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Cited by 103COVID-19 epidemiological studiesCOVID-19 Clinical Research StudiesHealth disparities and outcomes

The DOI matches its Crossref record; 45 of the 46 references it cites were found in a registry or an index.

Social determinants of mortality from COVID-19: A simulation study using NHANES

Open access
Seligman, Benjamin, Ferranna, Maddalena, Bloom, David E.·2021·PLOS Medicine
DOI 10.1371/journal.pmed.1003490PMC PMC7799807
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Abstract

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.

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Crossref · 10.1371/journal.pmed.1003490

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Fig 1 Calibration of simulated distributions of deaths by age and gender against reported distributions from the CDC. Age (top); gender (bottom). Gray bars and whiskers show mean and 2.5th–97.5th percentile range for simulated proportions, the blue circles show the CDC-reported proportions, and the red triangles show the NHANES-estimated proportions for the general population. CDC, US Centers for Disease Control and Prevention; NHANES, National Health and Nutrition Examination Survey.
Fig 1 Calibration of simulated distributions of deaths by age and gender against reported distributions from the CDC. Age (top); gender (bottom). Gray bars and whiskers show mean and 2.5th–97.5th percentile range for simulated proportions, the blue circles show the CDC-reported proportions, and the red triangles show the NHANES-estimated proportions for the general population. CDC, US Centers for Disease Control and Prevention; NHANES, National Health and Nutrition Examination Survey.CC0 · PubMed Central
Fig 2 Simulated proportions of deaths by race/ethnicity, income, veteran status, and education level. Panels show mean and 2.5th–97.5th percentile range for the simulations (gray bars and whiskers), the CDC-reported proportions (blue circles, only for race/ethnicity), and the NHANES-estimated proportions for the general population (red triangles). AA, associate’s degree; GED, General Educational Development; NHANES, National Health and Nutrition Examination Survey.
Fig 2 Simulated proportions of deaths by race/ethnicity, income, veteran status, and education level. Panels show mean and 2.5th–97.5th percentile range for the simulations (gray bars and whiskers), the CDC-reported proportions (blue circles, only for race/ethnicity), and the NHANES-estimated proportions for the general population (red triangles). AA, associate’s degree; GED, General Educational Development; NHANES, National Health and Nutrition Examination Survey.CC0 · PubMed Central

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Citations

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Research works printed but not linked: 13

  1. Centers for Disease Control and Prevention, 2020, CDC COVID data tracker
  2. JE Vespa, 2020, Those who served: America’s veterans from world war ii to the war on terror
  3. Centers for Disease Control and Prevention, 2020, Provisional death counts for coronavirus disease 2019 (COVID-19)
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  6. Instituto de Salud Carlos III, 2020, Report no. 32. Situation of COVID-19 in Spain on 21 May 2020
  7. SARS-CoV-2 Surveillance Group, 2020, Characteristics of COVID-19 patients dying in Italy
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  13. E Brown, 2020, Which deaths count toward the covid-19 death toll? It depends on the state, The Washington Post

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Metadata

Authors
Seligman, B., Ferranna, M., & Bloom, D. E.
Affiliations
Harvard University (US)
Corresponding author
Seligman, Benjamin
ORCID
Venue
PLOS Medicine
Publisher
Public Library of Science (PLoS)
Published
2021-01-11
Volume
18
Issue
1
Pages
e1003490
ISSN
  • 1549-1277 (ISSN-L)
  • 1549-1676
DOI
10.1371/journal.pmed.1003490
PMC
PMC7799807
OpenAlex
W3119998633
Cited by
103
References
46
Citations by year
2026: 1 · 2025: 4 · 2024: 11 · 2023: 15 · 2022: 39 · 2021: 32
FWCI
9.36
Type
journal article
Language
en
Update notices
correction (2021-12-29)
Open access
Licence
Locations
  • PLoS Medicine (publishedVersion, public-domain)
  • Europe PMC (PubMed Central) (publishedVersion, public-domain)
  • PubMed Central (publishedVersion, public-domain)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • U.S. Department of Veterans Affairs
  • Bill and Melinda Gates Foundation (OPP1158136)
  • Harvard T.H. Chan School of Public Health
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Social Sciences › Health › Health disparities and outcomes
Keywords
COVID-19 mortality, social determinants of health, racial and ethnic disparities, income inequality, educational attainment, veteran status, comorbidities, health disparities, NHANES, health care access, public health measures, age and sex differences in mortality, health equity policy, health workforce diversity, health workforce shortage
MeSH terms
COVID-19, SARS-CoV-2, Aged, Ethnicity, Female, Health Services Needs and Demand, Humans, Male, Mortality, Public Health, Socioeconomic Factors, United States, Comorbidity, Healthcare Disparities, Veterans Health, Quality Improvement, Social Determinants of Health

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