Abstract
Introduction: Social determinants of health (SDH) are major contributors to stroke incidence and disparities, yet their relationship with severity and disability is relatively unexplored. The purpose of this study is to provide preliminary findings on SDH measures at the individual- and ZIP code-level across outcomes of stroke severity and disability. Methods: We used data from 344 stroke patients from the ongoing Transitions of Care Stroke Disparities Study (TCSDS) enrolled 2018-2020 from sites throughout Florida. TCSDS aims to identify disparities in hospital-to-home transition of stroke care. Individual-level SDH were collected by a trained interviewer at discharge; ZIP-level SDH data were obtained from a contracted data company. Outcomes included stroke severity at admission measured by the NIH Stroke Scale (NIHSS; Mild: 0-4; Moderate: 5-14; Severe: ≥15) and obtained from the AHA Get with the Guidelines-Stroke program; and disability at discharge measured by the modified Rankin Scale (mRS; 0-1; 2-5). Non-parametric statistical tests were used to compare individual- and ZIP-level SDH by NIHSS and mRS scores. Results: Most patients were older (median age 62 years, IQR: 19), male (58%), non-Hispanic White (39%) or Hispanic (35%) and suffered mild strokes (median NIHSS, IQR: 2, 4) with mild disability (median mRS: 1, 4). Those living with children (LWC) had more moderate strokes, while those living with a spouse/partner (LWP) had more severe strokes (p=0.004). Less than high school (HS)-, HS-, and college-educated patients had more moderate, mild, and severe strokes, respectively (p=0.02). ZIP-level unemployment rate was positively associated with NIHSS (p=0.031). Higher mRS was seen among Spanish and Haitian Creole speakers (p=0.005); HS- and less than HS-educated patients (p=0.005); and those with lower levels of social support (p=0.019). LWC had higher mRS scores, while the opposite was true for LWP (p=0.001). Conclusions: Despite the intersectional nature of SDH, these findings highlight possible mechanisms by which education, economic conditions and psychosocial factors may influence stroke severity and disability after stroke. More data are necessary to determine whether these SDH influence long term stroke outcomes post-discharge.
