Abstract 11652: The Addition of Social Determinants of Health to Coronary Heart Disease Risk Prediction

Abstract

Introduction: Coronary heart disease (CHD) remains a leading cause of death worldwide, with an unequal distribution of this burden placed on individuals of lower socioeconomic status. Individual social determinants of health (SDoH) have been shown to be associated with CHD; however, whether the addition of SDoH can improve current CHD risk prediction algorithms has not been delineated. Hypothesis: We hypothesize that the addition of SDoH to the Multi-Ethnic Study of Atherosclerosis (MESA) risk score improves the prediction of 10-year CHD events. Methods: In 6,286 individuals from the MESA cohort, we evaluated the additional predictive value of SDoH beyond the traditional factors included in the existing MESA Risk Score. SDoH considered were employment, family income, house tenure, financial strain, education, marital status, social support, chronic stress, discrimination, neighborhood characteristics, healthcare access, and health insurance, which were organized into five composite domains. A penalized Cox proportional hazards model was used to select SDoH variables with the potential to improve prediction, then an unpenalized Cox regression model was fitted with traditional risk factors plus the selected SDoH variables. Results: Statistically significant differences in the distribution of SDoH were observed between racial and ethnic groups. Notably, unfavorable SDoH were concentrated in Black and Hispanic/Latino persons. Economic stability, education, and community and social context were associated with CHD events. The area under the curve (AUC) for prediction of a 10-year CHD event was 0.816 without SDoH factors and 0.818 with the addition of SDoH. Conclusions: Racial and ethnic differences in social determinants of health were obsserved. Economic stability, education, and community and social context were significantly associated with cardiovascular events, however the addition of SDoH did not significantly improve CHD risk prediction.