Abstract Body: Background: Women and racial minority groups bear a disproportionate stroke burden, including higher stroke prevalence and mortality. Stroke disparities have been partially explained by gender and race differences in individual-level socioeconomic status and neighborhood-level education and residential segregation. Whether macro-level structural inequalities between gender groups and between race-ethnic groups across multiple societal sectors are associated with stroke prevalence is unknown.

Methods: County-level age-adjusted stroke prevalence estimates among adults in 2019 from the CDC PLACES database were linked with educational, economic, and segregation data from the American Community Survey (2015-2019 five-year estimates) and the 2018 incarceration data from the Vera Institute of Justice. We calculated county-level relative inequalities between women and men and race-ethnic groups (White:Black, non-Hispanic White:Hispanic, White:Asian) in education attainment, employment, yearly earnings, poverty status (living above the poverty line), health insurance, home ownership, residential segregation, and jail incarceration rates (Table 1). We used beta regression to estimate the associations between these inequality measures and stroke prevalence, adjusting for county-level confounders.

Results: Age-adjusted stroke prevalence varied from 1.9% to 8.2%. Higher gender inequalities in educational attainment, employment, and yearly earnings were associated with lower stroke prevalence (Table 2). In comparison, higher gender inequalities in health insurance and poverty status were associated with higher stroke prevalence. The associations between racial-ethnic inequality measures and stroke prevalence were weaker than associations for gender inequalities (Table 2). For all race-ethnic minority groups, higher relative inequalities in poverty status and residential segregation were associated with higher stroke prevalence. Higher relative inequalities in incarceration rates between Hispanic-non-Hispanic White and Asian-White were also associated with higher stroke prevalence. Race-ethnic inequalities in other measures were not consistently associated with stroke prevalence.

Conclusion: In this ecological study, relationships between structural inequalities and stroke prevalence measured at the county level were evident, suggesting future individual-level studies with control for confounding factors are warranted.