ArticleBMC health services research2025
Association between population level social risk factors and prevalence of diabetes.
Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Marine microplastic concentration and associations with stroke and chronic disease prevalence.NPJ cardiovascular health · 2026Article
- Machine Learning Based County Level Phenotypes Related to Diabetes Prevalence.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
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3 authors.
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Abstract
objectiveThe goal of this study was to evaluate the relationship between population level social risk and diabetes prevalence using US census tract data.
methodsWe combined data from the CDC PLACES 2019 database and the Opportunity Insights database. Multiple linear regression was run with standardized estimates to investigate incarceration, poverty, housing, education, employment, job environment, economic mobility, and healthcare access as independent correlates of diabetes prevalence at the census tract, adjusting for US population and state fixed effects.
resultsThe final analytic sample consisted of 11,457 census tracts within 157 counties in 38 states. Mean prevalence of diabetes was 11.8%. Healthcare access variables had the strongest association with every standard deviation (SD) increase in proportion with an annual check-up or proportion uninsured, associated with crude prevalence increase of 0.7 or 0.5 SD, respectively. Social risk factors were significant with poverty (every SD increase in income below the poverty line in the full model), housing (every SD increase in average rent for a two-bedroom apartment), and education (every SD increase in proportion of residents with a college degree) each associated with a 0.1 SD increase in crude prevalence of diabetes, and incarceration associated with 0.05 SD increase. Crude prevalence of diabetes varied across states.
conclusionsThe strongest drivers of prevalence of diabetes at the census tract were healthcare access, measured by insurance and having a usual source of care, income, housing, education, and incarceration. Efforts are needed to improve healthcare access while also addressing social risk at the neighborhood level.
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