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High body mass index (BMI) continues to be a pressing public health concern in the U.S. Recent statistics show 75% of the adult population is overweight—42% of which are classified as obese (Ogden et al., 2012). Though changes in individuals' lifestyles have fueled the obesity epidemic in the United States, more work is needed to understand the joint contribution of biological and social forces that affect body weight over the life course. In particular, research must incorporate genetic, behavioral, and social factors to more accurately explain the complex etiology of cardiovascular risk factors like BMI and, more generally, the degree to which socioeconomic stressors trigger health inequities, and are amplified through biological channels. The following paper uses a gene-by-environment (G x E) interaction analysis to quantify the joint effect of individuals' genetic predisposition and job loss on changes in BMI. A major contribution of this paper is the use of both a mean PGS (mPGS) and a variance PGS (vPGS) for BMI in the G x E analysis. The vPGS—which has not been used in social genomics research—captures the genetic effects of phenotypic variability, making it a more suitable to detect changes in a complex phenotype like BMI that are the result of environmental factors.