Stroke in women between 2006 and 2018: Demographic, socioeconomic, and age disparities.

Abstract

Black Americans have a higher prevalence of stroke and stroke-related deaths than any other racial group. Racial disparities in stroke outcomes are even wider among women than men. Conventional studies have cited differences in lifestyle (i.e. smoking, alcohol consumption, etc.) and vascular risk factors between races as the source of these disparities. However, these studies fail to account for the higher prevalence of minoritized populations at the lower end of the socioeconomic distribution. This study explores differences in stroke risk factors across age and socioeconomic cohorts to determine whether comorbidities can sufficiently explain disparities at all ages and income levels. Using the 2006-2018 National Health Interview Survey data, statistical analysis evaluated differences in risk factors among a full sample cohort (aged 18-85 years; n = 131,091) and a "young" subsample cohort (aged 18-59 years; n = 6183) of women. Logistics and unconditional quantile regression models assessed the relationship between stroke and comorbid, demographic, and behavioral characteristics across socioeconomic classes. Results suggest that Black women had a 1.415-fold (confidence interval = 1.259, 1.591) higher likelihood of stroke compared with White women after controlling for age, behavior, and comorbidities. Racial disparities were not statistically significant at the higher income ranges for either the full (odds ratio = 1.404, p = 0.3114) or young samples (odds ratio = 1.576, p = 0.7718). However, Blacks had significantly higher odds of stroke in the lower quartiles (lower odds ratio: 1.329, p = 0.0242; lower middle odds ratio: 1.233, p = 0.0486; and upper middle odds ratio: 1.994, p = 0.0005). Disparities were larger among young women (odds ratio = 1.449, confidence interval = 1.211, 1.734). While comorbidities were highly associated with stroke prevalence in all socioeconomic cohorts, Blacks only had higher relative odds in the lower income classes. Lack of biological or behavioral explanations for these findings suggests that unobserved or uncontrolled factors such as systemic racism, prejudicial institutions, or differential treatment may contribute to this.