Abstract

Background: There is known geographic variation in recurrent stroke rates in the US; however, the contributions of socioeconomic status (SES), healthcare access/utilization, and community resources to these disparities are uncertain. We assessed community characteristics in counties having persistently higher recurrent stroke rates over a 16-year period. Methods: We included 3,485,618 fee-for-service Medicare beneficiaries aged ≥65y discharged with ischemic stroke from 2001-2016, grouped into four 4-year periods. We categorized 3221 US counties or equivalents into 6 groups based on the % of stroke patients with a recurrent stroke within 1 year. Persistently high-recurrence counties were those in the highest sextile for each 4-year period. We integrated county-specific demographic, geographic, SES, general health, care availability, health behavior, and environmental data from the US Census Bureau, USDA Economic Research Service, and Dartmouth Atlas. We calculated mean standardized differences in county characteristics between high-recurrence and other counties and used logistic regression to model high-recurrence counties as a function of 12 potentially modifiable county characteristics. Results: There were 133 persistently high-recurrence counties that were concentrated in the South Central US and included 140,144 stroke patients during the study (A; mean age 78.3y, 57% women, 82% White, 11.5% stroke recurrence vs 79.0 y, 55% women, 86% White, 10.5% stroke recurrence in other counties). Compared with the rest of the US, these counties had populations with lower SES, poorer health, more limited access to care providers and recreation/fitness, and reduced rates of preventive testing (B). The model including 12 potentially actionable characteristics had a c statistic of 0.84. Conclusions: Our findings highlight the value of identifying potentially modifiable community characteristics that, if improved, might reduce recurrent stroke rates.

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