Sociodemographic Disparities in Self-Reported Stroke: A Cross-Sectional, Population-Based Analysis

Background:Stroke is one of the leading causes of death and disability worldwide.There is a lack of comprehensive studies examining how multiple social determinants of health (SDOH) interact to influence stroke presentation. Methods:A cross-sectional, population-based analysis was performed using data from the 2023 U.S.National Health Interview Survey.Adult participants (>18 years) with self-reported stroke were compared to those without.Univariable and multivariable logistic regression analysis was performed to assess the association of each SDOH with self-reported stroke prevalence.Odds ratios (ORs) and 95% confidence intervals (CI) were reported.P-values <0.05 were statistically significant. Results:A total of 29,484 individuals responded to the self-reported stroke question, of which 1133 (3.84%) were stroke cases and 28,351 (96.16%) were non-stroke cases.In multivariable analysis, self-reported stroke prevalence was significantly associated with age (36-49: OR = 6.60, p<0.