The indirect effects of food insecurity on obesogenic environments.

Abstract

The Centers for Disease Control and Prevention (CDC) estimates 39.8% of United States (US) residents have obesity. This study examined obesity-related factors at the county-level to determine the indirect effects on physical inactivity, insufficient sleep duration, income inequality, food insecurity, on obesity rates. Using the 2018 Robert Wood Johnson Foundation (RWJF) County Health Rankings data set, a multiple regression analysis was conducted to measure the percentage of the obesity rate explained by physical inactivity, insufficient sleep duration, food insecurity, and income inequality via geographically weighted county means. RWJF combines US federal and state datasets to produce a composite dataset comprised of information primarily from adults over the age of 18 from the 3,143 counties found within US borders. The aggregate county-level data serves as the unit of measure (N = 3,143). The indirect relationships (the product of two direct relationships) between obesity-related variables and obesity were measured and illustrated through a path analysis model. This study found the combination of independent variables explained 53% of the obesity rates in the US, R 2 = 0.53, p < 0.001, two-tailed. This study also found that food insecurity has both a direct and indirect effect on obesity, physical inactivity, and insufficient sleep duration. Physical inactivity has a direct effect on obesity and insufficient sleep duration, along with an indirect effect on obesity. Insufficient sleep duration has a direct effect on obesity. This analysis found that food insecurity indirectly impacts an obesogenic environment and drives county-level BMI averages. The dataset used for analysis predates the COVID-19 pandemic but presents the effect of food insecurity during a normative year. The findings, though interesting, provide an opportunity for future research.