Background: Cardiovascular disease remains a leading cause of preventable mortality in the United States, with rural counties in the Deep South experiencing disproportionately high burdens. Grounded in the Andersen healthcare utilization model, this study examined how enabling resources, predisposing characteristics, and access-related barriers relate to coronary heart disease (CHD) prevalence and mortality. Methods: This ecological analysis included 418 counties across Alabama, Georgia, Louisiana, Mississippi, and South Carolina. Using Local Indicators of Spatial Association (LISA) and multivariable linear regression, we tested three theory-based hypotheses and assessed the spatial clustering of CHD outcomes, while identifying key structural and sociodemographic predictors. Results: Counties with greater rurality and fewer healthcare providers exhibited significantly higher rates of CHD prevalence and mortality. Primary care provider availability and higher household income were protective factors. Digital exclusion, measured by lack of access to computers or mobile devices, was significantly associated with higher CHD prevalence and mortality. Spatial analysis identified the counties with better-than-expected cardiovascular outcomes despite structural disadvantages, suggesting the potential role of localized resilience factors and unmeasured community-level interventions. Conclusions: The findings affirm the relevance of the Andersen model for understanding rural health disparities and highlight the importance of investing in both digital infrastructure and healthcare capacity. Expanding telehealth without addressing provider shortages and social determinants may be insufficient. Local policy innovations and community resilience mechanisms may offer scalable models for improving cardiovascular health in disadvantaged areas.

Background: Mississippi has one of the highest rates of food insecurity in the United States, with many counties experiencing significant disparities in access to healthy food. Therefore, understanding the spatial distribution of these disparities is essential for developing targeted interventions. Purpose: This study aims to investigate the spatial distribution of food insecurity and its associated social and health factors across Mississippi counties to identify areas in need of intervention. Methods: Cross sectional study was conducted using publicly available datasets to examine food insecurity and its associated factors at the county level. Pearson correlations and bivariate Moran’s I were used to explore relationships between food insecurity, food banks, health outcomes, and social determinants of health. Results: Food insecurity was highest in counties bordering Louisiana, with significant correlations between food insecurity and poverty, poor health outcomes, and limited broadband access. Conversely, food banks were concentrated in Northeast Mississippi, where food insecurity rates were lower. Conclusions: The findings highlight the need for more equitable distribution of resources across Mississippi counties, particularly in areas with higher food insecurity rates. This study provides valuable insights for public health officials to address food insecurity through targeted, region-specific interventions.