A team of health equity researchers from several institutions has leveraged a complex web of data to test a hypothesis: That structural racism is associated with resources and structures at the neighborhood level that are closely associated with poor health. What they found in an analysis of highly localized, community-level data illustrates how racism is deeply interrelated with poor health outcomes.
L. Ebony Boulware, M.D., dean of Wake Forest University School of Medicine, was senior author of the paper, which published online today in JAMA Network Open.
Dinushika Mohottige, M.D., assistant professor of population science and policy, and medicine (nephrology), at the Icahn School of Medicine at Mount Sinai, in New York City, served as first author of the paper, which describes how neighborhood prevalence of chronic kidney disease, diabetes and hypertension are strongly associated with an increased burden of structural racism indicators.
The research team conducted an observational cross-sectional study in Durham County, North Carolina, using public data sources and deidentified electronic health records to explore how a comprehensive collection of data points associate the presence of structural racism and the neighborhood prevalence of these three chronic health conditions.
They collaborated with colleagues from Duke University, the University of North Carolina at Chapel Hill, North Carolina State University and the Feinstein Institutes for Medical Research.
In the paper, the authors explained that structural racism is defined as how societies foster discrimination through a series of systems that are reinforcing, such as housing, education and unemployment.
“These systems cascade into discriminatory beliefs, values and the distribution of resources,” Boulware said. “Dr. Mohottige and I agreed it was important to tap the unusual data assets available in Durham to learn how we can improve the health of communities and individuals by identifying the factors that may affect their health the most. Our goal was to use the data to help us identify possible interventions.”
“Data which measure health outcomes such as kidney disease and diabetes - and which also measure social determinants of health, including information on the built environment and reported neighborhood violence - help us understand how the conditions where people live affect their well-being,” she said. “This is especially true for groups that, because of their race or ethnicity, historically experience worse health outcomes when compared to others.