MS3 Geisinger Commonwealth School of Medicine Old Forge, Pennsylvania, United States
Introduction: Analyses of stroke racial disparities center upon the Southeastern US, a region with markedly higher stroke burden. Some data suggest this is due to larger racial disparities in the prevalence of risk factors. With a concentration of primary and comprehensive stroke centers—and different demographics and socioeconomic profile—the San Francisco Bay Area is a valuable locale to investigate mechanisms of racial disparity in ischemic stroke.
Methods: Stroke hospitalization was selected as a surrogate for stroke incidence within the CDC Interactive Atlas of Heart Disease and Stroke. Eleven Bay Area counties were selected for analysis as defined by the California Regional Economies Employment. A search of the Atlas was conducted for demographics, ischemic stroke hospitalization rates, socioeconomic measures, and prevalence of risk factors.
Results: Blacks were hospitalized with ischemic stroke at an average rate 1.54 times greater than whites (SD=0.31). Counties with the greatest disparity were Santa Cruz (2.47), San Francisco (1.98), and Marin (1.79) despite relatively large white populations in Santa Cruz (57.2%) and Marin (71.1%) (x̄=41.6, SD=12.7). Among counties with the largest Black populations (Solano 13.5%, Alameda 10.3%, Sacramento 9.4%), Alameda and Sacramento had disproportionately greater Black stroke hospitalization rates than Solano (11.2, 12, and 10, respectively). When comparing these counties with those of the smallest Black populations (0.7-1.4%), there was no significant difference (p=ns) in the prevalence of smoking, diabetes, hypertension, hypercholesterolemia, and obesity. The prevalence of food stamps, severe housing cost burden, unemployment rate, and median household income also did not significantly differ.
Conclusion : These data suggest that ischemic stroke racial disparities may not correlate with Black population size in a given region, and differences in stroke hospitalization rates may not be wholly explained by the prevalence of risk factors or socioeconomic status. Investigation of these trends at the health system and patient level will further elucidate underlying mechanisms.
