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10.1371/journal.pmed.1003490

http://scihub22266oqcxt.onion/10.1371/journal.pmed.1003490
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33428624!7799807!33428624
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suck abstract from ncbi


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pmid33428624      PLoS+Med 2021 ; 18 (1): e1003490
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  • Social determinants of mortality from COVID-19: A simulation study using NHANES #MMPMID33428624
  • Seligman B; Ferranna M; Bloom DE
  • PLoS Med 2021[Jan]; 18 (1): e1003490 PMID33428624show ga
  • 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.
  • |*Public Health/methods/standards[MESH]
  • |*Socioeconomic Factors[MESH]
  • |Aged[MESH]
  • |COVID-19/*mortality[MESH]
  • |Comorbidity[MESH]
  • |Ethnicity/statistics & numerical data[MESH]
  • |Female[MESH]
  • |Health Services Needs and Demand[MESH]
  • |Healthcare Disparities/*standards[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Mortality[MESH]
  • |Quality Improvement/organization & administration[MESH]
  • |SARS-CoV-2/isolation & purification[MESH]
  • |Social Determinants of Health/*statistics & numerical data[MESH]
  • |United States[MESH]


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