Cardiometabolic Disease Severity, Social Determinants of Health and Poor COVID-19 Outcomes

ABSTRACT

Background: Social determinants of health (SDoH) contribute to disparities in obesity and diabetes yet relative contributions of SDoH and cardiometabolic disease on COVID-19 outcomes are unknown. We sought to determine the ability of SDoH and cardiometabolic disease staging (CMDS) data to predict subsequent COVID-19 outcomes, and to investigate the degree to which adding SDoH to the clinical CMDS improved prediction accuracy. Methods: Individual and neighborhood level SDoH and cardiometabolic disease staging (CMDS) data [BMI, glucose, blood pressure, HDL, triglycerides], collected at a medical encounter prior to a positive COVID-19 test, were extracted from the electronic medical record (EMR) at an academic medical center in the Southeastern US. We used Bayesian logistic regression to model each COVID-19 outcome [hospitalization, intensive care unit (ICU) admission, and mortality] using CMDS components, individual and neighborhood SDoH, controlling for age, race and gender. Models were cross-validated and areas under the curve (AUC) were compared using Delongs test. Results: A total of 2,873 patients were identified [mean age 58 years (SD 13.2), 59% female, 45% non-Hispanic Black]. CMDS score, insurance status, male sex and higher glucose values were associated with increased odds of all outcomes;area level social vulnerability was associated with increased odds of hospitalization [odds ratio (OR) 1.84, 95% confidence interval (CI) 1.38-2.45] and ICU admission [OR 1.98, 95 % CI 1.45-2.85]. AUCs improved when SDoH were added to CMDS (p<0.001) hospitalization (AUC 0.78 vs. 0.82);ICU admission (AUC 0.77 vs. 0.81);and mortality (AUC 0.77 vs. 0.83). Conclusions: Clinical markers of cardiometabolic disease and SDoH, collected up to 3 years in advance of COVID-19 infection, were independently highly predictive of subsequent COVID-19 outcomes in our population. Both clinical and SDoH factors should be utilized to identify individuals at high risk for poor outcomes.