Joint Effects of Socioeconomic Position, Race/Ethnicity, and Gender on COVID-19 Mortality among Working-Age Adults in the United States

  1. Elizabeth B. Pathak
  2. Janelle M. Menard
  3. Rebecca B. Garcia
  4. Jason L. Salemi

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Abstract

Substantial racial/ethnic and gender disparities in COVID-19 mortality have been previously documented. However, few studies have investigated the impact of individual socioeconomic position (SEP) on these disparities. Objectives: To determine the joint effects of SEP, race/ethnicity, and gender on the burden of COVID-19 mortality. A secondary objective was to determine whether differences in opportunities for remote work were correlated with COVID-19 death rates for sociodemographic groups. Design: Annual mortality study which used a special government tabulation of 2020 COVID-19-related deaths stratified by decedents’ SEP (measured by educational attainment), gender, and race/ethnicity. Setting: United States in 2020. Participants: COVID-19 decedents aged 25 to 64 years old (n = 69,001). Exposures: Socioeconomic position (low, intermediate, and high), race/ethnicity (Hispanic, Black, Asian, Indigenous, multiracial, and non-Hispanic white), and gender (women and men). Detailed census data on occupations held by adults in 2020 in each of the 36 sociodemographic groups studied were used to quantify the possibility of remote work for each group. Main Outcomes and Measures: Age-adjusted COVID-19 death rates for 36 sociodemographic groups. Disparities were quantified by relative risks and 95% confidence intervals. High-SEP adults were the (low-risk) referent group for all relative risk calculations. Results: A higher proportion of Hispanics, Blacks, and Indigenous people were in a low SEP in 2020, compared with whites. COVID-19 mortality was five times higher for low vs. high-SEP adults (72.2 vs. 14.6 deaths per 100,000, RR = 4.94, 95% CI 4.82–5.05). The joint detriments of low SEP, Hispanic ethnicity, and male gender resulted in a COVID-19 death rate which was over 27 times higher (178.0 vs. 6.5 deaths/100,000, RR = 27.4, 95% CI 25.9–28.9) for low-SEP Hispanic men vs. high-SEP white women. In regression modeling, percent of the labor force in never remote jobs explained 72% of the variance in COVID-19 death rates. Conclusions and Relevance: SARS-CoV-2 infection control efforts should prioritize low-SEP adults (i.e., the working class), particularly the majority with “never remote” jobs characterized by inflexible and unsafe working conditions (i.e., blue collar, service, and retail sales workers).

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  1. Version published to 10.3390/ijerph19095479
  2. ScreenIT

    SciScore for 10.1101/2021.11.23.21266759: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableWe analyzed provisional death counts for 2020 stratifed by four sociodemographic variables: 1) educational attainment (no college, some college, college graduate); 2) race and ethnicity (white non-Hispanic, Hispanic, Black non-Hispanic, Asian non-Hispanic, American Indian/Alaska Native non-Hispanic, Native Hawaiian and other Pacific Islander non-Hispanic, more than one race non-Hispanic, unknown); 3) gender (male, female, unknown); and 4) age group (25-39 years, 40-54 years, 55-64 years).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Study Limitations and Public Health Data Gaps: It is likely that COVID-19 deaths in the U.S. have been undercounted (i.e., cause of death has been misclassified), and this misclassification is likely to be differential by social class, resulting in a bias toward the null in our estimates of social class disparities. Misclassification occurs when there is insufficient medical information available at the time of death. Lack of access to medical care and out-of-hospital mortality can result in the use of non-specific cause of death coding on death certificates. We have previously shown that the percent of all non-injury deaths coded to “symptoms, signs, and ill-defined conditions” increased from 2019 to 2020 among working age adults.50 A simple step toward improving COVID-19 surveillance data, which could be implemented immediately across a wide range of data systems, is to add one yes/no question to all individual adult patient encounter medical records: “Has this person completed one or more years of college?” A “no” response on this single data item would identify the working class. A follow-up question for those who replied “yes” (“Does this person have a 4-year college degree?”) would easily identify the three social classes analyzed in this study.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.11.23.21266759v1 on medRxiv