The second important observation from our study was the genome-wide evidence for the heritability of BMI even though no single SNP emerged as a clear determinant of individual differences in BMI. Although finding the “missing heritability” has been a central issue for genetic epidemiologists (Manolio et al. 2009), it has not entered into recent demographic studies. As our methods section explains, genome-wide data provide exceptional detail on the genetic similarity of unrelated persons in our studies. These data are already available from a number of population data sources that also contain indicators of mobility, migration, mortality, marriage, birth outcomes, health, and health behaviors. If genes are associated with environmental exposure and the health outcome of interest (e.g., genes linked to novelty-seeking behaviors may predict selection into a social group of smokers and may also predict smoking behavior), then researchers may reach erroneous conclusions about the role of environmental factors. By creatively using these data to account for genetic factors that predict the independent and dependent variables, demographers can rule out alternative explanations. Lee and colleagues (2012) extended the GCTA model
