The Power of Social Determinants of Health: An Avenue for Eliminating Race-Based Cardiovascular Disease Risk Estimation

Abstract In 2000, social determinants of health (SDOH), including education, racial segregation, social support, poverty and income inequality, were linked to over 800,000 deaths in the United States. Moreover, prior studies have shown that SDOH explain more of the current disparity in cardiovascular mortality than traditional atherosclerotic cardiovascular disease (ASCVD) risk factors. However, current ASCVD risk prediction tools, like the 2013 pooled cohort equations (PCE), comprised of separate equations for white and Black men and women, do not incorporate SDOH. This project will analyze ASCVD risk attributable to SDOH and structural racism, defined as the macrolevel systems, social forces, institutions, ideologies, and processes that interact to generate and reinforce inequities among racial and ethnic groups. Clinical practice guidelines recommend using the PCE for ASCVD risk estimation. However, these equations are inadequate because: (1) individuals of Hispanic ethnicity were not included in the derivation cohort, so the results are not directly applicable to Hispanic individuals; and (2) self-identified race is a social construct and a proxy for the lived experience of structural racism. Incorporating SDOH into ASCVD risk prediction models could eliminate the need for race- specific risk equations while capturing the effect of racism on ASCVD risk. The goal of this study is to establish ASCVD risk estimators reflecting the impact of SDOH. We will create sex-specific equations with race and ethnicity as covariates (rather than as stratification variables), robustly adjusting for traditional ASCVD risk factors as well as SDOH. These alterations have the potential to increase statistical power while eliminating race-stratified risk estimation. In this project, we will leverage several existing NHLBI-funded cohort studies to build an ethnically and socioeconomically diverse sample by incorporating data from the Generation 3 and Omni 2 cohorts of the Framingham Heart Study, Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, Hispanic Community Health Study, and Coronary Artery Risk Development in Young Adults Study. Our overarching hypothesis is that, upon robust adjustment for SDOH, the effects of race and ethnicity on ASCVD risk will be attenuated, obviating the need for considering race in ASCVD risk assessment. To investigate this hypothesis, we will: identify SDOH variables that reflect the impact of structural racism using structural equation modeling (Aim 1); develop sex-specific ASCVD risk estimating equations, adjusting for race, ethnicity, traditional ASCVD risk factors, and SDOH using Cox proportional hazards regression (Aim 2); and internally validate ASCVD risk prediction models (Aim 3). Successful completion of this project would pave the way for integrating a risk estimator into electronic health records for broad use in clinical settings, allowing for earlier and more robust prevention measures – potentially preventing millions of ASCVD events and resulting in reduced healthcare expenditure.