Human height is a highly variable trait, both within and between populations, has a high heritability, and influences the manner in which people behave and are treated in society. Although we know much about human height, this information has rarely been brought together in a comprehensive, systematic fashion. Here, we present a synthetic review of the literature on human height from an explicit evolutionary perspective, addressing its phylogenetic history, development, and environmental and genetic influences on growth and stature. In addition to presenting evidence to suggest the past action of natural selection on human height, we also assess the evidence that natural and sexual selection continues to act on height in contemporary populations. Although there is clear evidence to suggest that selection acts on height, mainly through life-history processes but perhaps also directly, it is also apparent that methodological factors reduce the confidence with which such inferences can be drawn, and there remain surprising gaps in our knowledge. The inability to draw firm conclusions about the adaptiveness of such a highly visible and easily measured trait suggests we should show an appropriate degree of caution when dealing with other human traits in evolutionary perspective.

Meta-analyses of genome-wide association studies (GWAS), which dominate genetic discovery are based on data from diverse historical time periods and populations. Genetic scores derived from GWAS explain only a fraction of the heritability estimates obtained from whole-genome studies on single populations, known as the ‘hidden heritability’ puzzle. Using seven sampling populations (N=35,062), we test whether hidden heritability is attributed to heterogeneity across sampling populations and time, showing that estimates are substantially smaller from across compared to within populations. We show that the hidden heritability varies substantially: from zero (height), to 20% for BMI, 37% for education, 40% for age at first birth and up to 75% for number of children. Simulations demonstrate that our results more likely reflect heterogeneity in phenotypic measurement or gene-environment interaction than genetic heterogeneity. These findings have substantial implications for genetic discovery, suggesting that large homogenous datasets are required for behavioural phenotypes and that gene-environment interaction may be a central challenge for genetic discovery.