Pomeroy, Emma

Stock, Jay T

Wells, Jonathan CK

English

Worldwide variation in human stature and limb proportions is widely accepted to reflect thermal adaptation, but the contribution of population history to this variation is unknown. Furthermore, stature and relative lower limb length (LLL) show substantial plastic responses to environmental stressors, e.g., nutrition, pathogen load, which covary with climate. Thus ecogeographic patterns may go beyond temperature-based selection. We analysed global variation in stature, sitting height and absolute and relative LLL using large worldwide samples of published anthropometric data from adult male (n = 571) and female (n = 268) populations in relation to temperature, humidity, and net primary productivity (NPP). Population history was modeled using spatial eigenvector mapping based on geographic distances reflecting the hypothesized pattern for the spread of modern humans out of Africa. Regression models account for ~ 50% of variation in most morphological variables. Population history explains slightly more variation in stature, sitting height and LLL than the environmental/climatic variables. After adjusting for population history, associations between (usually maximum) temperature and LLL are consistent with Allen's "rule" and may drive similar relationships with stature. NPP is a consistent negative predictor of anthropometry, which may reflect the growth-limiting effects of lower environmental resource accessibility (inversely related to NPP) and/or pathogen load

Apollo (Cambridge)

1       Population history and ecology, in addition to climate, influence human stature and body proportions  Emma Pomeroy1, Jay T. Stock2, and Jonathan C.K. Wells3  1 Department of Archaeology, University of Cambridge, Downing Street, Cambridge CB2 3DZ, UK 2 Department of Anthropology, Western University, London, Ontario, Canada, N6A 5C2 3 UCL Great Ormond Street Institute of Child Health, University College London, Great Ormond Street, London WC1N 3JH, UK     Supplementary Information   2  Supplementary Tables  Table S1 and S2: Full datasets analysed in this study: see accompanying Excel file.   Table S3: Summary statistics for the anthropometric and environmental variables used in this study for the male sample (n = 571). Variable Mean Standard deviation Maximum Minimum Stature (cm) 165.3 5.7 182.1 144.4 Sitting height (cm) 85.5 3.4 95.2 75.9 Lower limb length (cm) 79.8 4.0 92.5 68.5 Date (years CE) 1944 39 2015 1870 Minimum temperature of the coldest month (°C) 5.4 13.1 24.6 -45.0 Maximum temperature of the warmest month (°C) 29.6 7.2 46.0 7.2 Net primary productivity (tonnes of carbon m−2 yr−1 x 10-6) 3.30 2.78 11.15 0.0 Temperature-adjusted relative humidity (%) 88.0 10.0 100.0 56.6   Table S4. Summary statistics for the anthropometric and environmental variables used in this study for the female sample (n = 268). Variable Mean Standard deviation Maximum Minimum Stature (cm) 153.8 5.7 166.5 136.0 Sitting height (cm) 80.2 3.4 87.8 70.4 Lower limb length (cm) 73.5 4.3 87.1 63.6 Date (years CE) 1959 42 2015 1885 Minimum temperature of the coldest month (°C) 4.2 15.2 23.8 -44.7 Maximum temperature of the warmest month (°C) 29.3 7.4 47.9 7.3 Net primary productivity (tonnes of carbon m−2 yr−1 x 10-6) 0.351 0.299 1.100 0.0 Mean maximum relative humidity (%) 66.9 15.0 96.8 36.5   3  Table S5. Regression models for stature and body proportions relative to environmental conditions for the full male sample (n = 571). Dependent variable R R2 Adjusted R2 p AIC Partial regression R2 Predictors B SE Beta p Spatial filters (n)     Predictors Filters Shared Unexplained       Stature 0.686 0.470 0.464 <0.001 3261 0.178 0.242 0.050 0.530 Max. temperature 0.191 0.036 0.242 <0.001 4          Min. temperature -0.012 0.022 -0.027 0.6           Humidity -0.052 0.184 -0.009 0.8           NPP -7.431 0.770 -0.363 <0.001  Lower limb length 0.705 0.497 0.487 <0.001 2826 0.169 0.268 0.059 0.503 Max. temperature 0.151 0.026 0.275 <0.001 8          Min. temperature 0.050 0.016 0.164 0.002           Humidity -0.771 0.131 -0.195 <0.001           NPP -3.528 0.530 -0.248 <0.001  Sitting height 0.687 0.471 0.464 <0.001 2675 0.136 0.156 0.179 0.529 Max. temperature 0.003 0.021 0.006 0.9 5          Min. temperature -0.046 0.013 -0.178 <0.001           Humidity 0.586 0.112 0.172 <0.001           NPP -3.320 0.455 -0.272 <0.001  Relative lower limb length  0.706 0.498 0.487 <0.001 1258 0.190 0.252 0.056 0.502 Max. temperature 0.041 0.007 0.298 <0.001 9          Min. temperature 0.015 0.004 0.191 <0.001           Humidity -0.242 0.033 -0.241 <0.001           NPP -0.703 0.134 -0.195 <0.001  Relative lower limb length = standardised residual from regression of lower limb length on sitting height. Max. temperature = maximum temperature of the warmest month; Min. temperature = Minimum temperature of the coldest month; Humidity = standardised residual of maximum relative humidity adjusted for maximum temperature of the warmest month; NPP = Net Primary Productivity. Statistically significant predictors of the dependent variable at p ≤ 0.05 are shown in bold. 4  Table S6. Regression models for stature and body proportions relative to environmental conditions for the pre-1950 male sample (sensitivity analysis: n = 323). Dependent variable R R2 Adjusted R2 p AIC Partial regression R2 Predictors B SE Beta p Spatial filters (n)     Predictors Filters Shared Unexplained       Stature 0.777 0.604 0.591 <0.001 1741 0.039 0.319 0.246 0.396 Max. temperature 0.073 0.047 0.091 0.1 7          Min. temperature -0.029 0.027 -0.067 0.3           Humidity -0.316 0.214 -0.058 0.1           NPP -3.953 1.049 -0.182 <0.001  Lower limb length 0.790 0.624 0.611 <0.001 1503 0.116 0.363 0.145 0.376 Max. temperature 0.152 0.034 0.266 <0.001 8          Min. temperature -0.001 0.019 -0.004 0.9           Humidity -0.922 0.145 -0.238 <0.001           NPP -1.950 0.727 -0.127 0.008  Sitting height 0.733 0.537 0.527 <0.001 1441 0.116 0.140 0.281 0.463 Max. temperature -0.078 0.029 -0.165 0.007 4          Min. temperature -0.040 0.017 -0.158 0.017           Humidity 0.413 0.135 0.128 0.002           NPP -2.428 0.634 -0.191 0.002  Relative lower limb length  0.787 0.619 0.607 <0.001 619 0.145 0.344 0.130 0.381 Max. temperature 0.038 0.008 0.264 <0.001 7          Min. temperature 0.004 0.005 0.046 0.4           Humidity -0.253 0.037 -0.258 <0.001           NPP -0.409 0.185 -0.105 0.028  Relative lower limb length = standardised residual from regression of lower limb length on sitting height. Max. temperature = maximum temperature of the warmest month; Min. temperature = Minimum temperature of the coldest month; Humidity = standardised residual of maximum relative humidity adjusted for maximum temperature of the warmest month; NPP = Net Primary Productivity. Statistically significant predictors of the dependent variable at p ≤ 0.05 are shown in bold. 5  Table S7. Regression models for stature and body proportions relative to environmental conditions for the full female sample (n = 268). Dependent variable R R2 Adjusted R2 p AIC Partial regression R2 Predictors B SE Beta p Spatial filters (n)     Predictors Filters Shared Unexplained       Stature 0.724 0.524 0.510 <0.001 1513 0.093 0.247 0.183 0.476 Max. temperature 0.147 0.048 0.193 0.003 5          Min. temperature 0.004 0.026 0.010 0.9           Humidity 0.072 0.322 0.013 0.8           NPP -6.130 1.001 -0.323 <0.001  Lower limb length 0.754 0.569 0.554 <0.001 1342 0.112 0.309 0.149 0.431 Max. temperature 0.173 0.034 0.299 <0.001 6          Min. temperature 0.023 0.019 0.082 0.2           Humidity -0.196 0.236 -0.046 0.4           NPP -2.442 0.715 -0.170 <0.001  Sitting height 0.653 0.427 0.405 <0.001 1301 0.146 0.166 0.115 0.573 Max. temperature -0.166 0.032 -0.359 <0.001 7          Min. temperature 0.012 0.017 0.053 0.5           Humidity 0.776 0.217 0.225 <0.001           NPP -1.369 0.706 -0.119 0.05  Relative lower limb length  0.761 0.579 0.564 <0.001 552 0.141 0.322 0.116 0.421 Max. temperature 0.043 0.008 0.319 <0.001 6          Min. temperature 0.006 0.004 0.087 0.2           Humidity -0.055 0.054 -0.055 0.3           NPP -0.815 0.172 -0.244 <0.001  Relative lower limb length = standardised residual from regression of lower limb length on sitting height. Max. temperature = maximum temperature of the warmest month; Min. temperature = Minimum temperature of the coldest month; Humidity = standardised residual of maximum relative humidity adjusted for maximum temperature of the warmest month; NPP = Net Primary Productivity. Statistically significant predictors of the dependent variable at p ≤ 0.05 are shown in bold. 6  Table S8. Regression models for stature and body proportions relative to environmental conditions for the pre-1950 female sample (sensitivity analysis: n = 94). Dependent variable R R2 Adjusted R2 p AIC Partial regression R2 Predictors B SE Beta p Spatial filters (n)     Predictors Filters Shared Unexplained       Stature 0.808 0.652 0.628 <0.001 523 0.155 0.161 0.336 0.348 Max. temperature 0.284 0.084 0.288 <0.001 3          Min. temperature -0.045 0.046 -0.109 0.3           Humidity -0.309 0.575 -0.059 0.6           NPP -7.547 1.798 -0.354 <0.001  Lower limb length 0.809 0.654 0.635 <0.001 462 0.135 0.242 0.277 0.346 Max. temperature 0.317 0.061 0.433 <0.001 2          Min. temperature -0.065 0.034 -0.213 0.06           Humidity 0.081 0.414 0.021 0.8           NPP -2.127 1.242 -0.134 0.09  Sitting height 0.661 0.437 0.412 <0.001 427 0.395 0.038 0.004 0.563 Max. temperature -0.117 0.05 -0.244 0.021 1          Min. temperature 0.011 0.027 0.056 0.7           Humidity 1.073 0.248 0.418 <0.001           NPP -2.841 1.006 -0.274 0.006  Relative lower limb length  0.786 0.618 0.596 <0.001 192 0.164 0.279 0.175 0.382 Max. temperature 0.082 0.014 0.500 <0.001 2          Min. temperature -0.015 0.008 -0.213 0.07           Humidity -0.065 0.097 -0.074 0.5           NPP -0.184 0.292 -0.052 0.5  Relative lower limb length = standardised residual from regression of lower limb length on sitting height. Max. temperature = maximum temperature of the warmest month; Min. temperature = Minimum temperature of the coldest month; Humidity = standardised residual of maximum relative humidity adjusted for maximum temperature of the warmest month; NPP = Net Primary Productivity. Statistically significant predictors of the dependent variable at p ≤ 0.05 are shown in bold.  

Population history and ecology, in addition to climate, influence human stature and body proportions.

https://www.repository.cam.ac.uk/bitstream/handle/1810/316370/Pomeroy%20et%20al%20Supplementary%20information.pdf?sequence=2&isAllowed=y

Population history and ecology, in addition to climate, influence human stature and body proportions.

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