Abstract
This paper uses baseline data from an observational study to estimate the determinants of racial and gender disparities in obesity. Samples of low-income workers in Minneapolis and Raleigh reveal that respondents in Minneapolis have lower Body Mass Indices (BMIs) than respondents in Raleigh. There are large, statistically significant race and gender effects in estimates of BMI that explain most of the disparity between the two cities. Accounting for intersectionality - the joint impacts of being Black and a woman - reveals that almost all the BMI gaps between Black women in Minneapolis and Raleigh can be explained by age and education differences.
Highlights
Much of the literature on food insecurity and racial disparities in health outcomes begins with the underlying assumption that consumers’ individual choices explain observed disparities across groups
For the purposes of this article, which uses the baseline data from the WAGE$ sample collected in 2018, the minimum wage serves to identify low-wage workers in each city but will not serve as a bespoke causal determinant of body mass indices (BMIs), but we will utilize this survey instrument as a tool to explore the determinants of BMI among low-wage workers in both sites
Because obesity and high BMI are predictors of adverse health outcomes, 24 Agricultural and Resource Economics Review policymakers and health advocates have sought economic interventions that might narrow the racial gaps in BMI
Summary
Much of the literature on food insecurity and racial disparities in health outcomes begins with the underlying assumption that consumers’ individual choices explain observed disparities across groups. Often missing from conventional analyses is an examination of contextual factors that might offer policy insights about racial and ethnic disparities in diets, food consumption, and, health outcomes. This article utilizes survey data from the WAGE$ survey of low-wage workers in Minneapolis, Minnesota, and Raleigh, North Carolina. This data was collected to study the long-term health effects of introducing a phased in minimum wage in Minneapolis, with Raleigh serving as a control site, as there is no planned minimum wage increase and the state of North Carolina’s preemption laws prevent cities or municipalities from establishing their own minimum wage. For the purposes of this article, which uses the baseline data from the WAGE$ sample collected in 2018, the minimum wage serves to identify low-wage workers in each city but will not serve as a bespoke causal determinant of BMI, but we will utilize this survey instrument as a tool to explore the determinants of BMI among low-wage workers in both sites
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