Background The COVID-19 epidemic in the United States is widespread, with more than 200,000 deaths reported as of September 23, 2020. While ecological studies show higher burdens of COVID-19 mortality in areas with higher rates of poverty, little is known about social determinants of COVID-19 mortality at the individual level. Methods and findings We estimated the proportions of COVID-19 deaths by age, sex, race/ethnicity, and comorbid conditions using their reported univariate proportions among COVID-19 deaths and correlations among these variables in the general population from the 2017–2018 National Health and Nutrition Examination Survey (NHANES). We used these proportions to randomly sample individuals from NHANES. We analyzed the distributions of COVID-19 deaths by race/ethnicity, income, education level, and veteran status. We analyzed the association of these characteristics with mortality by logistic regression. Summary demographics of deaths include mean age 71.6 years, 45.9% female, and 45.1% non-Hispanic white. We found that disproportionate deaths occurred among individuals with nonwhite race/ethnicity (54.8% of deaths, 95% CI 49.0%–59.6%, p < 0.001), individuals with income below the median (67.5%, 95% CI 63.4%–71.5%, p < 0.001), individuals with less than a high school level of education (25.6%, 95% CI 23.4% –27.9%, p < 0.001), and veterans (19.5%, 95% CI 15.8%–23.4%, p < 0.001). Except for veteran status, these characteristics are significantly associated with COVID-19 mortality in multiple logistic regression. Limitations include the lack of institutionalized people in the sample (e.g., nursing home residents and incarcerated persons), the need to use comorbidity data collected from outside the US, and the assumption of the same correlations among variables for the noninstitutionalized population and COVID-19 decedents. Conclusions Substantial inequalities in COVID-19 mortality are likely, with disproportionate burdens falling on those who are of racial/ethnic minorities, are poor, have less education, and are veterans. Healthcare systems must ensure adequate access to these groups. Public health measures should specifically reach these groups, and data on social determinants should be systematically collected from people with COVID-19. In this simulation study, Benjamin Seligman and colleagues explore socio-demographic factors associated with COVID-19 deaths in the US. Author summary Why was this study done? The COVID-19 epidemic in the United States of America (US) has been found to disproportionally affect racial/ethnic minorities and areas with higher concentrations of poverty. Few data on COVID-19 deaths with respect to individual-level social determinants of health other than race/ethnicity are available. What did the researchers do and find? We used the 2017–2018 National Health and Nutrition Examination Survey (NHANES) and publicly reported data on COVID-19 deaths from the public health agencies of the US, China, the United Kingdom, Spain, Italy, and France to simulate COVID-19 deaths among noninstitutionalized (e.g., not residing in a prison or nursing home) adults aged 20 years or older in the US. We found large social gradients in COVID-19 mortality. Adults from households earning less than the median income made up two-thirds of COVID-19 deaths, while those with less than a high school education accounted for approximately 1 in 4 deaths. Veterans also accounted for nearly 1 in 5 deaths, despite representing less than one-tenth of the population. Our simulation reproduced known racial/ethnic disparities in COVID-19 mortality. What do these findings mean? The associations between social determinants of health and COVID-19 mortality are similar in scale to those between hypertension and diabetes and COVID-19 mortality. COVID-19 mitigation will require measures to support people from low-income, low-education communities and the healthcare systems that serve them.
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