A meta-analysis of the association between male dimorphism and fitness outcomes in humans
Figures

Forest plot of the association between body masculinity and the mating domain.
Effect sizes are shown as Z-transformed r, with 95% confidence intervals in brackets. The width of the diamond corresponds to the confidence interval for the overall effect.

Forest plot of the association between voice pitch and the mating domain.
Effect sizes are shown as Z-transformed r, with 95% confidence intervals in brackets. The width of the diamond corresponds to the confidence interval for the overall effect.

Forest plot of the association between testosterone levels and the mating domain.
Effect sizes are shown as Z-transformed r, with 95% confidence intervals in brackets. The width of the diamond corresponds to the confidence interval for the overall effect.

Forest plot of the association between height and the mating domain.
Effect sizes are shown as Z-transformed r, with 95% confidence intervals in brackets. The width of the diamond corresponds to the confidence interval for the overall effect.
Tables
All studies included in the meta-analysis.
Authors | Year | Predictor | Outcome | Sample | Sample location | Low or high fert. | N |
---|---|---|---|---|---|---|---|
Alvergne et al., 2009 | 2009 | T | REP | Rural villagers | Senegal | High | 53 |
Apicella, 2014 | 2014 | Body masc | MAT, REP, OM | Hadza | Tanzania | High | 51 |
Apicella et al., 2007 | 2007 | Body masc, voice pitch, height | REP, OM | Hadza | Tanzania | High | 44-52 |
Arnocky et al., 2018 | 2018 | Facial masc | MAT | Students | Canada | Low | 135 |
Aronoff, 2017 | 2017 | T | MAT | Students | US | Low | 99 |
Atkinson, 2012 | 2012 | Body masc | MAT | Students | US | Low | 66 |
Atkinson et al., 2012 | 2012 | Body masc, voice pitch, height | REP | Himba (Ovahimba) | Namibia | High | 36 |
Bogaert and Fisher, 1995 | 1995 | T | MAT | Students | Canada | Low | 195-196 |
Booth et al., 1999 | 1999 | T | MAT | Army veterans and non-veterans | US | Low | 4393 |
Boothroyd et al., 2008 | 2008 | Facial masc | MAT | Students | UK | Low | 18-19 |
Boothroyd et al., 2011 | 2011 | Facial masc | MAT | Students | UK | Low | 36 |
Boothroyd et al., 2017 | 2017 | Facial masc | REP, OM | Agta | Philippines | High | 65 |
Facial masc | MAT, REP, OM | Maya | Belize | High | 23-35 | ||
Charles and Alexander, 2011 | 2011 | 2D:4D, T | MAT | Students | US | Low | 25-42 |
Chaudhary et al., 2015 | 2015 | Body masc, height | MAT, REP, OM | Mbendjele BaYaka | Democratic Republic of the Congo | High | 55-73 |
Edelstein et al., 2011 | 2011 | T | MAT | Students | US | Low | 134 |
Falcon, 2016 | 2016 | 2D:4D | MAT | Students | US | Low | 137 |
Farrelly et al., 2015 | 2015 | T | MAT | Students | UK | Low | 75-78 |
Frederick, 2010 | 2010 | Body masc, 2D:4D, height | MAT | Students | US | Low | 61 |
Frederick and Haselton, 2007 | 2007 | Body masc | MAT | Students | US | Low | 56-121 |
Frederick and Jenkins, 2015 | 2015 | Height | MAT | Online | Worldwide | Low | 28759-31418 |
Gallup et al., 2007 | 2007 | Body masc, 2D:4D | MAT | Students | US | Low | 71-75 |
Genovese, 2008 | 2008 | Body masc | REP | Former teenage delinquents | US | High | 181 |
Gettler et al., 2019 | 2019 | T | MAT | Cebu Longitudinal Health and Nutrition Survey | Philippines | High | 288 |
Gildner, 2018 | 2018 | Body masc, 2D:4D, height | REP | Shuar Health and Life History Project | Ecuador | High | 48 |
Gómez-Valdés et al., 2013 | 2013 | Facial masc | REP | Hallstatt skulls | Austria | High | 179 |
Hartl et al., 1982 | 1982 | Body masc, height | MAT, REP | Former teenage delinquents | US | High | 180-185 |
Hill et al., 2013 | 2013 | Facial masc, body masc, | MAT | Students | US | Low | 63 |
voice pitch, height | |||||||
Hoppler et al., 2018 | 2018 | T | REP | Men’s health 40+ study | Switzerland | Low | 268 |
Hughes and Gallup, 2003 | 2003 | Body masc | MAT | Students | US | Low | 50-59 |
Honekopp et al., 2006 | 2006 | 2D:4D, height | MAT | Students and non-students | Germany | Low | 79-99 |
Honekopp et al., 2007 | 2007 | Facial masc, body masc, height, T | MAT | Students and non-students | Germany | Low | 77 |
Kirchengast, 2000 | 2000 | Height | REP, OM | !Kung San | Namibia | High | 103 |
Kirchengast and Winkler, 1995 | 1995 | Height | REP, OM | Urban and rural Kavango people | Namibia | High | 59-78 |
Klimas et al., 2019 | 2019 | T | MAT | Men’s health 40+ study | Switzerland | Low | 159 |
Klimek et al., 2014 | 2014 | 2D:4D, height | REP | Mogielica Human Ecology Study Site | Poland | High | 238 |
Kordsmeyer et al., 2018 | 2018 | Body masc, voice pitch, height, T | MAT | Students and non-students | Germany | Low | 103-164 |
Kordsmeyer and Penke, 2017 | 2017 | 2D:4D, height | MAT | Students and non-students | Germany | Low | 141 |
Krzyżanowska et al., 2015 | 2015 | Height | REP | National Child Development Study | UK | Low | 6535 |
Kurzban and Weeden, 2005 | 2005 | Height | MAT, REP | Speed daters | US | Low | 1503-1501 |
Lassek and Gaulin, 2009 | 2009 | Body masc, height | MAT | NHANES III | US | Low | 4167-5159 |
Little et al., 1989 | 1989 | Height | REP, OM | Rural; growth stunted | Mexico | High | 103 |
Loehr and O’Hara, 2013 | 2013 | Facial masc | REP | WWII soldiers | Finland | High | 795 |
Longman et al., 2018 | 2018 | T | MAT | Students | UK | Low | 38 |
Luevano et al., 2018 | 2018 | Facial masc, height | MAT | Students | US | Low | 35-66 |
Lukaszewski et al., 2014 | 2014 | Body masc | MAT | Students | US | Low | 48-174 |
Maestripieri et al., 2014 | 2014 | T | MAT | Students | US | Low | 41-61 |
Manning and Fink, 2008 | 2008 | 2D:4D | MAT, REP | Online | Worldwide | Low | 26872-83681 |
Manning et al., 2003 | 2003 | 2D:4D | REP | Community | England | Low | 189 |
2D:4D | REP | Sugali and Yanadi tribal groups | India | High | 80 | ||
2D:4D | REP | Zulus from townships near Durban | South Africa | High | 66 | ||
Marczak et al., 2018 | 2018 | 2D:4D | REP | Yali | Indonesia | High | 47 |
McIntyre et al., 2006 | 2006 | T | MAT | Students | US | Low | 68-81 |
Međedović and Bulut, 2019 | 2019 | Height | MAT | Students | Serbia | Low | 39 |
Mosing et al., 2015 | 2015 | Height | MAT, REP | Study of Twin Adults: Genes and Environment | Sweden | Low | 2310-2549 |
Muller and Mazur, 1997 | 1997 | Facial masc | REP | West Point class of 1950 | US | High | 337 |
Nagelkerke et al., 2006 | 2006 | Height | MAT | NHANES 99–00 | US | Low | 798-809 |
Nettle, 2002 | 2002 | Height | REP | National Child Development Study | UK | Low | 4474 |
Pawlowski et al., 2008 | 2008 | Height | REP | Rural | Poland | High | 46 |
Pawlowski et al., 2000 | 2000 | Height | REP | Urban and rural | Poland | High | 3201 |
Peters et al., 2008 | 2008 | Facial masc, body masc, T | MAT | Students | Australia | Low | 100-113 |
Pollet et al., 2011 | 2011 | T | MAT | National Social Life, Health, and Aging Project | US | Low | 749 |
Polo et al., 2019 | 2019 | Facial masc, body masc, height | MAT | Students and non-students | Chile | Low | 198-206 |
Price et al., 2013 | 2013 | Body masc, height | MAT | Mainly students | UK | Low | 55 |
Prokop and Fedor, 2011 | 2011 | Height | REP | Friends and family of students | Slovakia | Low | 499 |
Prokop and Fedor, 2013 | 2013 | Height | MAT | Students | Slovakia | Low | 105-150 |
Puts et al., 2006 | 2006 | Voice pitch | MAT | Students | US | Low | 103 |
Puts et al., 2015 | 2015 | T | MAT | Students | US | Low | 59-61 |
Putz et al., 2004 | 2004 | 2D:4D | MAT | Students | US | Low | 207-219 |
Rahman et al., 2005 | 2005 | 2D:4D, height | MAT | Students and non-students | UK | Low | 78-150 |
Rhodes et al., 2005 | 2005 | Facial masc, body masc, height | MAT | Mainly students | Australia | Low | 142-166 |
Rosenfield et al., 2020 | 2020 | Body masc, voice pitch, height | MAT, REP, OM | Tsimané | Bolivia | High | 55-62 |
Schwarz et al., 2011 | 2011 | 2D:4D | MAT | Students | Germany | Low | 52-89 |
Scott and Bajema, 1982 | 1982 | Height | REP | Third Harvard Growth Study | US | High | 606 |
Shoup and Gallup, 2008 | 2008 | Body masc, 2D:4D | MAT | Students | US | Low | 28-38 |
Sim and Chun, 2016 | 2016 | Body masc, 2D:4D | MAT | Students | US | Low | 90 |
Simmons and Roney, 2011 | 2011 | Body masc, T | MAT | Students | US | Low | 138 |
Smith et al., 2017 | 2017 | Body masc | REP | Hadza | Tanzania | High | 51 |
Sneade and Furnham, 2016 | 2016 | Body masc | MAT | Students | UK | Low | 145 |
Sorokowski et al., 2013 | 2013 | Height | REP, OM | Yali | Indonesia | High | 49-52 |
Steiner, 2011 | 2011 | 2D:4D, T | REP | Students and non-students | US | Low | 30 |
Stern et al., 2020 | 2020 | T | MAT | Students | UK | Low | 61 |
Strong, 2014 | 2014 | Body masc | MAT | Students | US | Low | 31 |
Strong and Luevano, 2014 | 2014 | Body masc, 2D:4D, height | MAT | Students | US | Low | 51-66 |
Subramanian et al., 2009 | 2009 | Height | OM | 2005-2006 National Family Health Survey | India | Low | 21120 |
Suire et al., 2018 | 2018 | Voice pitch | MAT | Mainly students | France | Low | 57-58 |
Tao and Yin, 2016 | 2016 | Height | REP | The Panel Study of Family Dynamics | Taiwan | Low | 1409 |
van Anders et al., 2007 | 2007 | T | MAT | Non-students | US | Low | 31 |
Van Dongen and Sprengers, 2012 | 2012 | Facial masc, body masc, 2D:4D | MAT | Not specified | Not specified | Low | 52 |
Varella et al., 2014 | 2014 | Body masc, 2D:4D, height | MAT | Students | Brazil, Czech Republic | Low | 69-80 |
von Rueden et al., 2011 | 2011 | Body masc, height | REP, OM | Tsimané | Bolivia | High | 162-197 |
Voracek et al., 2010 | 2010 | 2D:4D, height | REP | Firefighters | Austria | Low | 134 |
Walther et al., 2016 | 2016 | Body masc | REP | Men’s health 40+ study | Switzerland | Low | 271 |
Walther et al., 2017a | 2017a | Body masc | MAT | Men’s health 40+ study | Switzerland | Low | 226 |
Walther et al., 2017b | 2017b | Height | REP | Men’s health 40+ study | Switzerland | Low | 271 |
Walther et al., 2017c | 2017c | Height | MAT | Men’s health 40+ study | Switzerland | Low | 226 |
Waynforth, 1998 | 1998 | 2D:4D, height | MAT, REP, OM | Villagers | Belize | High | 35-56 |
Weeden and Sabini, 2007 | 2007 | Body masc, 2D:4D, height | MAT | Students | US | Low | 188-212 |
Winkler and Kirchengast, 1994 | 1994 | Height | REP, OM | !Kung San | Namibia | High | 31-114 |
Masculine traits predicting mating: main analyses and subgroup analyses of mating attitudes vs mating behaviors and low vs high fertility samples.
Pearson’s r (95% CI); p value for meta-analytic effect, q-value (correcting for multiple comparisons); number of observations (k), samples (s), and unique participants (n); test for heterogeneity (Q), p value for heterogeneity. Statistically significant meta-analytic associations are bolded if still significant after controlling for multiple comparisons.
Mating | ||||||
---|---|---|---|---|---|---|
Outcome: Sample | Facial masculinity | Body masculinity | 2D:4D | Voice pitch | Height | T levels |
Mating domain: All samples | r = 0.080 (-0.003, 0.164), p = 0.060, q = 0.117 | r = 0.133 (0.091, 0.176), p < 0.001, q = 0.001 | r = 0.034 (0.000, 0.069), p = 0.049, q = 0.102 | r = 0.132 (0.061, 0.204), p < 0.001, q = 0.002 | r = 0.057 (0.027, 0.087), p < 0.001, q = 0.002 | r = 0.093 (0.066, 0.121), p < 0.001, q = 0.001 |
k = 30, s = 11, n = 948 | k = 121, s = 32, n = 7939 | k = 84, s = 23, n = 66,807 | k = 8, s = 5, n = 443 | k = 62, s = 25, n = 43,686 | k = 66, s = 21, n = 7083 | |
Q(df = 29) = 54.834, p = 0.003 | Q(df = 120) = 297.472, p < 0.001 | Q(df = 83) = 101.994, p = 0.077 | Q(df = 7) = 2.334, p = 0.939 | Q(df = 61) = 263.247, p < 0.001 | Q(df = 65) = 66.090, p = 0.439 | |
Mating attitudes: All samples | r = .095 (-0.072, 0.263), p = 0.263, q = 0.304 | r = .078 (0.002, 0.155), p = 0.045, q = 0.098 | r = 0.035 (-0.061, 0.132), p = 0.474, q = 0.385 | s = 0 | r = 0 .028 (-0.013, 0.068), p = 0.179, q = 0.253 | r = 0.099 (0.026, 0.173), p = 0.008, q = 0.032 |
k = 5, s = 4, n = 407 | k = 20, s = 9, n = 922 | k = 19, s = 7, n = 504 | k = 9, s = 6, n = 4232 | k = 21, s = 11, n = 1039 | ||
Q(df = 4) = 8.684, p = 0.070 | Q(df = 19) = 17.606, p = 0.549 | Q(df = 18) = 24.141, p = 0.151 | Q(df = 8) = 5.137, p = 0.743 | Q(df = 20) = 25.379, p = 0.187 | ||
Mating behaviors: All samples | r = .025 (-0.059, 0.109), p = 0.554, q = 0.424 | r = .142 (0.099, 0.187), p < 0.001, q = 0.001 | r = 0.038 (-0.002, 0.078), p = 0.061, q = 0.117 | r = 0.124 (0.043, 0.206), p = 0.003, q = 0.016 | r = 0.054 (0.021, 0.087), p = 0.001, q = 0.008 | r = 0.084 (0.058, 0.110), p < 0.001, q = 0.001 |
k = 22, s = 8, n = 755 | k = 91, s = 31, n = 7738 | k = 51, s = 19, n = 1607 | k = 7, s = 5, n = 443 | k = 48, s = 24, n = 42,179 | k = 32, s = 17, n = 6765 | |
Q(df = 21) = 37.044, p = 0.017 | Q(df = 90) = 267.876, p < 0.001 | Q(df = 50) = 64.049, p = 0.087 | Q(df = 6) = 2.162, p = 0.904 | Q(df = 47) = 247.032, p < 0.001 | Q(df = 31) = 28.558, p = 0.592 | |
Mating domain: Low fert. samples | r = 0.089 (-0.001, 0.179), p = 0.053, q = 0.109 | r = 0.135 (0.091, 0.180), p < 0.001, q = 0.001 | r = 0.038 (0.002, 0.073), p = 0.037, q = 0.086 | r = 0.129 (0.055, 0.204), p < 0.001, q = 0.005 | r = 0.055 (0.024, 0.086), p < 0.001, q = 0.004 | r = 0.099 (0.069, 0.129), p < 0.001, q = 0.001 |
k = 28, s = 10, n = 913 | k = 117, s = 28, n = 7572 | k = 82, s = 22, n = 66,751 | k = 7, s = 4, n = 388 | k = 58, s = 21, n = 43,310 | k = 58, s = 20, n = 6795 | |
Q(df = 27) = 54.287, p = 0.001 | Q(df = 116) = 289.080, p < 0.001 | Q(df = 81) = 101.369, p = 0.063 | Q(df = 6) = 2.234, p = 0.897 | Q(df = 57) = 259.576, p < 0.001 | Q(df = 57) = 61.443, p = 0.320 | |
Mating attitudes: Low fert. samples | r = 0.095 (-0.072, 0.262), p = 0.263, q = 0.304 | r = 0.078 (0.002, 0.155), p = 0.045, q = 0.098 | r = 0.035 (-0.061, 0.132), p = 0.474, q = 0.385 | s = 0 | r = 0.028 (-0.013, 0.068), p = 0.179, q = 0.253 | r = 0.108 (0.021, 0.195), p = 0.015, q = 0.047 |
k = 5, s = 4, n = 407 | k = 20, s = 9, n = 922 | k = 19, s = 7, n = 504 | k = 9, s = 6, n = 4,232 | k = 17, s = 10, n = 751 | ||
Q(df = 4) = 8.684, p = 0.070 | Q(df = 19) = 17.606, p = 0.549 | Q(df = 18) = 24.141, p = .151 | Q(df = 8) = 5.137, p = 0.743 | Q(df = 16) = 20.017, p = 0.220 | ||
Mating behaviors: Low fert. samples | r = 0.028 (-0.063, 0.119), p = 0.543, q = 0.420 | r = 0.145 (0.100, 0.193), p< 0.001, q = 0.001 | r = 0.042 (0.001, 0.083), p = 0.045, q = 0.098 | r = .119 (0.034, 0.205), p = 0.006, q = 0.025 | r = .051 (0.017, 0.086), p = 0.004, q = 0.019 | r = .088 (0.058, 0.119), p < 0.001, q = 0.001 |
k = 20, s = 7, n = 720 | k = 87, s = 27, n = 7371 | k = 49, s = 19, n = 1551 | k = 6, s = 4, n = 388 | k = 44, s = 20, n = 41,803 | k = 30, s = 16, n = 6477 | |
Q(df = 19) = 36.610, p = 0.009 | Q(df = 86) = 259.448, p < 0.001 | Q(df = 48) = 62.941, p = 0.073 | Q(df = 5) = 2.017, p = 0.847 | Q(df = 43) = 243.392, p < 0.001 | Q(df = 29) = 27.793, p = 0.529 | |
Mating domain: High fert. samples | s = 1 | r = 0.105 (-0.069, 0.280), p = 0.235, q = 0.285 | s = 1 | s = 1 | r = 0.089 (-0.016, 0.193), p = 0.096, q = 0.157 | s = 1 |
k = 4, s = 4, n = 367 | k = 4, s = 4, n = 376 | |||||
Q(df = 3) = 7.282, p = 0.063 | Q(df = 3) = 3.388, p = 0.336 | |||||
Mating attitudes: High fert. samples | s = 0 | s = 0 | s = 0 | s = 0 | s = 0 | s = 1 |
Mating behaviors: High fert. samples | s = 1 | r = 0.105 (-0.069, 0.280), p = 0.235, q = 0.285 | s = 1 | s = 1 | r = 0.089 (-0.016, 0.193), p = 0.096, q = 0.157 | s = 1 |
k = 4, s = 4, n = 367 | k = 4, s = 4, n = 376 | |||||
Q(df = 3) = 7.282, p = 0.063 | Q(df = 3) = 3.388, p = 0.336 |
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Note. Fert. = fertility; k = number of observations; n = number of unique participants; Q = Cochran’s Q test of heterogeneity; q = q-value; s = number of samples; T = testosterone.
Masculine traits predicting reproduction: main analyses and subgroup analyses of mating attitudes vs mating behaviors and low vs high fertility samples.
Pearson’s r (95% CI); p value for meta-analytic effect, q-value (correcting for multiple comparisons); number of observations (k), samples (s), and unique participants (n); test for heterogeneity (Q), p value for heterogeneity. Statistically significant meta-analytic associations are bolded if still significant after controlling for multiple comparisons.
Reproduction | ||||||
---|---|---|---|---|---|---|
Outcome: Sample | Facial masculinity | Body masculinity | 2D:4D | Voice pitch | Height | T levels |
Reproductive domain: All samples | r = 0.099 (-0.012, 0.211), p = 0.081, q = 0.140 | r = 0.143 (0.076, 0.212), p < 0.001, q = 0.001 | r = 0.074 (-0.006, 0.154), p = 0.070, q = 0.131 | r = 0.136 (-0.053, 0.328), p = 0.158, q = 0.228 | r = 0.006 (-0.049, 0.062), p = 0.819, q = 0.491 | r = 0.039 (-0.067, 0.145), p = 0.474, q = 0.385 |
k = 5, s = 5, n = 1411 | k = 14, s = 8, n = 897 | k = 19, s = 10, n = 84,558 | k = 5, s = 3, n = 143 | k = 35, s = 25, n = 22,326 | k = 3, s = 3, n = 351 | |
Q(df = 4) = 8.799, p = 0.066 | Q(df = 13) = 16.356, p = 0.230 | Q(df = 18) = 31.704, p = 0.024 | Q(df = 4) = 5.378, p = 0.251 | Q(df = 34) = 433.359, p < 0.001 | Q(df = 2) = 0.387, p = 0.824 | |
Fertility: All samples | r = 0.003 (-0.253, 0.260), p = 0.980, q = 0.543 | r = 0.130 (0.060, 0.201), p < 0.001, q = 0.002 | r = 0.032 (-0.065, 0.130), p = 0.514, q = 0.406 | s = 2 | r = 0.011 (-0.039, 0.062), p = 0.660, q = 0.451 | s = 2 |
k = 3, s = 3, n = 437 | k = 8, s = 6, n = 813 | k = 13, s = 5, n = 84,128 | k = 26, s = 23, n = 22,242 | |||
Q(df = 2) = 5.416, p = 0.067 | Q(df = 7) = 4.840, p = 0.679 | Q(df = 12) = 17.757, p = 0.123 | Q(df = 25) = 400.038, p < 0.001 | |||
RS: All samples | s = 2 | r = 0.192 (-0.052, 0.441), p = 0.122, q = 0.189 | r = 0.174 (0.085, 0.267), p < 0.001, q = 0.002 | s = 2 | r = −0.044 (-0.201, 0.113), p = 0.584, q = 0.430 | s = 1 |
k = 6, s = 4, n = 205 | k = 6, s = 5, n = 430 | k = 9, s = 9, n = 603 | ||||
Q(df = 5) = 11.344, p = 0.045 | Q(df = 5) = 0.976, p = 0.965 | Q(df = 8) = 33.311, p < 0.001 | ||||
Reproductive domain: Low fert. samples | s = 0 | s = 1 | r = 0.083 (-0.023, 0.190), p = 0.126, q = 0.191 | s = 0 | r = −0.037 (-0.112, 0.038), pp = 0.337, q = .347 | s = 2 |
k = 8, s = 4, n = 84,034 | k = 8, s = 8, n = 17,135 | |||||
Q(df = 7) = 13.988, p = 0.051 | Q(df = 7) = 244.970, p < 0.001 | |||||
Fertility: Low fert. samples | s = 0 | s = 1 | r = 0.052 (-0.065, 0.169), p = 0.386, q = 0.369 | s = 0 | r = −0.037 (-0.112, 0.038), p = 0.337, q = 0.347 | s = 2 |
k = 7, s = 3, n = 83,845 | k = 8, s = 8, n = 17,135 | |||||
Q(df = 6) = 8.335, p = 0.215 | Q(df = 7) = 244.970, p < 0.001 | |||||
RS: Low fert. samples | s = 0 | s = 0 | s = 1 | s = 0 | s = 0 | s = 0 |
Reproductive domain: High fert. samples | r = 0.099 (-0.012, 0.211), p = 0.081, q = 0.140 | r = 0.163 (0.104, 0.225), p < 0.001, q = 0.001 | r = 0.083 (-0.039, 0.205), p = 0.184, q = 0.257 | r = 0.136 (-0.053, 0.327), p = 0.158, q = 0.228 | r = 0.034 (-0.041, 0.109), p = 0.377, q = 0.367 | s = 1 |
k = 5, s = 5, n = 1411 | k = 13, s = 7, n = 626 | k = 11, s = 6, n = 524 | k = 5, s = 3, n = 143 | k = 27, s = 17, n = 5191 | ||
Q(df = 4) = 8.799, p = 0.066 | Q(df = 12) = 12.347, p = 0.418 | Q(df = 10) = 12.595, p = 0.247 | Q(df = 4) = 5.378, p = 0.251 | Q(df = 26) = 70.216, p < 0.001 | ||
Fertility: High fert. samples | r = 0.003 (-0.253, 0.260), p = 0.980, q = 0.543 | r = 0.165 (0.095, 0.237), p < 0.001, q = 0.001 | s = 2 | s = 2 | r = 0.059 (0.007, 0.111), p = 0.025, q = 0.068 | s = 0 |
k = 3, s = 3, n = 437 | k = 7, s = 5, n = 542 | k = 18, s = 15, n = 5,107 | ||||
Q(df = 2) = 5.416, p = 0.067 | Q(df = 6) = 0.988, p = 0.986 | Q(df = 17) = 26.458, p = 0.067 | ||||
RS: High fert. samples | s = 2 | r = 0.192 (-0.052, 0.441), p = 0.122, q = 0.189 | r = 0.170 (0.053, 0.291), p = 0.005, q = 0.022 | s = 2 | r = -0.044 (-0.201, 0.113), p = 0.584, q = 0.430 | s = 1 |
k = 6, s = 4, n = 205 | k = 5, s = 4, n = 241 | k = 9, s = 9, n = 603 | ||||
Q(df = 5) = 11.344, p = 0.045 | Q(df = 4) = 0.965, p = 0.915 | Q(df = 8) = 33.311, p < 0.001 |
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Note. fert. = fertility; k = number of observations; n = number of unique participants; Q = Cochran’s Q test of heterogeneity; q = q-value; RS = reproductive success; s = number of samples; T = testosterone.
Overview of moderation analyses for the mating vs reproductive domains.
Significant associations are indicated by+ and – signs, showing the direction of the moderator relative to the reference category (stated first in the moderator column); crosses indicate no significant moderation; and ‘na’ indicates that power was too low to run that specific analysis. Only associations that remained significant after controlling for multiple comparisons are indicated here. Note that this table only shows general moderators shared by all masculine traits; for trait-specific moderation analyses, see Supplementary file 4. Likewise, for moderation analyses of the two mating domain measures attitudes and behaviors, and the two reproductive domain measures fertility and reproductive success, we also refer to Supplementary file 4.
Moderator | Facial masc. | Body masc. | 2D:4D | Voice pitch | Height | T levels | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
MAT | REP | MAT | REP | MAT | REP | MAT | REP | MAT | REP | MAT | REP | |
Mating vs reproductive domain | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ | ||||||
Mating attitudes vs behaviors | ✗ | na | ✗ | na | ✗ | na | na | na | ✗ | na | ✗ | na |
Fertility vs reproductive success | na | na | na | ✗ | na | ✗ | na | na | na | ✗ | na | na |
Low vs high fertility sample | na | na | ✗ | na | na | ✗ | na | na | ✗ | ✗ | na | na |
Low fertility: student vs non-student sample | na | na | ✗ | na | ✗ | na | na | na | ✗ | na | ✗ | na |
High fertility: traditional vs industrialized sample | na | na | na | na | na | ✗ | na | na | na | ✗ | na | na |
Predominantly white vs mixed/other/unknown ethnicity sample | ✗ | na | ✗ | na | – | ✗ | na | na | ✗ | ✗ | ✗ | na |
Monogamous vs non-monogamous marriage system | na | na | ✗ | na | na | ✗ | na | na | na | ✗ | na | na |
Published vs non-published results | ✗ | na | ✗ | ✗ | ✗ | ✗ | na | na | ✗ | ✗ | ✗ | na |
Peer reviewed vs not peer reviewed study | na | na | ✗ | na | ✗ | na | na | na | ✗ | na | na | na |
Heterosexual vs gay/mixed/unknown sample | ✗ | na | ✗ | na | ✗ | ✗ | na | na | ✗ | + | – | na |
Non-normality-transformed vs transformed variables | na | na | ✗ | ✗ | + | ✗ | na | na | ✗ | ✗ | + | na |
Non-converted vs converted effect sizes | na | na | ✗ | + | na | na | na | na | ✗ | ✗ | ✗ | na |
Age controlled for vs not controlled for | ✗ | na | + | na | ✗ | ✗ | na | na | ✗ | ✗ | ✗ | na |
Inclusion of non-relevant control variables vs not | na | na | na | ✗ | na | na | na | na | na | ✗ | ✗ | na |
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Note. Masc = masculinity; MAT = mating; REP = reproduction; T = testosterone.
Additional files
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Supplementary file 1
Effect size conversion formulas.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp1-v2.docx
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Supplementary file 2
Study coding decisions.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp2-v2.docx
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Supplementary file 3
Description of moderators.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp3-v2.docx
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Supplementary file 4
Moderation analyses.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp4-v2.docx
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Supplementary file 5
Global masculinity analyses.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp5-v2.docx
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Supplementary file 6
Funnel plots of effect sizes for mating measures.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp6-v2.docx
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Supplementary file 7
Output for q-value computation for all analyses.
- https://cdn.elifesciences.org/articles/65031/elife-65031-supp7-v2.docx
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Transparent reporting form
- https://cdn.elifesciences.org/articles/65031/elife-65031-transrepform1-v2.pdf