The impact of late-career job loss and genetic risk on body mass index: Evidence from variance polygenic scores

Unemployment shocks from the COVID-19 pandemic have reignited concerns over the long-term effects of job loss on population health. Past research has highlighted the corrosive effects of unemployment on health and health behaviors. This study examines whether the effects of job loss on changes in body mass index (BMI) are moderated by genetic predisposition using data from the U.S. Health and Retirement Study (HRS). To improve detection of gene-by-environment (G × E) interplay, we interacted layoffs from business closures—a plausibly exogenous environmental exposure—with whole-genome polygenic scores (PGSs) that capture genetic contributions to both the population mean (mPGS) and variance (vPGS) of BMI. Results show evidence of genetic moderation using a vPGS (as opposed to an mPGS) and indicate genome-wide summary measures of phenotypic plasticity may further our understanding of how environmental stimuli modify the distribution of complex traits in a population.

Household income (log) Log of total (respondent + spouse) household income in 2010 dollars. Includes earnings, household capital income, income from all pensions and annuities, income from social security disability and supplemental social security income, income from social security retirement, spouse or widow benefits, income from unemployment or workers compensation, income from veteran's benefits, welfare and food stamps, alimony, other income, and lump sums from insurance, pension and inheritance.
Household wealth ($100k) Total household income in 2010 dollars divided by 100,000 for scalar consistency. It is the sum of the value of primary residence, net value of real estate (not including primary residence), net value of vehicles, net value of businesses, net value of stocks, mutual funds, and investment trusts, value of checking, savings or money market accounts, value of CD, government savings bonds, and T-bills, net value of bonds and bond funds, and the net value of all other savings, less the value of all mortgages/land contracts (primary residence), value of other home loans (primary residence), and the value of any other debt.
Firm size a Binary (0/1) variables for firm size categories: Less than or equal to 4 employees; 5-14 employees; 15-24 employees; 25-99 employees; 100-499 employees. The omitted category is firm size greater than or equal to 500 employees.
Part time 1=works part time; 0=does not work part time.
Industry a Binary (0/1) variables for industry categories: agriculture, fishing, or farming; construction or mining; manufacturing; trade; public services; finance, insurance, or real estate; public administration. The omitted category is misc. services.
Occupational status a Binary (0/1) variables for blue collar and service workers. The omitted category is white collar workers.
Job tenure a Current job tenure in years.
Health status 1=excellent or very good self-reported health; 0=good, fair, or poor selfreported health.
Health insurance 1=covered by a federal or employer-sponsored health insurance program; 0=otherwise.
Exercise 1=exercises vigorously three or more times per week; 0=otherwise.
Ever smoke cigarettes 1=smoked 100 or more cigarettes in their lifetime; 0=otherwise.
Cigarettes per day a Total number of cigarettes smoked per day, excluding pipes or cigars. Variable is set equal to zero if respondent does not smoke.
Drinks per week Total number of alcoholic drinks per week Doctor diagnosed psychiatric issue a 1=reports doctor diagnosed emotional or psychiatric problems; 0=otherwise.
a Variables with additional category for missing values. Analyses also controlled for the first 10 principal components of the European ancestry genetic data.  The t-test p-value refers to the p-value from the difference in means between the treated and control groups before and after matching. The V(T)/V(C) column presents the ratio of a continuous variable's variance for the treatment group over the variance for the control group. Additional covariates in the matching procedure: survey year, regional Census division, additional categories for variables with missing values, and the first 10 principal components of the European ancestry genetic data. We used kernel-based propensity score matching with a bandwidth of 0.06. Unmatched control observations=11,629; Unmatched treated observations=399; Matched control observations=11,559; Matched treated observations=375. Regressions were run separately for the full analytic sample (Column 1), and then stratified by high versus low vPGS groups (Columns 2 and 3). vPGS groups were stratified at the median vPGS value. All specifications adjust for BMI in the previous wave, or BMI(t-2), and for the conditioning variables used in the propensity score matching that are reported in Table 1 and defined in detail in Supplementary Table S1. Individuals in the treated and control groups can have multiple observations. Unique N(treated)=428; unique N(control)= 3,562. Abbreviations: SD, standard deviation; Obs., observations. BMI statistics were calculated for control and treated individuals for all waves they were observed in the HRS between the ages of 50 and 70 (regardless of whether or not all waves were included as treated or control observations in the final analytic sample). Personwave observations (N=14,412). Total unique observations (N=3,939).