Abstract
BACKGROUND: Socially determined vulnerabilities (SDVs) to health disparities often cluster within the same individual. SDVs are separately associated with increased risk of heart failure (HF). The objective of this study was to determine the cumulative effect of SDVs to health disparities on incident HF hospitalization. METHODS AND RESULTS: Using the REGARDS (Reasons for Geographic and Racial Differences in Stroke) cohort study, we studied 25 790 participants without known HF and followed them for 10+ years. Our primary outcome was an incident HF hospitalization through December 31, 2016. Guided by the Healthy People 2020 framework for social determinants of health, we examined 10 potential SDVs. We retained SDVs associated with incident HF hospitalization (P<0.10) and created an SDV count (0, 1, 2, 3+). Using the count, we estimated Cox proportional hazard models to examine associations with incident HF hospitalization, adjusting for potential confounders. Models were stratified by age (45-64, 65-74, and 75+ years) because past reports suggest greater disparities in HF incidence at younger ages. Participants were followed for a median of 10.1 years (interquartile range, 6.5-11.9). Black race, low educational attainment, low annual household income, zip code poverty, poor public health infrastructure, and lack of health insurance were associated with incident HF hospitalization. In adjusted models, among those 45 to 64 years, compared with having no SDV, having 1 SDV (hazard ratio, 1.85 [95% CI, 1.12-3.05]), 2 SDVs (hazard ratio, 2.12 [95% CI, 1.28-3.50]), and 3+ SDVs (hazard ratio, 2.45 [95% CI, 1.48-4.04]) were significantly associated with incident HF hospitalization (P for trend, 0.001). We observed no significant associations for older individuals. CONCLUSIONS: A greater number of SDVs significantly increased risk of incident HF hospitalization among adults <65 years, which persisted after adjustment for cardiovascular risk factors. Using a simple SDV count that could be obtained from a social history during clinical assessment may identify younger individuals at increased risk.