Diversity in social, cultural, and environmental factors also affect disease risk, and can contribute to confounding in genetic studies. In the case of complex traits with strong environmental influences, such as psychiatric conditions, the need to account for non-genetic contributors to disease is important. Unfortunately, measurement of environmental factors can be difficult, so proxy measures such as zip code or insurance status can be used to model non-genetic risk factors such as air quality or accessibility to quality health care. PCs calculated from genotypes can control for population structure due to genetic relatedness, but this approach alone may not capture the social and environmental factors that are encompassed in self-reported “race” and “ethnicity”, even though these measures can be correlated with genetic ancestry. Self-reported measures of diversity can help in the modeling of societal determinants of health, such as increased stress due to the experience of racism and inequality and related variability in environmental factors (e.g., socio-economic status) that affect disease risk. However, the reliance on race and ethnicity as proxy variables for environmental effects or in order to control
