Burgeoning epidemiological, animal, and cellular data link environmental endocrine-disrupting chemicals (EDCs) to metabolic dysfunction. Disproportionate exposure to diabetes-associated EDCs may be an underappreciated contributor to disparities in metabolic disease risk. The burden of diabetes is not uniformly borne by American society; rather, this disease disproportionately affects certain populations, including African Americans, Latinos, and low-income individuals. The purpose of this study was to review the evidence linking unequal exposures to EDCs with racial, ethnic, and socioeconomic diabetes disparities in the U.S.; discuss social forces promoting these disparities; and explore potential interventions. Articles examining the links between chemical exposures and metabolic disease were extracted from the U.S. National Library of Medicine for the period of 1966 to 3 December 2016. EDCs associated with diabetes in the literature were then searched for evidence of racial, ethnic, and socioeconomic exposure disparities. Among Latinos, African Americans, and low-income individuals, numerous studies have reported significantly higher exposures to diabetogenic EDCs, including polychlorinated biphenyls, organochlorine pesticides, multiple chemical constituents of air pollution, bisphenol A, and phthalates. This review reveals that unequal exposure to EDCs may be a novel contributor to diabetes disparities. Efforts to reduce the individual and societal burden of diabetes should include educating clinicians on environmental exposures that may increase disease risk, strategies to reduce those exposures, and social policies to address environmental inequality as a novel source of diabetes disparities.

This study provides an empirical test of two mechanisms (social capital and exposure to air pollution) that are theorized to mediate the effect of neighborhood on health and contribute to racial disparities in health outcomes. To this end, we utilize the Social Capital Benchmark Study, a national survey of individuals nested within communities in the United States, to estimate how multiple dimensions of social capital and exposure to air pollution, explain racial disparities in self-rated health. Our main findings show that when controlling for individual-confounders, and nesting within communities, our indicator of cognitive bridging, generalized trust, decreases the gap in self-rated health between African Americans and Whites by 84%, and the gap between Hispanics and Whites by 54%. Our other indicator of cognitive social capital, cognitive linking as represented by engagement in politics, decreases the gap in health between Hispanics and Whites by 32%, but has little impact on African Americans. We also assessed whether the gap in health was explained by respondents’ estimated exposure to toxicity-weighted air pollutants from large industrial facilities over the previous year. Our results show that accounting for exposure to these toxins has no effect on the racial gap in self-rated health in these data. This paper contributes to the neighborhood effects literature by examining the impact that estimated annual industrial air pollution, and multiple measures of social capital, have on explaining the racial gap in health in a sample of individuals nested within communities across the United States.

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Cities in the United States (U.S.) are increasingly developing sustainability initiatives to improve local economies while addressing environmental concerns. Since 1990, the U.S. Environmental Protection Agency’s (EPA) Brownfield Revitalization Program has encouraged the remediation of postindustrial sites to create new areas for real estate development. However, previous research demonstrates that industrial areas are more likely to be in predominantly poor and racial/ethnic minority communities. A central argument favoring redevelopment is that remediation helps mitigate environmental inequality and achieve environmental justice for aggrieved communities. Still, very little research examines if and how these communities benefit from these changes. This article examines this question by reviewing the related literature and applying insights to a quasi-experimental analysis of brownfield redevelopment’s impact on racial/ethnic composition and income levels of neighborhoods. Publicly available data were acquired from the EPA Cleanups in My Community data portal and the 5-Year American Community Survey—released annually from 2006 to 2015—to examine demographic changes in neighborhoods where brownfield redevelopment occurred. The study implements a difference-in-differences model using two-way fixed effects regression models on a panel data set of 4,740 census tracts in 48 contiguous U.S. states (or Lower 48 states). This study’s findings suggest that wealthier White and Latino populations are more likely to benefit from brownfield redevelopment than Black populations in affected neighborhoods.

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