County-Level Associations Between Structural Inequalities in Social Determinants of Health and Stroke Prevalence Among U.S. Adults: An Ecologic Study.

Abstract

Women and racial minority groups bear a disproportionate burden of stroke. Stroke disparities have been partially explained by gender and race differences in individual-level SES and neighborhood-level education and residential segregation. This study explored whether structural sexism and structural racism, operationalized as structural inequalities between gender groups and between race-ethnic groups across multiple social determinants of health at the county level, could be contributors by investigating their associations with stroke prevalence. County-level age-adjusted stroke prevalence in 2019 from the Centers for Disease Control and Prevention Population Level Analysis and Community Estimates were linked with data from the American Community Survey (2015-2019) and the 2018 Vera Institute of Justice report. County-level structural sexism and structural racism toward Asian, Black, and Hispanic persons in 8 social determinants of health (education, employment, yearly earnings, poverty status, health insurance, home ownership, residential segregation, and jail incarceration) were calculated. Beta regressions were used to estimate the associations between structural sexism, structural racism, and stroke prevalence. Age-adjusted stroke prevalence varied from 1.9% to 8.2% across 3,121 U.S. counties. Structural sexism in being self-employed in own incorporated business, having an insurance, and living above poverty line at the county level were associated with higher stroke prevalence. Indicators of structural racism toward Black persons were consistently associated with higher stroke prevalence, whereas most indicators of structural racism toward Asian and Hispanic persons were associated with lower stroke prevalence. Structural sexism and structural racism at the county level were associated with stroke prevalence, suggesting that future multilevel studies to understand their role in explaining individual level stroke risk and disparities are warranted.