.2309; 0.2719] 3.4 3.4 SIT
## Honkala 2017 (T2D) 0.0000 [-0.9877; 0.9877] 2.0 2.0 SIT
## Jo 2020 0.4589 [-0.2222; 1.1399] 4.2 4.2 HIIT
## Keating 2014 -0.2384 [-1.0771; 0.6003] 2.8 2.8 HIIT
## Kim 2015 0.4689 [-0.2820; 1.2198] 3.5 3.5 HIIT
## Lunt 2014 -0.2087 [-1.0482; 0.6309] 2.8 2.8 HIIT
## Lunt 2014 -0.7385 [-1.6026; 0.1257] 2.6 2.6 SIT
## Madssen 2014 0.4002 [-0.2688; 1.0692] 4.3 4.3 HIIT
## Maillard 2016 -0.1685 [-1.1503; 0.8132] 2.0 2.0 HIIT
## Matsuo 2015 0.6403 [-0.1801; 1.4607] 2.9 2.9 HIIT
## Mitranun 2014 0.0035 [-0.7373; 0.7443] 3.5 3.5 HIIT
## Motiani 2017 -0.6864 [-1.4775; 0.1046] 3.1 3.1 SIT
## Nalcakan 2014 0.4655 [-0.5624; 1.4935] 1.8 1.8 SIT
## Ramos 2016a 0.0347 [-0.5633; 0.6327] 5.4 5.4 HIIT
## Ramos 2016b 0.2851 [-0.4127; 0.9829] 4.0 4.0 HIIT
## Sandvei 2012 0.6305 [-0.2077; 1.4686] 2.8 2.8 SIT
## Sawyer 2016 0.6031 [-0.3416; 1.5478] 2.2 2.2 HIIT
## Tjønna 2008 0.2944 [-0.6211; 1.2100] 2.3 2.3 HIIT
## Winn 2018 -0.4553 [-1.4479; 0.5373] 2.0 2.0 HIIT
## Zapata-Lamana 2018 -0.4783 [-1.2297; 0.2730] 3.4 3.4 HIIT
##
## Number of studies combined: k = 27
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
## Random effects model 0.0300 [-0.1095; 0.1695] 0.42 0.6736
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1436]; tau = 0 [0.0000; 0.3789];
## I^2 = 0.0% [0.0%; 42.2%]; H = 1.00 [1.00; 1.32]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 36.2%]; H = 1.00 [1.00; 1.25]
##
## Test of heterogeneity:
## Q d.f. p-value
## 25.83 26 0.4723
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 20 0.0734 [-0.0814; 0.2282] 13.79 0.0%
## SIT 7 -0.1640 [-0.4878; 0.1598] 8.47 29.2%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.68 1 0.1948
## Within groups 22.27 25 0.6204
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 20 0.0734 [-0.0814; 0.2282] 0 0
## SIT 7 -0.1506 [-0.5374; 0.2361] 0.0792 0.2815
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.11 1 0.2919
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 27; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0404)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 25) = 24.0595, p-val = 0.5159
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.7743, p-val = 0.1829
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0754 0.0789 0.9550 0.3396 -0.0793 0.2300
## HIIESIT -0.2435 0.1828 -1.3320 0.1829 -0.6018 0.1148
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 0.1220 [-0.0676; 0.3116] 0.2071 0.0683 0.2614 31.6%
## Omitting Ciolac 2010 0.1272 [-0.0622; 0.3165] 0.1881 0.0698 0.2643 32.4%
## Omitting Conraads 2015 0.1518 [-0.0476; 0.3512] 0.1356 0.0790 0.2810 30.8%
## Omitting Currie 2015 0.1639 [-0.0109; 0.3386] 0.0661 0.0412 0.2031 22.2%
## Omitting Eguchi 2012 0.1570 [-0.0267; 0.3408] 0.0939 0.0584 0.2417 28.7%
## Omitting Fisher 2015 0.1465 [-0.0427; 0.3356] 0.1290 0.0691 0.2629 32.1%
## Omitting Grieco 2013 0.1093 [-0.0721; 0.2907] 0.2375 0.0535 0.2313 26.9%
## Omitting Helgerud 2007 0.1411 [-0.0486; 0.3308] 0.1448 0.0709 0.2663 32.8%
## Omitting Honkala 2017 (Healthy) 0.1055 [-0.0756; 0.2866] 0.2535 0.0515 0.2269 26.0%
## Omitting Honkala 2017 (T2D) 0.1208 [-0.0651; 0.3067] 0.2029 0.0642 0.2533 30.8%
## Omitting Jo 2020 0.0985 [-0.0797; 0.2766] 0.2785 0.0446 0.2111 23.2%
## Omitting Keating 2014 0.1275 [-0.0619; 0.3169] 0.1871 0.0700 0.2645 32.4%
## Omitting Kim 2015 0.1133 [-0.0723; 0.2990] 0.2316 0.0607 0.2464 29.2%
## Omitting Lunt 2014 0.1625 [-0.0176; 0.3426] 0.0770 0.0506 0.2250 25.8%
## Omitting Lunt 2014 0.1529 [-0.0338; 0.3397] 0.1085 0.0642 0.2533 30.5%
## Omitting Madssen 2014 0.1357 [-0.0565; 0.3280] 0.1665 0.0733 0.2707 33.0%
## Omitting Maillard 2016 0.1432 [-0.0453; 0.3317] 0.1365 0.0695 0.2637 32.5%
## Omitting Matsuo 2015 0.1355 [-0.0552; 0.3261] 0.1637 0.0720 0.2684 33.0%
## Omitting Mitranun 2014 0.1408 [-0.0502; 0.3319] 0.1485 0.0720 0.2684 32.8%
## Omitting Motiani 2017 0.1042 [-0.0752; 0.2837] 0.2549 0.0487 0.2206 25.0%
## Omitting Nalcakan 2014 0.1333 [-0.0557; 0.3223] 0.1668 0.0708 0.2661 32.9%
## Omitting Ramos 2016b 0.1658 [-0.0159; 0.3476] 0.0737 0.0517 0.2273 25.9%
## Omitting Sandvei 2012 0.1247 [-0.0642; 0.3137] 0.1958 0.0687 0.2622 32.0%
## Omitting Sawyer 2016 0.1399 [-0.0496; 0.3293] 0.1478 0.0710 0.2664 32.8%
## Omitting Winn 2018 0.1381 [-0.0511; 0.3273] 0.1526 0.0710 0.2665 32.9%
## Omitting Zapata-Lamana 2018 0.1420 [-0.0489; 0.3329] 0.1450 0.0717 0.2678 32.7%
##
## Pooled estimate 0.1400 [-0.0502; 0.3303] 0.1491 0.0801 0.2830 35.4%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.1400 [-0.0502; 0.3303] Overall
## Healthy 0.4047 [ 0.0539; 0.7554] Population
## Overweight/obese -0.1225 [-0.4446; 0.1996] Population
## Cardiac Rehabilitation 0.0035 [-0.4653; 0.4723] Population
## Metabolic Syndrome 0.1555 [-0.6771; 0.9881] Population
## T2D 0.2301 [-0.1858; 0.6460] Population
## < 30 y 0.2189 [-0.1024; 0.5402] Age
## 30 - 50 y 0.2159 [-0.1462; 0.5781] Age
## > 50 y 0.0279 [-0.2774; 0.3332] Age
## < 5 weeks 0.7095 [ 0.3151; 1.1040] Training Duration
## 5 - 10 weeks 0.2855 [ 0.0308; 0.5401] Training Duration
## > 10 weeks -0.1411 [-0.3509; 0.0687] Training Duration
## < 0.5 0.0766 [-0.1802; 0.3334] Men Ratio
## > 0.5 0.1744 [-0.0890; 0.4377] Men Ratio
## Cycling 0.1667 [-0.0777; 0.4112] Type of Exercise
## Running 0.0915 [-0.2020; 0.3850] Type of Exercise
## < 5.2 mmol/L 0.2066 [ 0.0076; 0.4057] Baseline Values
## > 5.2 mmol/L -0.2059 [-0.5974; 0.1855] Baseline Values
## HIIT 0.0642 [-0.1394; 0.2677] Type of HIIE
## SIT 0.3642 [-0.0135; 0.7419] Type of HIIE
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801; tau = 0.2830; I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Population 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Age 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Training Duration 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Men Ratio 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Type of Exercise 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Baseline Values 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
## Type of HIIE 26 0.1400 [-0.0502; 0.3303] 0.0801 0.2830 38.68 35.4%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 T2D
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 Healthy
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 Cardiac Rehabilitation
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 Cardiac Rehabilitation
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 Healthy
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 Overweight/obese
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 Healthy
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 Healthy
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 Healthy
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 T2D
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 Metabolic Syndrome
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 Overweight/obese
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 Cardiac Rehabilitation
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 Overweight/obese
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 Overweight/obese
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 Cardiac Rehabilitation
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 T2D
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 Metabolic Syndrome
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 T2D
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 Healthy
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 Healthy
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 Metabolic Syndrome
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 Healthy
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 Overweight/obese
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 Overweight/obese
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 Overweight/obese
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 27.4% [0.0%; 56.9%]; H = 1.17 [1.00; 1.52]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 8 0.4131 [ 0.1088; 0.7174] 9.26 24.4%
## Overweight/obese 7 -0.1225 [-0.4446; 0.1996] 3.43 0.0%
## Cardiac Rehabilitation 4 0.0050 [-0.2421; 0.2520] 6.77 55.7%
## Metabolic Syndrome 3 0.1573 [-0.2672; 0.5819] 7.64 73.8%
## T2D 4 0.2301 [-0.1858; 0.6460] 1.85 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 6.87 4 0.1429
## Within groups 28.94 21 0.1155
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 8 0.4047 [ 0.0539; 0.7554] 0.0624 0.2497
## Overweight/obese 7 -0.1225 [-0.4446; 0.1996] 0 0
## Cardiac Rehabilitation 4 0.0035 [-0.4653; 0.4723] 0.1225 0.3501
## Metabolic Syndrome 3 0.1555 [-0.6771; 0.9881] 0.3992 0.6319
## T2D 4 0.2301 [-0.1858; 0.6460] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 5.22 4 0.2656
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0791 (SE = 0.0755)
## tau (square root of estimated tau^2 value): 0.2812
## I^2 (residual heterogeneity / unaccounted variability): 32.74%
## H^2 (unaccounted variability / sampling variability): 1.49
## R^2 (amount of heterogeneity accounted for): 1.30%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 31.2204, p-val = 0.0701
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 4.7048, p-val = 0.3190
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4179 0.1844 2.2664 0.0234 0.0565 0.7793 *
## .byvarOverweight/obese -0.5458 0.2692 -2.0275 0.0426 -1.0735 -0.0182 *
## .byvarCardiac Rehabilitation -0.4126 0.2802 -1.4724 0.1409 -0.9618 0.1366
## .byvarMetabolic Syndrome -0.2569 0.3276 -0.7842 0.4329 -0.8990 0.3852
## .byvarT2D -0.1770 0.3163 -0.5597 0.5757 -0.7970 0.4429
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 > 50 y
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 < 30 y
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 > 50 y
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 > 50 y
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 > 50 y
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 < 30 y
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 < 30 y
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 < 30 y
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 30 - 50 y
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 30 - 50 y
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 > 50 y
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 30 - 50 y
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 > 50 y
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 30 - 50 y
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 30 - 50 y
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 > 50 y
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 > 50 y
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 30 - 50 y
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 > 50 y
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 30 - 50 y
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 < 30 y
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 > 50 y
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 < 30 y
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 30 - 50 y
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 30 - 50 y
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 < 30 y
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 32.6% [0.0%; 59.0%]; H = 1.22 [1.00; 1.56]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 7 0.2189 [-0.1024; 0.5402] 4.01 0.0%
## 30 - 50 y 9 0.2234 [-0.0650; 0.5118] 12.52 36.1%
## > 50 y 10 0.0287 [-0.1657; 0.2232] 17.58 48.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.70 2 0.4274
## Within groups 34.11 23 0.0636
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 7 0.2189 [-0.1024; 0.5402] 0 0
## 30 - 50 y 9 0.2159 [-0.1462; 0.5781] 0.1105 0.3324
## > 50 y 10 0.0279 [-0.2774; 0.3332] 0.1085 0.3294
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.92 2 0.6326
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0796 (SE = 0.0685)
## tau (square root of estimated tau^2 value): 0.2821
## I^2 (residual heterogeneity / unaccounted variability): 34.66%
## H^2 (unaccounted variability / sampling variability): 1.53
## R^2 (amount of heterogeneity accounted for): 0.66%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 36.7329, p-val = 0.0465
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.1284, p-val = 0.2881
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.4679 0.3235 1.4462 0.1481 -0.1662 1.1020
## age -0.0072 0.0068 -1.0623 0.2881 -0.0204 0.0061
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 5 - 10 weeks
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 > 10 weeks
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 > 10 weeks
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 > 10 weeks
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 > 10 weeks
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 5 - 10 weeks
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 < 5 weeks
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 5 - 10 weeks
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 < 5 weeks
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 < 5 weeks
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 5 - 10 weeks
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 > 10 weeks
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 5 - 10 weeks
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 > 10 weeks
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 > 10 weeks
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 > 10 weeks
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 > 10 weeks
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 5 - 10 weeks
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 5 - 10 weeks
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 < 5 weeks
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 5 - 10 weeks
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 > 10 weeks
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 5 - 10 weeks
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 5 - 10 weeks
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 < 5 weeks
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 > 10 weeks
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 34.1%]; H = 1.00 [1.00; 1.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 5 0.7095 [ 0.3151; 1.1040] 2.30 0.0%
## 5 - 10 weeks 10 0.2855 [ 0.0308; 0.5401] 6.42 0.0%
## > 10 weeks 11 -0.1291 [-0.3241; 0.0658] 10.62 5.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 16.47 2 0.0003
## Within groups 19.34 23 0.6815
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 5 0.7095 [ 0.3151; 1.1040] 0 0
## 5 - 10 weeks 10 0.2855 [ 0.0308; 0.5401] 0 0
## > 10 weeks 11 -0.1411 [-0.3509; 0.0687] 0.0079 0.0890
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 16.14 2 0.0003
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0428)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 21.5591, p-val = 0.6056
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 17.1191, p-val < .0001
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.9030 0.2031 4.4468 <.0001 0.5050 1.3011 ***
## duration -0.0802 0.0194 -4.1375 <.0001 -0.1182 -0.0422 ***
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 > 0.5
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 < 0.5
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 > 0.5
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 > 0.5
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 > 0.5
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 > 0.5
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 < 0.5
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 > 0.5
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 > 0.5
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 > 0.5
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 > 0.5
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 < 0.5
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 > 0.5
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 < 0.5
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 < 0.5
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 > 0.5
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 < 0.5
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 > 0.5
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 < 0.5
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 > 0.5
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 > 0.5
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 > 0.5
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 < 0.5
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 < 0.5
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 < 0.5
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 < 0.5
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 32.7% [0.0%; 58.7%]; H = 1.22 [1.00; 1.56]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 11 0.0766 [-0.1802; 0.3334] 9.05 0.0%
## > 0.5 15 0.1335 [-0.0406; 0.3076] 26.63 47.4%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.13 1 0.7189
## Within groups 35.68 24 0.0589
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 11 0.0766 [-0.1802; 0.3334] 0 0
## > 0.5 15 0.1744 [-0.0890; 0.4377] 0.1173 0.3425
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.27 1 0.6024
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0910 (SE = 0.0722)
## tau (square root of estimated tau^2 value): 0.3016
## I^2 (residual heterogeneity / unaccounted variability): 37.90%
## H^2 (unaccounted variability / sampling variability): 1.61
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 38.6472, p-val = 0.0297
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0027, p-val = 0.9587
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1302 0.2190 0.5943 0.5523 -0.2991 0.5594
## men_ratio 0.0156 0.3016 0.0518 0.9587 -0.5755 0.6068
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 Cycling
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 Running
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 Cycling
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 Cycling
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 Cycling
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 Cycling
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 Cycling
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 Running
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 Cycling
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 Cycling
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 Running
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 Cycling
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 Running
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 Running
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 Running
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 Running
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 Cycling
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 Cycling
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 Running
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 Cycling
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 Cycling
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 Running
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 Running
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 Cycling
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 Running
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 Cycling
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 32.9% [0.0%; 58.8%]; H = 1.22 [1.00; 1.56]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 15 0.1254 [-0.0559; 0.3067] 20.69 32.3%
## Running 11 0.0988 [-0.1386; 0.3362] 15.09 33.7%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.03 1 0.8614
## Within groups 35.78 24 0.0577
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 15 0.1667 [-0.0777; 0.4112] 0.0688 0.2623
## Running 11 0.0915 [-0.2020; 0.3850] 0.0826 0.2873
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.15 1 0.6995
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0919 (SE = 0.0727)
## tau (square root of estimated tau^2 value): 0.3031
## I^2 (residual heterogeneity / unaccounted variability): 37.89%
## H^2 (unaccounted variability / sampling variability): 1.61
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 38.6428, p-val = 0.0298
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1655, p-val = 0.6842
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1752 0.1315 1.3327 0.1826 -0.0825 0.4329
## type_exerciseRunning -0.0819 0.2013 -0.4068 0.6842 -0.4765 0.3127
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 < 5.2 mmol/L
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 < 5.2 mmol/L
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 < 5.2 mmol/L
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 < 5.2 mmol/L
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 > 5.2 mmol/L
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 < 5.2 mmol/L
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 < 5.2 mmol/L
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 < 5.2 mmol/L
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 < 5.2 mmol/L
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 < 5.2 mmol/L
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 < 5.2 mmol/L
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 > 5.2 mmol/L
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 < 5.2 mmol/L
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 > 5.2 mmol/L
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 > 5.2 mmol/L
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 < 5.2 mmol/L
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 < 5.2 mmol/L
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 > 5.2 mmol/L
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 < 5.2 mmol/L
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 < 5.2 mmol/L
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 < 5.2 mmol/L
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 < 5.2 mmol/L
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 < 5.2 mmol/L
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 < 5.2 mmol/L
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 < 5.2 mmol/L
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 < 5.2 mmol/L
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 26.4% [0.0%; 55.0%]; H = 1.17 [1.00; 1.49]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5.2 mmol/L 21 0.1695 [ 0.0138; 0.3253] 28.36 29.5%
## > 5.2 mmol/L 5 -0.2047 [-0.5843; 0.1749] 4.25 5.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 3.20 1 0.0738
## Within groups 32.61 24 0.1125
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5.2 mmol/L 21 0.2066 [ 0.0076; 0.4057] 0.0589 0.2427
## > 5.2 mmol/L 5 -0.2059 [-0.5974; 0.1855] 0.0119 0.1089
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.39 1 0.0656
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0887 (SE = 0.0725)
## tau (square root of estimated tau^2 value): 0.2978
## I^2 (residual heterogeneity / unaccounted variability): 35.96%
## H^2 (unaccounted variability / sampling variability): 1.56
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 37.4792, p-val = 0.0392
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3526, p-val = 0.5527
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.2894 0.7303 -0.3963 0.6919 -1.7207 1.1419
## bsln_adjusted 0.0939 0.1582 0.5938 0.5527 -0.2161 0.4040
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 0.4282 [-0.2843; 1.1406] 4.1 4.4 HIIT
## Ciolac 2010 0.3701 [-0.4728; 1.2130] 2.9 3.6 HIIT
## Conraads 2015 -0.0242 [-0.3215; 0.2731] 23.4 9.1 HIIT
## Currie 2015 -1.0152 [-1.9719; -0.0586] 2.3 3.0 HIIT
## Eguchi 2012 -0.5729 [-1.4672; 0.3214] 2.6 3.3 HIIT
## Fisher 2015 -0.1696 [-0.9955; 0.6562] 3.0 3.7 SIT
## Grieco 2013 0.9216 [ 0.0393; 1.8038] 2.7 3.3 HIIT
## Helgerud 2007 -0.0341 [-0.9107; 0.8424] 2.7 3.4 HIIT
## Honkala 2017 (Healthy) 0.8577 [ 0.0836; 1.6318] 3.5 4.0 SIT
## Honkala 2017 (T2D) 0.7046 [-0.3128; 1.7221] 2.0 2.7 SIT
## Jo 2020 0.8928 [ 0.1878; 1.5978] 4.2 4.5 HIIT
## Keating 2014 0.3604 [-0.4821; 1.2029] 2.9 3.6 HIIT
## Kim 2015 0.6605 [-0.1002; 1.4213] 3.6 4.1 HIIT
## Lunt 2014 -0.7221 [-1.5851; 0.1409] 2.8 3.4 HIIT
## Lunt 2014 -0.3736 [-1.2179; 0.4707] 2.9 3.5 SIT
## Madssen 2014 0.1319 [-0.5314; 0.7952] 4.7 4.8 HIIT
## Maillard 2016 -0.1494 [-1.1308; 0.8319] 2.2 2.8 HIIT
## Matsuo 2015 0.1370 [-0.6641; 0.9380] 3.2 3.8 HIIT
## Mitranun 2014 0.0115 [-0.7293; 0.7523] 3.8 4.2 HIIT
## Motiani 2017 0.9454 [ 0.1348; 1.7559] 3.2 3.8 SIT
## Nalcakan 2014 0.2218 [-0.7957; 1.2393] 2.0 2.7 SIT
## Ramos 2016b -0.5535 [-1.2609; 0.1539] 4.1 4.5 HIIT
## Sandvei 2012 0.4295 [-0.3980; 1.2570] 3.0 3.6 SIT
## Sawyer 2016 -0.0089 [-0.9328; 0.9150] 2.4 3.1 HIIT
## Winn 2018 0.0419 [-0.9382; 1.0220] 2.2 2.9 HIIT
## Zapata-Lamana 2018 -0.0156 [-0.7564; 0.7252] 3.8 4.2 HIIT
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.1196 [-0.0243; 0.2635] 1.63 0.1032
## Random effects model 0.1400 [-0.0502; 0.3303] 1.44 0.1491
##
## Quantifying heterogeneity:
## tau^2 = 0.0801 [0.0000; 0.3233]; tau = 0.2830 [0.0000; 0.5686];
## I^2 = 35.4% [0.0%; 59.9%]; H = 1.24 [1.00; 1.58]
##
## Quantifying residual heterogeneity:
## I^2 = 27.2% [0.0%; 55.5%]; H = 1.17 [1.00; 1.50]
##
## Test of heterogeneity:
## Q d.f. p-value
## 38.68 25 0.0397
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 19 0.0545 [-0.1061; 0.2151] 24.98 27.9%
## SIT 7 0.3673 [ 0.0413; 0.6934] 7.98 24.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 2.85 1 0.0916
## Within groups 32.96 24 0.1048
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 19 0.0642 [-0.1394; 0.2677] 0.0530 0.2302
## SIT 7 0.3642 [-0.0135; 0.7419] 0.0644 0.2537
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.88 1 0.1705
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0708 (SE = 0.0651)
## tau (square root of estimated tau^2 value): 0.2661
## I^2 (residual heterogeneity / unaccounted variability): 32.49%
## H^2 (unaccounted variability / sampling variability): 1.48
## R^2 (amount of heterogeneity accounted for): 11.60%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 35.5486, p-val = 0.0607
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.9847, p-val = 0.1589
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0649 0.1088 0.5964 0.5509 -0.1484 0.2782
## HIIESIT 0.3143 0.2231 1.4088 0.1589 -0.1230 0.7516
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Conraads 2015 -0.1274 [-0.5043; 0.2495] 0.5077 0.0345 0.1856 15.5%
## Omitting Hovanloo 2013 -0.0876 [-0.3511; 0.1759] 0.5147 0.0119 0.1090 9.3%
## Omitting Keating 2014 -0.0789 [-0.3356; 0.1779] 0.5471 0.0079 0.0888 6.2%
## Omitting Kim 2015 -0.0967 [-0.3857; 0.1924] 0.5122 0.0204 0.1427 13.9%
## Omitting Madssen 2014 -0.1851 [-0.4236; 0.0534] 0.1282 0.0000 0.0000 0.0%
## Omitting Nalcakan 2014 -0.0748 [-0.3049; 0.1554] 0.5243 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 -0.1166 [-0.4013; 0.1682] 0.4225 0.0213 0.1458 15.3%
##
## Pooled estimate -0.1122 [-0.3595; 0.1351] 0.3740 0.0085 0.0921 6.4%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.1122 [-0.3595; 0.1351] Overall
## Healthy -0.5575 [-1.2818; 0.1668] Population
## Overweight/obese -0.2565 [-0.8810; 0.3679] Population
## Cardiac Rehabilitation 0.0306 [-0.3678; 0.4290] Population
## < 30 y -0.5575 [-1.2818; 0.1668] Age
## 30 - 50 y -0.2565 [-0.8810; 0.3679] Age
## > 50 y 0.0306 [-0.3678; 0.4290] Age
## < 5 weeks -0.4165 [-1.4105; 0.5775] Training Duration
## 5 - 10 weeks -0.2876 [-0.7956; 0.2205] Training Duration
## > 10 weeks 0.0115 [-0.4491; 0.4721] Training Duration
## < 0.5 -0.3018 [-0.8306; 0.2270] Men Ratio
## > 0.5 -0.0504 [-0.4433; 0.3425] Men Ratio
## Cycling -0.1807 [-0.4324; 0.0711] Type of Exercise
## Running 0.1789 [-0.5784; 0.9361] Type of Exercise
## < 2 mg/L -0.1385 [-0.4045; 0.1276] Baseline Values
## > 2 mg/L -0.0844 [-0.6548; 0.4860] Baseline Values
## HIIT -0.0536 [-0.2976; 0.1903] Type of HIIE
## SIT -0.5575 [-1.2818; 0.1668] Type of HIIE
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085; tau = 0.0921; I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Population 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Age 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Training Duration 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Men Ratio 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Type of Exercise 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Baseline Values 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
## Type of HIIE 7 -0.1122 [-0.3595; 0.1351] 0.0085 0.0921 6.41 6.4%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 Cardiac Rehabilitation
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 Healthy
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 Overweight/obese
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 Cardiac Rehabilitation
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 Cardiac Rehabilitation
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 Healthy
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 Overweight/obese
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 78.0%]; H = 1.00 [1.00; 2.13]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 2 -0.5575 [-1.2818; 0.1668] 0.16 0.0%
## Overweight/obese 2 -0.2565 [-0.8810; 0.3679] 0.33 0.0%
## Cardiac Rehabilitation 3 -0.0217 [-0.2774; 0.2339] 3.29 39.2%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 2.13 2 0.3442
## Within groups 3.78 4 0.4362
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 2 -0.5575 [-1.2818; 0.1668] 0 0
## Overweight/obese 2 -0.2565 [-0.8810; 0.3679] 0 0
## Cardiac Rehabilitation 3 0.0306 [-0.3678; 0.4290] 0.0523 0.2288
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.11 2 0.3474
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0850)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 4) = 3.9852, p-val = 0.4080
##
## Test of Moderators (coefficients 2:3):
## QM(df = 2) = 2.4274, p-val = 0.2971
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.5920 0.3679 -1.6090 0.1076 -1.3131 0.1291
## .byvarOverweight/obese 0.3248 0.4865 0.6676 0.5044 -0.6288 1.2784
## .byvarCardiac Rehabilitation 0.5712 0.3904 1.4632 0.1434 -0.1939 1.3363
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 > 50 y
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 < 30 y
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 30 - 50 y
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 > 50 y
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 > 50 y
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 < 30 y
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 30 - 50 y
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 78.0%]; H = 1.00 [1.00; 2.13]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 2 -0.5575 [-1.2818; 0.1668] 0.16 0.0%
## 30 - 50 y 2 -0.2565 [-0.8810; 0.3679] 0.33 0.0%
## > 50 y 3 -0.0217 [-0.2774; 0.2339] 3.29 39.2%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 2.13 2 0.3442
## Within groups 3.78 4 0.4362
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 2 -0.5575 [-1.2818; 0.1668] 0 0
## 30 - 50 y 2 -0.2565 [-0.8810; 0.3679] 0 0
## > 50 y 3 0.0306 [-0.3678; 0.4290] 0.0523 0.2288
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 2.11 2 0.3474
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0817)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 5) = 4.3002, p-val = 0.5071
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 2.1125, p-val = 0.1461
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.8531 0.5251 -1.6245 0.1043 -1.8824 0.1761
## age 0.0142 0.0098 1.4534 0.1461 -0.0049 0.0333
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 > 10 weeks
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 < 5 weeks
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 > 10 weeks
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 5 - 10 weeks
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 > 10 weeks
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 5 - 10 weeks
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 5 - 10 weeks
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 16.0% [0.0%; 82.5%]; H = 1.09 [1.00; 2.39]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 1 -0.4165 [-1.4105; 0.5775] 0.00 --
## 5 - 10 weeks 3 -0.2876 [-0.7956; 0.2205] 0.90 0.0%
## > 10 weeks 3 -0.0347 [-0.2939; 0.2244] 3.86 48.2%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.16 2 0.5612
## Within groups 4.76 4 0.3127
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 1 -0.4165 [-1.4105; 0.5775] -- --
## 5 - 10 weeks 3 -0.2876 [-0.7956; 0.2205] 0 0
## > 10 weeks 3 0.0115 [-0.4491; 0.4721] 0.0828 0.2878
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.03 2 0.5977
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0026 (SE = 0.0860)
## tau (square root of estimated tau^2 value): 0.0511
## I^2 (residual heterogeneity / unaccounted variability): 1.92%
## H^2 (unaccounted variability / sampling variability): 1.02
## R^2 (amount of heterogeneity accounted for): 69.18%
##
## Test for Residual Heterogeneity:
## QE(df = 5) = 5.0980, p-val = 0.4040
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.3101, p-val = 0.2524
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.5929 0.4387 -1.3515 0.1765 -1.4526 0.2669
## duration 0.0465 0.0407 1.1446 0.2524 -0.0332 0.1262
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 > 0.5
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 < 0.5
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 < 0.5
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 > 0.5
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 > 0.5
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 > 0.5
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 < 0.5
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 4.9% [0.0%; 75.9%]; H = 1.03 [1.00; 2.04]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 3 -0.3018 [-0.8306; 0.2270] 0.40 0.0%
## > 0.5 4 -0.0601 [-0.3086; 0.1884] 4.86 38.3%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.66 1 0.4175
## Within groups 5.26 5 0.3851
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 3 -0.3018 [-0.8306; 0.2270] 0 0
## > 0.5 4 -0.0504 [-0.4433; 0.3425] 0.0624 0.2499
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.56 1 0.4544
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0276 (SE = 0.1020)
## tau (square root of estimated tau^2 value): 0.1663
## I^2 (residual heterogeneity / unaccounted variability): 17.24%
## H^2 (unaccounted variability / sampling variability): 1.21
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 5) = 6.0415, p-val = 0.3022
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3146, p-val = 0.5748
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.3912 0.5038 -0.7765 0.4374 -1.3786 0.5962
## men_ratio 0.3595 0.6409 0.5609 0.5748 -0.8966 1.6156
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 Cycling
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 Cycling
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 Cycling
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 Running
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 Running
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 Cycling
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 Cycling
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 69.4%]; H = 1.00 [1.00; 1.81]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 5 -0.1807 [-0.4324; 0.0711] 1.87 0.0%
## Running 2 0.1994 [-0.3008; 0.6996] 2.28 56.1%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.77 1 0.1835
## Within groups 4.15 5 0.5285
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 5 -0.1807 [-0.4324; 0.0711] 0 0
## Running 2 0.1789 [-0.5784; 0.9361] 0.1676 0.4094
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.78 1 0.3772
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0879)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 5) = 4.5375, p-val = 0.4749
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.8752, p-val = 0.1709
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1873 0.1284 -1.4592 0.1445 -0.4389 0.0643
## type_exerciseRunning 0.3909 0.2855 1.3694 0.1709 -0.1686 0.9505
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 < 2 mg/L
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 < 2 mg/L
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 > 2 mg/L
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 < 2 mg/L
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 > 2 mg/L
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 > 2 mg/L
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 > 2 mg/L
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 12.1% [0.0%; 77.7%]; H = 1.07 [1.00; 2.12]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 2 mg/L 3 -0.1385 [-0.4045; 0.1276] 0.42 0.0%
## > 2 mg/L 4 -0.0172 [-0.4380; 0.4037] 5.27 43.1%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.23 1 0.6331
## Within groups 5.69 5 0.3377
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 2 mg/L 3 -0.1385 [-0.4045; 0.1276] 0 0
## > 2 mg/L 4 -0.0844 [-0.6548; 0.4860] 0.1453 0.3812
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.03 1 0.8663
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0379 (SE = 0.1128)
## tau (square root of estimated tau^2 value): 0.1946
## I^2 (residual heterogeneity / unaccounted variability): 21.37%
## H^2 (unaccounted variability / sampling variability): 1.27
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 5) = 6.3588, p-val = 0.2729
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0279, p-val = 0.8674
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1719 0.3218 -0.5340 0.5933 -0.8027 0.4589
## bsln_adjusted 0.0226 0.1353 0.1669 0.8674 -0.2426 0.2877
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Conraads 2015 -0.1003 [-0.3978; 0.1971] 57.1 50.5 HIIT
## Hovanloo 2013 -0.4405 [-1.4323; 0.5513] 5.1 6.0 SIT
## Keating 2014 -0.4402 [-1.2860; 0.4056] 7.1 8.2 HIIT
## Kim 2015 -0.2307 [-0.9739; 0.5126] 9.1 10.5 HIIT
## Madssen 2014 0.5620 [-0.1132; 1.2371] 11.1 12.5 HIIT
## Nalcakan 2014 -0.7619 [-1.8123; 0.2885] 4.6 5.4 SIT
## Sawyer 2016 -0.0607 [-0.9849; 0.8634] 5.9 6.9 HIIT
##
## Number of studies combined: k = 7
##
## SMD 95%-CI z p-value
## Fixed effect model -0.1083 [-0.3330; 0.1165] -0.94 0.3450
## Random effects model -0.1122 [-0.3595; 0.1351] -0.89 0.3740
##
## Quantifying heterogeneity:
## tau^2 = 0.0085 [0.0000; 0.6243]; tau = 0.0921 [0.0000; 0.7901];
## I^2 = 6.4% [0.0%; 72.7%]; H = 1.03 [1.00; 1.91]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 70.1%]; H = 1.00 [1.00; 1.83]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.41 6 0.3786
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 5 -0.0554 [-0.2920; 0.1812] 4.08 2.0%
## SIT 2 -0.5575 [-1.2818; 0.1668] 0.16 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.67 1 0.1965
## Within groups 4.25 5 0.5143
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 5 -0.0536 [-0.2976; 0.1903] 0.0022 0.0464
## SIT 2 -0.5575 [-1.2818; 0.1668] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.67 1 0.1963
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 7; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0745)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 5) = 4.4981, p-val = 0.4801
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.9145, p-val = 0.1665
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0562 0.1207 -0.4660 0.6412 -0.2928 0.1803
## HIIESIT -0.5358 0.3872 -1.3837 0.1665 -1.2947 0.2231
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Ciolac 2010 0.0168 [-0.1788; 0.2123] 0.8664 0.0000 0.0000 0.0%
## Omitting Gillen 2016 0.0257 [-0.1691; 0.2206] 0.7957 0.0000 0.0000 0.0%
## Omitting Grieco 2013 0.0081 [-0.1873; 0.2036] 0.9350 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) 0.0156 [-0.1814; 0.2127] 0.8765 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) 0.0264 [-0.1677; 0.2205] 0.7898 0.0000 0.0000 0.0%
## Omitting Keating 2014 0.0282 [-0.1673; 0.2238] 0.7771 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 0.0252 [-0.1709; 0.2213] 0.8011 0.0000 0.0000 0.0%
## Omitting Motiani 2017 0.0041 [-0.1923; 0.2006] 0.9670 0.0000 0.0000 0.0%
## Omitting Ramos 2016a 0.0642 [-0.1365; 0.2649] 0.5308 0.0000 0.0000 0.0%
## Omitting Robinson 2015 -0.0003 [-0.2001; 0.1994] 0.9973 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 0.0419 [-0.1538; 0.2377] 0.6746 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 0.0268 [-0.1678; 0.2214] 0.7875 0.0000 0.0000 0.0%
## Omitting Sjöros 2018 0.0232 [-0.1722; 0.2185] 0.8163 0.0000 0.0000 0.0%
## Omitting Skleryk 2013 0.0262 [-0.1680; 0.2203] 0.7917 0.0000 0.0000 0.0%
## Omitting Tjønna 2008 0.0261 [-0.1686; 0.2208] 0.7928 0.0000 0.0000 0.0%
## Omitting Trapp 2008 -0.0212 [-0.2184; 0.1759] 0.8327 0.0000 0.0000 0.0%
## Omitting Winn 2018 0.0619 [-0.1316; 0.2554] 0.5306 0.0000 0.0000 0.0%
## Omitting Zapata-Lamana 2018 0.0430 [-0.1540; 0.2400] 0.6688 0.0000 0.0000 0.0%
##
## Pooled estimate 0.0237 [-0.1666; 0.2139] 0.8074 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.0237 [-0.1666; 0.2139] Overall
## Healthy 0.2174 [-0.0862; 0.5211] Population
## Overweight/obese -0.2396 [-0.6377; 0.1586] Population
## Metabolic Syndrome -0.0270 [-0.3798; 0.3258] Population
## T2D 0.0201 [-0.6270; 0.6672] Population
## < 30 y 0.1180 [-0.2122; 0.4481] Age
## 30 - 50 y -0.0138 [-0.3034; 0.2757] Age
## > 50 y -0.0370 [-0.4301; 0.3562] Age
## < 5 weeks 0.0902 [-0.2025; 0.3829] Training Duration
## 5 - 10 weeks -0.1005 [-0.5879; 0.3869] Training Duration
## > 10 weeks 0.0041 [-0.2884; 0.2965] Training Duration
## < 0.5 0.0417 [-0.2249; 0.3083] Men Ratio
## > 0.5 -0.0012 [-0.2845; 0.2821] Men Ratio
## Running -0.2694 [-0.6293; 0.0906] Type of Exercise
## Cycling 0.1389 [-0.0856; 0.3633] Type of Exercise
## < 40 pmol/L 0.1317 [-0.1912; 0.4546] Baseline Values
## > 40 pmol/L -0.0553 [-0.3020; 0.1914] Baseline Values
## HIIT -0.0625 [-0.3116; 0.1865] Type of HIIE
## SIT 0.1472 [-0.1483; 0.4427] Type of HIIE
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0; tau = 0; I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Population 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Age 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Training Duration 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Men Ratio 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Type of Exercise 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Baseline Values 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
## Type of HIIE 18 0.0237 [-0.1666; 0.2139] 0 0 12.88 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 Healthy
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 Healthy
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 Healthy
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 Healthy
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 T2D
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 Overweight/obese
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 Metabolic Syndrome
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 Healthy
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 Metabolic Syndrome
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 Metabolic Syndrome
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 Healthy
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 Overweight/obese
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 T2D
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 Overweight/obese
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 Metabolic Syndrome
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 Healthy
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 Overweight/obese
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 Overweight/obese
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 23.1%]; H = 1.00 [1.00; 1.14]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 7 0.2174 [-0.0862; 0.5211] 3.28 0.0%
## Overweight/obese 5 -0.2396 [-0.6377; 0.1586] 3.29 0.0%
## Metabolic Syndrome 4 -0.0270 [-0.3798; 0.3258] 1.87 0.0%
## T2D 2 0.0201 [-0.6270; 0.6672] 0.01 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 3.32 3 0.3445
## Within groups 8.45 14 0.8646
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 7 0.2174 [-0.0862; 0.5211] 0 0
## Overweight/obese 5 -0.2396 [-0.6377; 0.1586] 0 0
## Metabolic Syndrome 4 -0.0270 [-0.3798; 0.3258] 0 0
## T2D 2 0.0201 [-0.6270; 0.6672] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.32 3 0.3445
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0648)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 14) = 9.2220, p-val = 0.8166
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 3.6531, p-val = 0.3014
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2245 0.1548 1.4503 0.1470 -0.0789 0.5279
## .byvarOverweight/obese -0.4795 0.2551 -1.8799 0.0601 -0.9794 0.0204 .
## .byvarMetabolic Syndrome -0.2519 0.2374 -1.0609 0.2887 -0.7171 0.2134
## .byvarT2D -0.2037 0.3647 -0.5587 0.5764 -0.9184 0.5110
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 < 30 y
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 < 30 y
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 < 30 y
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 30 - 50 y
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 30 - 50 y
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 30 - 50 y
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 30 - 50 y
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 30 - 50 y
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 > 50 y
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 > 50 y
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 < 30 y
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 30 - 50 y
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 30 - 50 y
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 30 - 50 y
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 > 50 y
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 < 30 y
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 30 - 50 y
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 < 30 y
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 36.7%]; H = 1.00 [1.00; 1.26]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 6 0.1180 [-0.2122; 0.4481] 4.24 0.0%
## 30 - 50 y 9 -0.0138 [-0.3034; 0.2757] 5.20 0.0%
## > 50 y 3 -0.0370 [-0.4301; 0.3562] 1.86 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.47 2 0.7909
## Within groups 11.30 15 0.7308
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 6 0.1180 [-0.2122; 0.4481] 0 0
## 30 - 50 y 9 -0.0138 [-0.3034; 0.2757] 0 0
## > 50 y 3 -0.0370 [-0.4301; 0.3562] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.47 2 0.7909
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0611)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 16) = 12.3043, p-val = 0.7228
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.5709, p-val = 0.4499
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2613 0.3291 0.7939 0.4273 -0.3838 0.9063
## age -0.0059 0.0078 -0.7556 0.4499 -0.0213 0.0094
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 > 10 weeks
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 > 10 weeks
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 < 5 weeks
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 < 5 weeks
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 < 5 weeks
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 > 10 weeks
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 5 - 10 weeks
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 < 5 weeks
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 > 10 weeks
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 < 5 weeks
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 5 - 10 weeks
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 5 - 10 weeks
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 < 5 weeks
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 < 5 weeks
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 > 10 weeks
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 > 10 weeks
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 < 5 weeks
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 > 10 weeks
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 36.7%]; H = 1.00 [1.00; 1.26]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 8 0.0902 [-0.2025; 0.3829] 6.15 0.0%
## 5 - 10 weeks 3 -0.1005 [-0.5879; 0.3869] 0.29 0.0%
## > 10 weeks 7 0.0041 [-0.2884; 0.2965] 4.87 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.47 2 0.7925
## Within groups 11.31 15 0.7305
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 8 0.0902 [-0.2025; 0.3829] 0 0
## 5 - 10 weeks 3 -0.1005 [-0.5879; 0.3869] 0 0
## > 10 weeks 7 0.0041 [-0.2884; 0.2965] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.47 2 0.7925
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0611)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 16) = 12.7039, p-val = 0.6943
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1713, p-val = 0.6789
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0827 0.1726 0.4794 0.6317 -0.2556 0.4211
## duration -0.0071 0.0172 -0.4139 0.6789 -0.0408 0.0266
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 < 0.5
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 > 0.5
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 < 0.5
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 > 0.5
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 > 0.5
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 < 0.5
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 > 0.5
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 > 0.5
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 > 0.5
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 < 0.5
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 < 0.5
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 < 0.5
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 > 0.5
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 > 0.5
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 < 0.5
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 < 0.5
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 < 0.5
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 < 0.5
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 33.2%]; H = 1.00 [1.00; 1.22]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 10 0.0459 [-0.2114; 0.3031] 9.62 6.4%
## > 0.5 8 -0.0012 [-0.2845; 0.2821] 2.10 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.06 1 0.8095
## Within groups 11.72 16 0.7634
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 10 0.0417 [-0.2249; 0.3083] 0.0119 0.1091
## > 0.5 8 -0.0012 [-0.2845; 0.2821] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.05 1 0.8288
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0606)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 16) = 12.7336, p-val = 0.6921
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1415, p-val = 0.7067
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0751 0.1677 0.4479 0.6542 -0.2536 0.4039
## men_ratio -0.0983 0.2614 -0.3762 0.7067 -0.6106 0.4139
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 Running
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 Cycling
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 Cycling
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 Cycling
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 Cycling
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 Cycling
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 Cycling
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 Cycling
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 Running
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 Cycling
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 Running
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 Cycling
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 Cycling
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 Cycling
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 Running
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 Cycling
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 Running
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 Cycling
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 4.7%]; H = 1.00 [1.00; 1.02]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 5 -0.2694 [-0.6293; 0.0906] 3.89 0.0%
## Cycling 13 0.1389 [-0.0856; 0.3633] 4.32 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 3.56 1 0.0592
## Within groups 8.21 16 0.9422
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 5 -0.2694 [-0.6293; 0.0906] 0 0
## Cycling 13 0.1389 [-0.0856; 0.3633] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.56 1 0.0592
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0609)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 16) = 8.9933, p-val = 0.9137
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 3.8819, p-val = 0.0488
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1431 0.1145 1.2504 0.2112 -0.0812 0.3674
## type_exerciseRunning -0.4257 0.2161 -1.9703 0.0488 -0.8493 -0.0022 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 > 40 pmol/L
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 > 40 pmol/L
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 < 40 pmol/L
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 < 40 pmol/L
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 > 40 pmol/L
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 > 40 pmol/L
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 > 40 pmol/L
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 < 40 pmol/L
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 > 40 pmol/L
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 > 40 pmol/L
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 > 40 pmol/L
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 < 40 pmol/L
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 < 40 pmol/L
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 < 40 pmol/L
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 > 40 pmol/L
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 < 40 pmol/L
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 < 40 pmol/L
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 > 40 pmol/L
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 27.4%]; H = 1.00 [1.00; 1.17]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 40 pmol/L 8 0.1423 [-0.1572; 0.4419] 8.07 13.2%
## > 40 pmol/L 10 -0.0553 [-0.3020; 0.1914] 2.71 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.00 1 0.3183
## Within groups 10.78 16 0.8230
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 40 pmol/L 8 0.1317 [-0.1912; 0.4546] 0.0288 0.1696
## > 40 pmol/L 10 -0.0553 [-0.3020; 0.1914] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.81 1 0.3673
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0608)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 16) = 12.0213, p-val = 0.7425
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.8539, p-val = 0.3555
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1647 0.1809 0.9105 0.3625 -0.1898 0.5192
## bsln_adjusted -0.0022 0.0024 -0.9240 0.3555 -0.0069 0.0025
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Ciolac 2010 0.1742 [-0.6631; 1.0115] 5.2 5.2 HIIT
## Gillen 2016 0.0000 [-0.9005; 0.9005] 4.5 4.5 SIT
## Grieco 2013 0.3461 [-0.4993; 1.1915] 5.1 5.1 HIIT
## Honkala 2017 (Healthy) 0.1562 [-0.5857; 0.8981] 6.6 6.6 SIT
## Honkala 2017 (T2D) -0.0238 [-1.0115; 0.9640] 3.7 3.7 SIT
## Keating 2014 -0.0439 [-0.8797; 0.7919] 5.2 5.2 HIIT
## Matsuo 2015 0.0148 [-0.7854; 0.8150] 5.7 5.7 HIIT
## Motiani 2017 0.3542 [-0.4206; 1.1289] 6.0 6.0 SIT
## Ramos 2016a -0.3385 [-0.9407; 0.2637] 10.0 10.0 HIIT
## Robinson 2015 0.2792 [-0.3518; 0.9101] 9.1 9.1 HIIT
## Sandvei 2012 -0.2927 [-1.1152; 0.5298] 5.4 5.4 SIT
## Sawyer 2016 -0.0258 [-0.9498; 0.8982] 4.2 4.2 HIIT
## Sjöros 2018 0.0543 [-0.8022; 0.9108] 4.9 4.9 SIT
## Skleryk 2013 -0.0164 [-0.9964; 0.9636] 3.8 3.8 SIT
## Tjønna 2008 -0.0090 [-0.9197; 0.9018] 4.4 4.4 HIIT
## Trapp 2008 0.6862 [-0.0503; 1.4226] 6.7 6.7 SIT
## Winn 2018 -1.2046 [-2.2698; -0.1395] 3.2 3.2 HIIT
## Zapata-Lamana 2018 -0.2451 [-0.9887; 0.4985] 6.5 6.5 HIIT
##
## Number of studies combined: k = 18
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
## Random effects model 0.0237 [-0.1666; 0.2139] 0.24 0.8074
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.1336]; tau = 0 [0.0000; 0.3655];
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 26.5%]; H = 1.00 [1.00; 1.17]
##
## Test of heterogeneity:
## Q d.f. p-value
## 12.88 17 0.7445
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 10 -0.0625 [-0.3116; 0.1865] 7.07 0.0%
## SIT 8 0.1472 [-0.1483; 0.4427] 3.57 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.13 1 0.2874
## Within groups 10.64 16 0.8311
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 10 -0.0625 [-0.3116; 0.1865] 0 0
## SIT 8 0.1472 [-0.1483; 0.4427] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.13 1 0.2874
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 18; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0606)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 16) = 11.6417, p-val = 0.7683
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.2335, p-val = 0.2667
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0672 0.1269 -0.5291 0.5967 -0.3160 0.1816
## HIIESIT 0.2188 0.1970 1.1106 0.2667 -0.1673 0.6050
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Ciolac 2010 0.0136 [-0.1681; 0.1954] 0.8833 0.0586 0.2420 29.5%
## Omitting Conraads 2015 0.0229 [-0.1708; 0.2167] 0.8166 0.0712 0.2668 29.7%
## Omitting Eguchi 2012 0.0086 [-0.1720; 0.1892] 0.9255 0.0567 0.2380 28.9%
## Omitting Gillen 2016 0.0181 [-0.1635; 0.1996] 0.8454 0.0588 0.2425 29.7%
## Omitting Grieco 2013 -0.0073 [-0.1818; 0.1672] 0.9345 0.0446 0.2112 24.2%
## Omitting Honkala 2017 (Healthy) 0.0378 [-0.1393; 0.2149] 0.6756 0.0483 0.2197 25.5%
## Omitting Honkala 2017 (T2D) -0.0163 [-0.1779; 0.1452] 0.8428 0.0240 0.1549 14.8%
## Omitting Jo 2020 0.0194 [-0.1643; 0.2031] 0.8358 0.0601 0.2452 29.7%
## Omitting Keating 2014 -0.0041 [-0.1804; 0.1722] 0.9637 0.0480 0.2191 25.6%
## Omitting Lira 2017 0.0334 [-0.1440; 0.2108] 0.7119 0.0505 0.2248 26.6%
## Omitting Madssen 2014 0.0021 [-0.1792; 0.1834] 0.9818 0.0551 0.2347 27.9%
## Omitting Maillard 2016 0.0162 [-0.1648; 0.1972] 0.8608 0.0585 0.2418 29.6%
## Omitting Matsuo 2015 0.0283 [-0.1525; 0.2092] 0.7589 0.0564 0.2374 28.7%
## Omitting Mitranun 2014 0.0184 [-0.1646; 0.2013] 0.8441 0.0596 0.2441 29.7%
## Omitting Motiani 2017 0.0183 [-0.1643; 0.2009] 0.8441 0.0594 0.2438 29.7%
## Omitting Ramos 2016a 0.0397 [-0.1397; 0.2192] 0.6643 0.0502 0.2240 25.8%
## Omitting Ramos 2016b 0.0214 [-0.1619; 0.2047] 0.8190 0.0597 0.2444 29.6%
## Omitting Robinson 2015 0.0482 [-0.1228; 0.2192] 0.5804 0.0353 0.1878 19.8%
## Omitting Sandvei 2012 0.0182 [-0.1639; 0.2004] 0.8446 0.0592 0.2432 29.7%
## Omitting Sawyer 2016 -0.0082 [-0.1804; 0.1641] 0.9259 0.0414 0.2036 23.0%
## Omitting Sjöros 2018 -0.0047 [-0.1804; 0.1710] 0.9583 0.0470 0.2169 25.2%
## Omitting Skleryk 2013 0.0327 [-0.1434; 0.2088] 0.7158 0.0490 0.2214 26.1%
## Omitting Tjønna 2008 -0.0032 [-0.1789; 0.1724] 0.9713 0.0476 0.2181 25.5%
## Omitting Trapp 2008 0.0048 [-0.1765; 0.1860] 0.9590 0.0560 0.2366 28.3%
## Omitting Winn 2018 0.0370 [-0.1316; 0.2056] 0.6672 0.0354 0.1882 20.4%
## Omitting Zapata-Lamana 2018 0.0284 [-0.1531; 0.2100] 0.7588 0.0569 0.2386 28.7%
##
## Pooled estimate 0.0224 [-0.1617; 0.2066] 0.8114 0.0711 0.2667 33.6%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## 0.0224 [-0.1617; 0.2066] Overall
## Healthy 0.0316 [-0.2417; 0.3049] Population
## Overweight/obese -0.0805 [-0.7515; 0.5904] Population
## Cardiac Rehabilitation 0.0406 [-0.2309; 0.3121] Population
## Metabolic Syndrome -0.1970 [-0.5145; 0.1205] Population
## T2D 0.4465 [-0.1372; 1.0302] Population
## < 30 y 0.0512 [-0.2580; 0.3603] Age
## 30 - 50 y 0.0884 [-0.3905; 0.5673] Age
## > 50 y -0.0391 [-0.2272; 0.1490] Age
## < 5 weeks -0.1055 [-0.5849; 0.3739] Training Duration
## 5 - 10 weeks 0.0523 [-0.2985; 0.4032] Training Duration
## > 10 weeks 0.0542 [-0.1296; 0.2381] Training Duration
## < 0.5 0.0902 [-0.2156; 0.3961] Men Ratio
## > 0.5 -0.0327 [-0.2420; 0.1766] Men Ratio
## Running -0.0716 [-0.3185; 0.1753] Type of Exercise
## Cycling 0.0837 [-0.1607; 0.3282] Type of Exercise
## < 5.6 mmol/L 0.0276 [-0.1913; 0.2465] Baseline Values
## > 5.6 mmol/L 0.0139 [-0.2785; 0.3062] Baseline Values
## HIIT -0.0131 [-0.2091; 0.1830] Type of HIIE
## SIT 0.1009 [-0.2898; 0.4916] Type of HIIE
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711; tau = 0.2667; I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Population 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Age 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Training Duration 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Men Ratio 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Type of Exercise 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Baseline Values 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
## Type of HIIE 26 0.0224 [-0.1617; 0.2066] 0.0711 0.2667 37.65 33.6%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 Healthy
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 Cardiac Rehabilitation
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 Healthy
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 Healthy
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 Healthy
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 Healthy
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 T2D
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 Metabolic Syndrome
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 Overweight/obese
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 Healthy
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 Cardiac Rehabilitation
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 T2D
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 Metabolic Syndrome
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 T2D
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 Healthy
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 Metabolic Syndrome
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 Metabolic Syndrome
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 Metabolic Syndrome
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 Healthy
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 Overweight/obese
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 T2D
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 Overweight/obese
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 Metabolic Syndrome
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 Healthy
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 Overweight/obese
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 Overweight/obese
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 27.3% [0.0%; 56.8%]; H = 1.17 [1.00; 1.52]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 9 0.0316 [-0.2417; 0.3049] 6.65 0.0%
## Overweight/obese 5 -0.0528 [-0.4590; 0.3534] 10.60 62.3%
## Cardiac Rehabilitation 2 0.0406 [-0.2309; 0.3121] 0.75 0.0%
## Metabolic Syndrome 6 -0.2078 [-0.4954; 0.0798] 6.02 16.9%
## T2D 4 0.4010 [-0.0497; 0.8518] 4.85 38.2%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 5.25 4 0.2628
## Within groups 28.88 21 0.1169
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 9 0.0316 [-0.2417; 0.3049] 0 0
## Overweight/obese 5 -0.0805 [-0.7515; 0.5904] 0.3615 0.6012
## Cardiac Rehabilitation 2 0.0406 [-0.2309; 0.3121] 0 0
## Metabolic Syndrome 6 -0.1970 [-0.5145; 0.1205] 0.0267 0.1633
## T2D 4 0.4465 [-0.1372; 1.0302] 0.1352 0.3676
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.92 4 0.4174
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0831 (SE = 0.0760)
## tau (square root of estimated tau^2 value): 0.2883
## I^2 (residual heterogeneity / unaccounted variability): 34.08%
## H^2 (unaccounted variability / sampling variability): 1.52
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 21) = 31.8581, p-val = 0.0605
##
## Test of Moderators (coefficients 2:5):
## QM(df = 4) = 4.0100, p-val = 0.4046
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0344 0.1697 0.2025 0.8395 -0.2982 0.3670
## .byvarOverweight/obese -0.1043 0.2980 -0.3499 0.7264 -0.6884 0.4798
## .byvarCardiac Rehabilitation 0.0677 0.3130 0.2162 0.8288 -0.5458 0.6812
## .byvarMetabolic Syndrome -0.2180 0.2545 -0.8564 0.3918 -0.7168 0.2809
## .byvarT2D 0.4278 0.3216 1.3305 0.1834 -0.2024 1.0581
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 < 30 y
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 > 50 y
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 > 50 y
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 < 30 y
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 < 30 y
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 30 - 50 y
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 30 - 50 y
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 > 50 y
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 30 - 50 y
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 < 30 y
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 > 50 y
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 > 50 y
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 30 - 50 y
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 > 50 y
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 30 - 50 y
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 > 50 y
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 > 50 y
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 > 50 y
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 < 30 y
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 30 - 50 y
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 30 - 50 y
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 30 - 50 y
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 > 50 y
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 < 30 y
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 30 - 50 y
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 < 30 y
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 31.7% [0.0%; 58.5%]; H = 1.21 [1.00; 1.55]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 7 0.0512 [-0.2580; 0.3603] 4.81 0.0%
## 30 - 50 y 9 0.0607 [-0.2368; 0.3582] 20.26 60.5%
## > 50 y 10 -0.0391 [-0.2272; 0.1490] 8.63 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.43 2 0.8064
## Within groups 33.70 23 0.0696
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 7 0.0512 [-0.2580; 0.3603] 0 0
## 30 - 50 y 9 0.0884 [-0.3905; 0.5673] 0.3205 0.5662
## > 50 y 10 -0.0391 [-0.2272; 0.1490] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.40 2 0.8191
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0804 (SE = 0.0672)
## tau (square root of estimated tau^2 value): 0.2835
## I^2 (residual heterogeneity / unaccounted variability): 35.72%
## H^2 (unaccounted variability / sampling variability): 1.56
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 37.3371, p-val = 0.0405
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1380, p-val = 0.7103
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1418 0.3318 0.4275 0.6690 -0.5084 0.7921
## age -0.0026 0.0070 -0.3715 0.7103 -0.0164 0.0112
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 > 10 weeks
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 > 10 weeks
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 > 10 weeks
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 > 10 weeks
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 < 5 weeks
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 < 5 weeks
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 < 5 weeks
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 5 - 10 weeks
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 > 10 weeks
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 < 5 weeks
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 > 10 weeks
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 > 10 weeks
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 5 - 10 weeks
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 5 - 10 weeks
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 < 5 weeks
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 > 10 weeks
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 > 10 weeks
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 < 5 weeks
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 5 - 10 weeks
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 5 - 10 weeks
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 < 5 weeks
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 < 5 weeks
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 > 10 weeks
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 > 10 weeks
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 < 5 weeks
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 > 10 weeks
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 29.4% [0.0%; 57.2%]; H = 1.19 [1.00; 1.53]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 9 -0.1554 [-0.4404; 0.1295] 21.81 63.3%
## 5 - 10 weeks 5 0.0523 [-0.2985; 0.4032] 3.30 0.0%
## > 10 weeks 12 0.0542 [-0.1296; 0.2381] 7.46 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.56 2 0.4581
## Within groups 32.57 23 0.0889
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 9 -0.1055 [-0.5849; 0.3739] 0.3337 0.5777
## 5 - 10 weeks 5 0.0523 [-0.2985; 0.4032] 0 0
## > 10 weeks 12 0.0542 [-0.1296; 0.2381] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.38 2 0.8268
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0748 (SE = 0.0649)
## tau (square root of estimated tau^2 value): 0.2736
## I^2 (residual heterogeneity / unaccounted variability): 34.60%
## H^2 (unaccounted variability / sampling variability): 1.53
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 36.6967, p-val = 0.0469
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.6565, p-val = 0.4178
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1200 0.2004 -0.5990 0.5492 -0.5128 0.2727
## duration 0.0152 0.0187 0.8102 0.4178 -0.0215 0.0519
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 < 0.5
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 > 0.5
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 > 0.5
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 > 0.5
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 < 0.5
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 > 0.5
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 > 0.5
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 > 0.5
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 < 0.5
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 > 0.5
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 > 0.5
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 < 0.5
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 > 0.5
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 < 0.5
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 > 0.5
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 > 0.5
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 > 0.5
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 < 0.5
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 < 0.5
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 < 0.5
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 > 0.5
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 > 0.5
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 < 0.5
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 < 0.5
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 < 0.5
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 < 0.5
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 28.7% [0.0%; 56.4%]; H = 1.18 [1.00; 1.51]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 12 0.0681 [-0.1699; 0.3061] 17.76 38.1%
## > 0.5 14 -0.0336 [-0.2093; 0.1422] 15.91 18.3%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.45 1 0.5006
## Within groups 33.67 24 0.0906
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 12 0.0902 [-0.2156; 0.3961] 0.1097 0.3312
## > 0.5 14 -0.0327 [-0.2420; 0.1766] 0.0278 0.1668
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.42 1 0.5156
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0811 (SE = 0.0673)
## tau (square root of estimated tau^2 value): 0.2847
## I^2 (residual heterogeneity / unaccounted variability): 36.00%
## H^2 (unaccounted variability / sampling variability): 1.56
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 37.4985, p-val = 0.0390
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1297, p-val = 0.7188
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0817 0.1869 0.4369 0.6622 -0.2847 0.4480
## men_ratio -0.0977 0.2712 -0.3601 0.7188 -0.6293 0.4339
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 Running
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 Cycling
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 Cycling
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 Cycling
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 Cycling
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 Cycling
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 Cycling
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 Running
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 Cycling
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 Running
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 Running
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 Cycling
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 Cycling
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 Running
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 Cycling
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 Running
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 Running
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 Cycling
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 Running
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 Cycling
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 Cycling
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 Cycling
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 Running
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 Cycling
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 Running
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 Cycling
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 28.5% [0.0%; 56.3%]; H = 1.18 [1.00; 1.51]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Running 10 -0.0715 [-0.3122; 0.1691] 9.42 4.5%
## Cycling 16 0.0412 [-0.1335; 0.2159] 24.15 37.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.55 1 0.4575
## Within groups 33.58 24 0.0925
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Running 10 -0.0716 [-0.3185; 0.1753] 0.0072 0.0849
## Cycling 16 0.0837 [-0.1607; 0.3282] 0.0856 0.2925
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.77 1 0.3808
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0781 (SE = 0.0664)
## tau (square root of estimated tau^2 value): 0.2794
## I^2 (residual heterogeneity / unaccounted variability): 35.13%
## H^2 (unaccounted variability / sampling variability): 1.54
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 36.9987, p-val = 0.0438
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.7391, p-val = 0.3900
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0892 0.1224 0.7292 0.4659 -0.1506 0.3290
## type_exerciseRunning -0.1684 0.1958 -0.8597 0.3900 -0.5522 0.2155
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 < 5.6 mmol/L
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 < 5.6 mmol/L
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 < 5.6 mmol/L
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 < 5.6 mmol/L
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 < 5.6 mmol/L
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 < 5.6 mmol/L
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 > 5.6 mmol/L
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 > 5.6 mmol/L
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 < 5.6 mmol/L
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 < 5.6 mmol/L
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 > 5.6 mmol/L
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 > 5.6 mmol/L
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 > 5.6 mmol/L
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 > 5.6 mmol/L
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 < 5.6 mmol/L
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 > 5.6 mmol/L
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 > 5.6 mmol/L
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 > 5.6 mmol/L
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 < 5.6 mmol/L
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 < 5.6 mmol/L
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 > 5.6 mmol/L
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 > 5.6 mmol/L
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 > 5.6 mmol/L
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 < 5.6 mmol/L
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 < 5.6 mmol/L
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 < 5.6 mmol/L
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 29.5% [0.0%; 56.8%]; H = 1.19 [1.00; 1.52]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5.6 mmol/L 14 0.0198 [-0.1634; 0.2030] 15.74 17.4%
## > 5.6 mmol/L 12 -0.0235 [-0.2458; 0.1989] 18.30 39.9%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.09 1 0.7684
## Within groups 34.04 24 0.0839
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5.6 mmol/L 14 0.0276 [-0.1913; 0.2465] 0.0291 0.1705
## > 5.6 mmol/L 12 0.0139 [-0.2785; 0.3062] 0.1037 0.3221
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.01 1 0.9412
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0798 (SE = 0.0663)
## tau (square root of estimated tau^2 value): 0.2825
## I^2 (residual heterogeneity / unaccounted variability): 36.25%
## H^2 (unaccounted variability / sampling variability): 1.57
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 37.6474, p-val = 0.0377
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.0224, p-val = 0.8809
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0568 0.5465 -0.1040 0.9172 -1.1280 1.0144
## bsln_adjusted 0.0140 0.0936 0.1498 0.8809 -0.1695 0.1975
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Ciolac 2010 0.1301 [-0.7065; 0.9667] 2.8 3.5 HIIT
## Conraads 2015 -0.0131 [-0.3103; 0.2842] 22.6 9.4 HIIT
## Eguchi 2012 0.2888 [-0.5923; 1.1699] 2.6 3.2 HIIT
## Gillen 2016 0.0000 [-0.9005; 0.9005] 2.5 3.1 SIT
## Grieco 2013 0.7150 [-0.1504; 1.5804] 2.7 3.3 HIIT
## Honkala 2017 (Healthy) -0.5370 [-1.2910; 0.2171] 3.5 4.0 SIT
## Honkala 2017 (T2D) 1.4863 [ 0.3724; 2.6002] 1.6 2.2 SIT
## Jo 2020 -0.0169 [-0.6892; 0.6554] 4.4 4.7 HIIT
## Keating 2014 0.6187 [-0.2368; 1.4742] 2.7 3.4 HIIT
## Lira 2017 -0.5603 [-1.4539; 0.3332] 2.5 3.2 HIIT
## Madssen 2014 0.3177 [-0.3489; 0.9844] 4.5 4.7 HIIT
## Maillard 2016 0.0663 [-0.9140; 1.0465] 2.1 2.7 HIIT
## Matsuo 2015 -0.2904 [-1.0947; 0.5140] 3.1 3.7 HIIT
## Mitranun 2014 0.0012 [-0.7396; 0.7420] 3.6 4.1 HIIT
## Motiani 2017 -0.0000 [-0.7688; 0.7688] 3.4 3.9 SIT
## Ramos 2016a -0.4043 [-1.0083; 0.1998] 5.5 5.3 HIIT
## Ramos 2016b -0.0631 [-0.7575; 0.6314] 4.1 4.5 HIIT
## Robinson 2015 -0.6719 [-1.3172; -0.0265] 4.8 4.9 HIIT
## Sandvei 2012 0.0000 [-0.8181; 0.8181] 3.0 3.6 SIT
## Sawyer 2016 0.8925 [-0.0763; 1.8613] 2.1 2.8 HIIT
## Sjöros 2018 0.6632 [-0.2163; 1.5427] 2.6 3.2 SIT
## Skleryk 2013 -0.6900 [-1.6987; 0.3187] 2.0 2.6 SIT
## Tjønna 2008 0.6903 [-0.2465; 1.6271] 2.3 2.9 HIIT
## Trapp 2008 0.2981 [-0.4215; 1.0178] 3.8 4.3 SIT
## Winn 2018 -1.1390 [-2.1954; -0.0825] 1.8 2.4 HIIT
## Zapata-Lamana 2018 -0.2544 [-0.9982; 0.4894] 3.6 4.1 HIIT
##
## Number of studies combined: k = 26
##
## SMD 95%-CI z p-value
## Fixed effect model 0.0044 [-0.1368; 0.1456] 0.06 0.9512
## Random effects model 0.0224 [-0.1617; 0.2066] 0.24 0.8114
##
## Quantifying heterogeneity:
## tau^2 = 0.0711 [0.0025; 0.3551]; tau = 0.2667 [0.0495; 0.5959];
## I^2 = 33.6% [0.0%; 58.8%]; H = 1.23 [1.00; 1.56]
##
## Quantifying residual heterogeneity:
## I^2 = 28.9% [0.0%; 56.5%]; H = 1.19 [1.00; 1.52]
##
## Test of heterogeneity:
## Q d.f. p-value
## 37.65 25 0.0500
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 18 -0.0206 [-0.1810; 0.1397] 22.14 23.2%
## SIT 8 0.0824 [-0.2173; 0.3822] 11.63 39.8%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.35 1 0.5523
## Within groups 33.78 24 0.0887
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 18 -0.0131 [-0.2091; 0.1830] 0.0390 0.1975
## SIT 8 0.1009 [-0.2898; 0.4916] 0.1251 0.3536
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.26 1 0.6094
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 26; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0781 (SE = 0.0660)
## tau (square root of estimated tau^2 value): 0.2795
## I^2 (residual heterogeneity / unaccounted variability): 35.56%
## H^2 (unaccounted variability / sampling variability): 1.55
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 24) = 37.2425, p-val = 0.0414
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.2632, p-val = 0.6079
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.0065 0.1120 -0.0579 0.9538 -0.2260 0.2131
## HIIESIT 0.1101 0.2146 0.5131 0.6079 -0.3105 0.5308
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.9 12.9
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 8.4 8.4
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.9 10.9
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 14.6 14.6
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.7 6.7
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 10.0 10.0
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.8 9.8
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 17.9 17.9
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.8 8.8
##
## Number of studies combined: k = 9
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2655 [-0.5190; -0.0120] -2.05 0.0401
## Random effects model -0.2655 [-0.5190; -0.0120] -2.05 0.0401
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2195]; tau = 0 [0.0000; 0.4685];
## I^2 = 0.0% [0.0%; 46.4%]; H = 1.00 [1.00; 1.37]
##
## Test of heterogeneity:
## Q d.f. p-value
## 5.25 8 0.7302
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 -0.2589 [-0.5212; 0.0033] 0.0530 0.0000 0.0000 0.0%
## Omitting Eguchi 2012 -0.2423 [-0.4983; 0.0138] 0.0637 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (Healthy) -0.1708 [-0.4303; 0.0886] 0.1968 0.0000 0.0000 0.0%
## Omitting Honkala 2017 (T2D) -0.2565 [-0.5102; -0.0027] 0.0476 0.0000 0.0000 0.0%
## Omitting Madssen 2014 -0.2367 [-0.5013; 0.0279] 0.0795 0.0000 0.0000 0.0%
## Omitting Maillard 2016 -0.2290 [-0.4829; 0.0248] 0.0770 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 -0.2327 [-0.4909; 0.0255] 0.0773 0.0000 0.0000 0.0%
## Omitting Motiani 2017 -0.1609 [-0.4187; 0.0970] 0.2215 0.0000 0.0000 0.0%
## Omitting Ramos 2016a -0.2467 [-0.5162; 0.0229] 0.0729 0.0000 0.0000 0.0%
## Omitting Sjöros 2018 -0.2408 [-0.4973; 0.0158] 0.0659 0.0000 0.0000 0.0%
##
## Pooled estimate -0.2352 [-0.4807; 0.0104] 0.0605 0.0000 0.0000 0.0%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.2655 [-0.5190; -0.0120] Overall
## Healthy -0.5844 [-1.0638; -0.1049] Population
## Cardiac Rehabilitation -0.1689 [-0.8328; 0.4950] Population
## Metabolic Syndrome -0.1481 [-0.6279; 0.3316] Population
## T2D -0.0180 [-0.4471; 0.4112] Population
## 30 - 50 y -0.3785 [-0.7706; 0.0135] Age
## > 50 y -0.1097 [-0.4357; 0.2163] Age
## < 5 weeks -0.4228 [-0.9169; 0.0713] Training Duration
## 5 - 10 weeks -0.0768 [-0.6061; 0.4525] Training Duration
## > 10 weeks -0.1396 [-0.5073; 0.2282] Training Duration
## < 0.5 -0.2034 [-1.1868; 0.7799] Men Ratio
## > 0.5 -0.2290 [-0.4829; 0.0248] Men Ratio
## Cycling -0.2620 [-0.5570; 0.0329] Type of Exercise
## Running -0.1487 [-0.5933; 0.2958] Type of Exercise
## < 40 mmol/mol -0.3318 [-0.6759; 0.0124] Baseline Values
## > 40 mmol/mol -0.1188 [-0.4699; 0.2324] Baseline Values
## HIIT -0.1191 [-0.4211; 0.1829] Type of HIIE
## SIT -0.4228 [-0.9169; 0.0713] Type of HIIE
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 T2D
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 Healthy
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 Healthy
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 T2D
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 Cardiac Rehabilitation
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 T2D
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 Metabolic Syndrome
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 Healthy
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 Metabolic Syndrome
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 T2D
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 28.6%]; H = 1.00 [1.00; 1.18]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 3 -0.5854 [-1.0562; -0.1145] 2.07 3.5%
## Cardiac Rehabilitation 1 -0.1689 [-0.8328; 0.4950] 0.00 --
## Metabolic Syndrome 2 -0.1481 [-0.6279; 0.3316] 0.01 0.0%
## T2D 4 -0.0180 [-0.4471; 0.4112] 0.37 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 3.27 3 0.3518
## Within groups 2.45 6 0.8738
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 3 -0.5844 [-1.0638; -0.1049] 0.0063 0.0794
## Cardiac Rehabilitation 1 -0.1689 [-0.8328; 0.4950] -- --
## Metabolic Syndrome 2 -0.1481 [-0.6279; 0.3316] 0 0
## T2D 4 -0.0180 [-0.4471; 0.4112] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.18 3 0.3649
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.1007)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 6) = 2.6343, p-val = 0.8531
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 3.5150, p-val = 0.3188
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.6053 0.2396 -2.5268 0.0115 -1.0748 -0.1358 *
## .byvarCardiac Rehabilitation 0.4326 0.4148 1.0428 0.2970 -0.3805 1.2456
## .byvarMetabolic Syndrome 0.4533 0.3425 1.3237 0.1856 -0.2179 1.1246
## .byvarT2D 0.5866 0.3245 1.8077 0.0706 -0.0494 1.2227 .
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 > 50 y
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 > 50 y
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 30 - 50 y
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 30 - 50 y
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 > 50 y
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 > 50 y
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 30 - 50 y
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 30 - 50 y
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 > 50 y
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 30 - 50 y
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 38.3%]; H = 1.00 [1.00; 1.27]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## 30 - 50 y 5 -0.3825 [-0.7567; -0.0084] 4.38 8.7%
## > 50 y 5 -0.1097 [-0.4357; 0.2163] 0.18 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.16 1 0.2812
## Within groups 4.56 8 0.8033
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## 30 - 50 y 5 -0.3785 [-0.7706; 0.0135] 0.0175 0.1321
## > 50 y 5 -0.1097 [-0.4357; 0.2163] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.07 1 0.3014
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0781)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 8) = 5.6930, p-val = 0.6816
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.4564, p-val = 0.4993
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -1.0026 1.1429 -0.8772 0.3804 -3.2426 1.2374
## age 0.0145 0.0214 0.6755 0.4993 -0.0275 0.0564
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 5 - 10 weeks
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 > 10 weeks
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 < 5 weeks
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 < 5 weeks
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 > 10 weeks
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 > 10 weeks
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 5 - 10 weeks
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 < 5 weeks
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 > 10 weeks
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 < 5 weeks
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 46.3%]; H = 1.00 [1.00; 1.36]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 4 -0.4398 [-0.8628; -0.0169] 4.06 26.0%
## 5 - 10 weeks 2 -0.0768 [-0.6061; 0.4525] 0.10 0.0%
## > 10 weeks 4 -0.1396 [-0.5073; 0.2282] 0.06 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.50 2 0.4726
## Within groups 4.22 7 0.7538
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 4 -0.4228 [-0.9169; 0.0713] 0.0663 0.2575
## 5 - 10 weeks 2 -0.0768 [-0.6061; 0.4525] 0 0
## > 10 weeks 4 -0.1396 [-0.5073; 0.2282] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.09 2 0.5790
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0807)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 8) = 5.1622, p-val = 0.7401
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.9871, p-val = 0.3204
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.4325 0.2348 -1.8417 0.0655 -0.8927 0.0278 .
## duration 0.0227 0.0229 0.9935 0.3204 -0.0221 0.0676
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 > 0.5
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 > 0.5
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 > 0.5
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 > 0.5
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 > 0.5
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 < 0.5
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 > 0.5
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 > 0.5
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 > 0.5
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 > 0.5
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 50.8%]; H = 1.00 [1.00; 1.43]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 1 -0.2034 [-1.1868; 0.7799] 0.00 --
## > 0.5 9 -0.2290 [-0.4829; 0.0248] 5.72 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.00 1 0.9606
## Within groups 5.72 8 0.6786
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 1 -0.2034 [-1.1868; 0.7799] -- --
## > 0.5 9 -0.2290 [-0.4829; 0.0248] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.00 1 0.9606
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0776)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 8) = 5.5401, p-val = 0.6986
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.6093, p-val = 0.4351
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0497 0.3858 0.1288 0.8975 -0.7065 0.8059
## men_ratio -0.3705 0.4747 -0.7806 0.4351 -1.3009 0.5598
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 Cycling
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 Cycling
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 Cycling
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 Cycling
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 Running
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 Cycling
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 Cycling
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 Cycling
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 Running
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 Cycling
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 49.2%]; H = 1.00 [1.00; 1.40]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 8 -0.2620 [-0.5570; 0.0329] 5.54 0.0%
## Running 2 -0.1487 [-0.5933; 0.2958] 0.01 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.17 1 0.6773
## Within groups 5.55 8 0.6976
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 8 -0.2620 [-0.5570; 0.0329] 0 0
## Running 2 -0.1487 [-0.5933; 0.2958] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.17 1 0.6773
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0832)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 8) = 5.9552, p-val = 0.6523
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1942, p-val = 0.6595
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.2717 0.1503 -1.8079 0.0706 -0.5663 0.0229 .
## type_exerciseRunning 0.1199 0.2721 0.4406 0.6595 -0.4134 0.6532
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 > 40 mmol/mol
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 < 40 mmol/mol
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 < 40 mmol/mol
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 < 40 mmol/mol
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 > 40 mmol/mol
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 > 40 mmol/mol
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 < 40 mmol/mol
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 < 40 mmol/mol
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 > 40 mmol/mol
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 < 40 mmol/mol
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 43.7%]; H = 1.00 [1.00; 1.33]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 40 mmol/mol 6 -0.3318 [-0.6759; 0.0124] 4.84 0.0%
## > 40 mmol/mol 4 -0.1188 [-0.4699; 0.2324] 0.16 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.72 1 0.3958
## Within groups 5.00 8 0.7575
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 40 mmol/mol 6 -0.3318 [-0.6759; 0.0124] 0 0
## > 40 mmol/mol 4 -0.1188 [-0.4699; 0.2324] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.72 1 0.3958
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0780)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 8) = 5.4957, p-val = 0.7035
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.6536, p-val = 0.4188
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.9685 0.9157 -1.0577 0.2902 -2.7633 0.8262
## bsln_adjusted 0.0175 0.0216 0.8085 0.4188 -0.0249 0.0599
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 -0.0000 [-0.7044; 0.7044] 12.2 12.2 HIIT
## Eguchi 2012 -0.0554 [-0.9321; 0.8213] 7.8 7.8 HIIT
## Honkala 2017 (Healthy) -0.7456 [-1.5117; 0.0205] 10.3 10.3 SIT
## Honkala 2017 (T2D) 0.2285 [-0.7624; 1.2194] 6.1 6.1 SIT
## Madssen 2014 -0.1727 [-0.8365; 0.4911] 13.7 13.7 HIIT
## Maillard 2016 -0.2152 [-1.1980; 0.7676] 6.2 6.2 HIIT
## Matsuo 2015 -0.1827 [-0.9845; 0.6192] 9.4 9.4 HIIT
## Motiani 2017 -0.9164 [-1.7245; -0.1083] 9.2 9.2 SIT
## Ramos 2016a -0.1349 [-0.7335; 0.4638] 16.8 16.8 HIIT
## Sjöros 2018 -0.0817 [-0.9384; 0.7750] 8.2 8.2 SIT
##
## Number of studies combined: k = 10
##
## SMD 95%-CI z p-value
## Fixed effect model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
## Random effects model -0.2352 [-0.4807; 0.0104] -1.88 0.0605
##
## Quantifying heterogeneity:
## tau^2 = 0 [0.0000; 0.2142]; tau = 0 [0.0000; 0.4628];
## I^2 = 0.0% [0.0%; 44.9%]; H = 1.00 [1.00; 1.35]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 33.9%]; H = 1.00 [1.00; 1.23]
##
## Test of heterogeneity:
## Q d.f. p-value
## 6.15 9 0.7249
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 6 -0.1191 [-0.4211; 0.1829] 0.20 0.0%
## SIT 4 -0.4398 [-0.8628; -0.0169] 4.06 26.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 1.46 1 0.2265
## Within groups 4.26 8 0.8330
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 6 -0.1191 [-0.4211; 0.1829] 0 0
## SIT 4 -0.4228 [-0.9169; 0.0713] 0.0663 0.2575
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 1.06 1 0.3041
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 10; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0794)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 8) = 4.5804, p-val = 0.8013
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.5690, p-val = 0.2104
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1228 0.1541 -0.7974 0.4252 -0.4248 0.1791
## HIIESIT -0.3316 0.2647 -1.2526 0.2104 -0.8505 0.1873
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random)
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Influential analysis (Random effects model)
##
## SMD 95%-CI p-value tau^2 tau I^2
## Omitting Abdelbasset 2020 -0.0403 [-0.2407; 0.1600] 0.6932 0.0000 0.0000 0.0%
## Omitting Ciolac 2010 -0.0331 [-0.2338; 0.1675] 0.7462 0.0000 0.0000 0.0%
## Omitting Fisher 2015 -0.0262 [-0.2244; 0.1719] 0.7953 0.0000 0.0000 0.0%
## Omitting Gillen 2016 -0.0440 [-0.2412; 0.1533] 0.6624 0.0000 0.0000 0.0%
## Omitting Grieco 2013 -0.0566 [-0.2545; 0.1413] 0.5751 0.0000 0.0000 0.0%
## Omitting Hovanloo 2013 -0.0741 [-0.2701; 0.1218] 0.4585 0.0000 0.0000 0.0%
## Omitting Lunt 2014 -0.0190 [-0.2169; 0.1789] 0.8509 0.0000 0.0000 0.0%
## Omitting Lunt 2014 -0.0247 [-0.2227; 0.1733] 0.8069 0.0000 0.0000 0.0%
## Omitting Matsuo 2015 -0.0356 [-0.2342; 0.1629] 0.7252 0.0000 0.0000 0.0%
## Omitting Mitranun 2014 -0.0425 [-0.2421; 0.1571] 0.6766 0.0000 0.0000 0.0%
## Omitting Ramos 2016a -0.0035 [-0.2069; 0.2000] 0.9735 0.0000 0.0000 0.0%
## Omitting Robinson 2015 -0.0573 [-0.2597; 0.1452] 0.5794 0.0000 0.0000 0.0%
## Omitting Sandvei 2012 -0.0221 [-0.2203; 0.1762] 0.8274 0.0000 0.0000 0.0%
## Omitting Sawyer 2016 -0.0437 [-0.2408; 0.1533] 0.6635 0.0000 0.0000 0.0%
## Omitting Skleryk 2013 -0.0256 [-0.2221; 0.1709] 0.7982 0.0000 0.0000 0.0%
## Omitting Trapp 2008 -0.0846 [-0.2843; 0.1151] 0.4065 0.0000 0.0000 0.0%
## Omitting Winn 2018 -0.0015 [-0.1974; 0.1944] 0.9880 0.0000 0.0000 0.0%
##
## Pooled estimate -0.0388 [-0.2345; 0.1568] 0.6972 0.0049 0.0701 2.9%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI meta-analysis
## -0.0388 [-0.2345; 0.1568] Overall
## Healthy 0.2277 [-0.1342; 0.5896] Population
## Overweight/obese -0.3300 [-0.6995; 0.0396] Population
## Metabolic Syndrome -0.0922 [-0.4744; 0.2901] Population
## T2D 0.0161 [-0.4944; 0.5266] Population
## < 30 y 0.1619 [-0.1690; 0.4928] Age
## 30 - 50 y -0.2937 [-0.6607; 0.0733] Age
## > 50 y -0.0513 [-0.3824; 0.2799] Age
## < 5 weeks 0.0367 [-0.5651; 0.6386] Training Duration
## 5 - 10 weeks -0.0735 [-0.3979; 0.2509] Training Duration
## > 10 weeks -0.0706 [-0.3759; 0.2346] Training Duration
## < 0.5 0.0282 [-0.2511; 0.3075] Men Ratio
## > 0.5 -0.1569 [-0.4724; 0.1586] Men Ratio
## Cycling 0.1548 [-0.1024; 0.4120] Type of Exercise
## Running -0.2835 [-0.5745; 0.0076] Type of Exercise
## < 3 0.0138 [-0.2081; 0.2358] Baseline Values
## > 3 -0.1939 [-0.5823; 0.1944] Baseline Values
## HIIT -0.0952 [-0.3336; 0.1432] Type of HIIE
## SIT 0.0715 [-0.3040; 0.4470] Type of HIIE
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049; tau = 0.0701; I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for meta-analyses (random effects model):
## k SMD 95%-CI tau^2 tau Q I^2
## Overall 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Population 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Age 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Training Duration 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Men Ratio 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Type of Exercise 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Baseline Values 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
## Type of HIIE 17 -0.0388 [-0.2345; 0.1568] 0.0049 0.0701 16.48 2.9%
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## SMD 95%-CI %W(fixed) %W(random) population
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 T2D
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 Healthy
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 Overweight/obese
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 Healthy
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 Healthy
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 Healthy
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 Overweight/obese
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 Overweight/obese
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 Metabolic Syndrome
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 T2D
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 Metabolic Syndrome
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 Metabolic Syndrome
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 Healthy
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 Overweight/obese
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 Overweight/obese
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 Healthy
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 Overweight/obese
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 41.6%]; H = 1.00 [1.00; 1.31]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Healthy 6 0.2221 [-0.1128; 0.5569] 5.78 13.5%
## Overweight/obese 6 -0.3300 [-0.6995; 0.0396] 3.00 0.0%
## Metabolic Syndrome 3 -0.0922 [-0.4744; 0.2901] 1.22 0.0%
## T2D 2 0.0161 [-0.4944; 0.5266] 0.00 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 4.84 3 0.1842
## Within groups 10.01 13 0.6934
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Healthy 6 0.2277 [-0.1342; 0.5896] 0.0277 0.1666
## Overweight/obese 6 -0.3300 [-0.6995; 0.0396] 0 0
## Metabolic Syndrome 3 -0.0922 [-0.4744; 0.2901] 0 0
## T2D 2 0.0161 [-0.4944; 0.5266] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 4.58 3 0.2054
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0670)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 13) = 11.0804, p-val = 0.6041
##
## Test of Moderators (coefficients 2:4):
## QM(df = 3) = 5.3966, p-val = 0.1450
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.2341 0.1705 1.3731 0.1697 -0.1001 0.5683
## .byvarOverweight/obese -0.5825 0.2539 -2.2944 0.0218 -1.0801 -0.0849 *
## .byvarMetabolic Syndrome -0.3282 0.2590 -1.2671 0.2051 -0.8359 0.1795
## .byvarT2D -0.2176 0.3113 -0.6989 0.4846 -0.8277 0.3926
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_age
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 > 50 y
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 < 30 y
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 < 30 y
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 < 30 y
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 < 30 y
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 < 30 y
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 30 - 50 y
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 30 - 50 y
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 30 - 50 y
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 > 50 y
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 > 50 y
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 > 50 y
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 < 30 y
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 30 - 50 y
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 30 - 50 y
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 < 30 y
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 30 - 50 y
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 43.2%]; H = 1.00 [1.00; 1.33]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 30 y 7 0.1584 [-0.1520; 0.4688] 6.77 11.4%
## 30 - 50 y 6 -0.2937 [-0.6607; 0.0733] 3.33 0.0%
## > 50 y 4 -0.0513 [-0.3824; 0.2799] 1.33 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 3.41 2 0.1818
## Within groups 11.43 14 0.6517
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 30 y 7 0.1619 [-0.1690; 0.4928] 0.0227 0.1508
## 30 - 50 y 6 -0.2937 [-0.6607; 0.0733] 0 0
## > 50 y 4 -0.0513 [-0.3824; 0.2799] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 3.27 2 0.1951
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0609)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 15) = 14.5449, p-val = 0.4847
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.9320, p-val = 0.1645
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.3425 0.2914 1.1754 0.2398 -0.2286 0.9135
## age -0.0095 0.0068 -1.3900 0.1645 -0.0228 0.0039
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_duration
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 5 - 10 weeks
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 > 10 weeks
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 5 - 10 weeks
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 > 10 weeks
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 < 5 weeks
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 < 5 weeks
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 > 10 weeks
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 > 10 weeks
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 5 - 10 weeks
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 5 - 10 weeks
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 > 10 weeks
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 < 5 weeks
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 5 - 10 weeks
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 5 - 10 weeks
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 < 5 weeks
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 > 10 weeks
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 < 5 weeks
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 3.2% [0.0%; 55.1%]; H = 1.02 [1.00; 1.49]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 5 weeks 5 0.0675 [-0.3191; 0.4541] 8.98 55.5%
## 5 - 10 weeks 6 -0.0735 [-0.3979; 0.2509] 0.70 0.0%
## > 10 weeks 6 -0.0706 [-0.3759; 0.2346] 4.79 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.38 2 0.8287
## Within groups 14.47 14 0.4155
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 5 weeks 5 0.0367 [-0.5651; 0.6386] 0.2563 0.5062
## 5 - 10 weeks 6 -0.0735 [-0.3979; 0.2509] 0 0
## > 10 weeks 6 -0.0706 [-0.3759; 0.2346] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.11 2 0.9463
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0141 (SE = 0.0664)
## tau (square root of estimated tau^2 value): 0.1189
## I^2 (residual heterogeneity / unaccounted variability): 7.77%
## H^2 (unaccounted variability / sampling variability): 1.08
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 15) = 16.2639, p-val = 0.3647
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.1764, p-val = 0.6745
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0430 0.2204 0.1950 0.8454 -0.3890 0.4750
## duration -0.0089 0.0213 -0.4200 0.6745 -0.0506 0.0328
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_men_ratio
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 > 0.5
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 < 0.5
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 > 0.5
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 > 0.5
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 < 0.5
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 < 0.5
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 < 0.5
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 < 0.5
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 > 0.5
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 < 0.5
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 > 0.5
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 < 0.5
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 < 0.5
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 < 0.5
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 > 0.5
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 < 0.5
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 < 0.5
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 48.8%]; H = 1.00 [1.00; 1.40]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 0.5 11 0.0338 [-0.2096; 0.2772] 12.92 22.6%
## > 0.5 6 -0.1569 [-0.4724; 0.1586] 1.04 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.88 1 0.3482
## Within groups 13.96 15 0.5283
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 0.5 11 0.0282 [-0.2511; 0.3075] 0.0500 0.2237
## > 0.5 6 -0.1569 [-0.4724; 0.1586] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.74 1 0.3893
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0015 (SE = 0.0612)
## tau (square root of estimated tau^2 value): 0.0386
## I^2 (residual heterogeneity / unaccounted variability): 0.89%
## H^2 (unaccounted variability / sampling variability): 1.01
## R^2 (amount of heterogeneity accounted for): 69.77%
##
## Test for Residual Heterogeneity:
## QE(df = 15) = 15.1344, p-val = 0.4418
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 1.3259, p-val = 0.2495
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1373 0.1820 0.7543 0.4507 -0.2195 0.4941
## men_ratio -0.3591 0.3119 -1.1515 0.2495 -0.9703 0.2521
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) type_exercise
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 Cycling
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 Running
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 Cycling
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 Cycling
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 Cycling
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 Cycling
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 Running
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 Running
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 Cycling
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 Running
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 Running
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 Cycling
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 Running
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 Cycling
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 Cycling
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 Cycling
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 Running
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 28.1%]; H = 1.00 [1.00; 1.18]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## Cycling 10 0.1548 [-0.1024; 0.4120] 6.55 0.0%
## Running 7 -0.2835 [-0.5745; 0.0076] 3.40 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 4.89 1 0.0270
## Within groups 9.95 15 0.8227
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## Cycling 10 0.1548 [-0.1024; 0.4120] 0 0
## Running 7 -0.2835 [-0.5745; 0.0076] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 4.89 1 0.0270
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0608)
## tau (square root of estimated tau^2 value): 0
## I^2 (residual heterogeneity / unaccounted variability): 0.00%
## H^2 (unaccounted variability / sampling variability): 1.00
## R^2 (amount of heterogeneity accounted for): 100.00%
##
## Test for Residual Heterogeneity:
## QE(df = 15) = 11.1226, p-val = 0.7439
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 5.3543, p-val = 0.0207
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.1620 0.1310 1.2361 0.2164 -0.0949 0.4188
## type_exerciseRunning -0.4579 0.1979 -2.3139 0.0207 -0.8458 -0.0701 *
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) category_bsln
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 > 3
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 < 3
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 < 3
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 < 3
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 < 3
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 < 3
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 < 3
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 < 3
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 > 3
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 < 3
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 < 3
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 < 3
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 < 3
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 > 3
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 > 3
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 < 3
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 > 3
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 48.9%]; H = 1.00 [1.00; 1.40]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## < 3 12 0.0138 [-0.2081; 0.2358] 10.31 0.0%
## > 3 5 -0.1939 [-0.5823; 0.1944] 3.71 0.0%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.83 1 0.3626
## Within groups 14.01 15 0.5245
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## < 3 12 0.0138 [-0.2081; 0.2358] 0 0
## > 3 5 -0.1939 [-0.5823; 0.1944] 0 0
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.83 1 0.3626
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0130 (SE = 0.0650)
## tau (square root of estimated tau^2 value): 0.1140
## I^2 (residual heterogeneity / unaccounted variability): 7.31%
## H^2 (unaccounted variability / sampling variability): 1.08
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 15) = 16.1829, p-val = 0.3700
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.3098, p-val = 0.5778
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt 0.0776 0.2329 0.3329 0.7392 -0.3790 0.5341
## bsln_adjusted -0.0464 0.0834 -0.5566 0.5778 -0.2099 0.1170
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## SMD 95%-CI %W(fixed) %W(random) HIIE
## Abdelbasset 2020 0.0000 [-0.7044; 0.7044] 7.5 7.4 HIIT
## Ciolac 2010 -0.0896 [-0.7829; 0.6037] 7.7 7.7 HIIT
## Fisher 2015 -0.2395 [-1.0668; 0.5878] 5.4 5.4 SIT
## Gillen 2016 0.1059 [-0.7953; 1.0071] 4.6 4.6 SIT
## Grieco 2013 0.3271 [-0.5176; 1.1719] 5.2 5.2 HIIT
## Hovanloo 2013 1.1129 [ 0.0598; 2.1660] 3.3 3.4 SIT
## Lunt 2014 -0.3860 [-1.2308; 0.4588] 5.2 5.2 HIIT
## Lunt 2014 -0.2755 [-1.1167; 0.5656] 5.2 5.3 SIT
## Matsuo 2015 -0.0673 [-0.8677; 0.7331] 5.8 5.8 HIIT
## Mitranun 2014 0.0348 [-0.7060; 0.7757] 6.7 6.7 HIIT
## Ramos 2016a -0.3407 [-0.9430; 0.2615] 10.2 10.0 HIIT
## Robinson 2015 0.1583 [-0.4706; 0.7872] 9.4 9.2 HIIT
## Sandvei 2012 -0.3121 [-1.1352; 0.5110] 5.5 5.5 SIT
## Sawyer 2016 0.1095 [-0.8151; 1.0342] 4.3 4.4 HIIT
## Skleryk 2013 -0.3525 [-1.3400; 0.6351] 3.8 3.8 SIT
## Trapp 2008 0.6178 [-0.1148; 1.3503] 6.9 6.9 SIT
## Winn 2018 -1.1850 [-2.2475; -0.1225] 3.3 3.3 HIIT
##
## Number of studies combined: k = 17
##
## SMD 95%-CI z p-value
## Fixed effect model -0.0388 [-0.2313; 0.1537] -0.40 0.6927
## Random effects model -0.0388 [-0.2345; 0.1568] -0.39 0.6972
##
## Quantifying heterogeneity:
## tau^2 = 0.0049 [0.0000; 0.2894]; tau = 0.0701 [0.0000; 0.5379];
## I^2 = 2.9% [0.0%; 52.5%]; H = 1.01 [1.00; 1.45]
##
## Quantifying residual heterogeneity:
## I^2 = 0.0% [0.0%; 49.6%]; H = 1.00 [1.00; 1.41]
##
## Test of heterogeneity:
## Q d.f. p-value
## 16.48 16 0.4202
##
## Results for subgroups (fixed effect model):
## k SMD 95%-CI Q I^2
## HIIT 10 -0.0952 [-0.3336; 0.1432] 6.38 0.0%
## SIT 7 0.0717 [-0.2556; 0.3990] 7.81 23.2%
##
## Test for subgroup differences (fixed effect model):
## Q d.f. p-value
## Between groups 0.65 1 0.4191
## Within groups 14.19 15 0.5112
##
## Results for subgroups (random effects model):
## k SMD 95%-CI tau^2 tau
## HIIT 10 -0.0952 [-0.3336; 0.1432] 0 0
## SIT 7 0.0715 [-0.3040; 0.4470] 0.0594 0.2437
##
## Test for subgroup differences (random effects model):
## Q d.f. p-value
## Between groups 0.54 1 0.4625
##
## Details on meta-analytical method:
## - Inverse variance method
## - DerSimonian-Laird estimator for tau^2
## - Jackson method for confidence interval of tau^2 and tau
## - Cohen's d (standardised mean difference)
##
## Mixed-Effects Model (k = 17; tau^2 estimator: DL)
##
## tau^2 (estimated amount of residual heterogeneity): 0.0081 (SE = 0.0633)
## tau (square root of estimated tau^2 value): 0.0899
## I^2 (residual heterogeneity / unaccounted variability): 4.67%
## H^2 (unaccounted variability / sampling variability): 1.05
## R^2 (amount of heterogeneity accounted for): 0.00%
##
## Test for Residual Heterogeneity:
## QE(df = 15) = 15.7346, p-val = 0.3999
##
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.7131, p-val = 0.3984
##
## Model Results:
##
## estimate se zval pval ci.lb ci.ub
## intrcpt -0.1014 0.1251 -0.8107 0.4176 -0.3467 0.1438
## HIIESIT 0.1784 0.2113 0.8445 0.3984 -0.2357 0.5926
##
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1