ArticleJournal of public health management and practice : JPHMP
Examining the Burden of Chronic Disease and Low SES to Identify High-Need Rural Counties.
Article in Journal of public health management and practice : JPHMP. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThis study aims to identify rural counties across the United States that experience combined high prevalence of chronic diseases and low socioeconomic status (SES), categorizing them as high-need areas. We analyze the geographic and sociodemographic profiles of these counties and examine differences in access to care for high-need rural counties.
methodsWe used the 2023 PLACES dataset from the Centers for Disease Control and Prevention for chronic disease prevalence estimates and the 2020 American Community Survey for SES indicators. Counties were classified into tertiles based on disease prevalence and SES indicators, creating an overall composite score identifying counties as low, moderate, or high need. We used ArcGIS Pro to map the distribution of high-need counties across the United States with statistical analyses of geographic distribution and health care access conducted through quantile regression and spatial autocorrelation methods.
findingsA total of 1934 rural counties, representing nearly 99% of rural counties, were included in this analysis, identifying 534 high-need counties, primarily in the southeastern United States. These counties had significantly higher proportions of non-Hispanic Black residents. Significant spatial autocorrelation indicated that counties with similar levels of chronic disease and SES are geographically clustered. High-need counties faced greater distances to health care facilities compared to their lower-need counterparts, highlighting substantial barriers to accessing care.
conclusionThis analysis identified geographic variation in chronic disease burden and socioeconomic status across rural US counties, with high-need areas concentrated in the Southeast. The findings demonstrate the value of a simple, replicable framework for identifying rural counties facing overlapping health and socioeconomic challenges. This approach can support efforts to prioritize resource allocation and guide future research and policy aimed at improving access and outcomes in underserved rural communities.
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