National Population-Level Disparities in COVID-19 Mortality Across the Intersection of Race/Ethnicity and Sex in the United States

  1. Jay J. Xu
  2. Jarvis T. Chen
  3. Thomas R. Belin
  4. Ronald S. Brookmeyer
  5. Marc A. Suchard
  6. Christina M. Ramirez

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Abstract

Males and certain racial/ethnic minority groups have borne a disproportionate burden of COVID-19 mortality in the United States, and substantial scientific research has sought to quantify and characterize population-level disparities in COVID-19 mortality outcomes by sex and across categories of race/ethnicity. However, there has not yet been a national population-level study to quantify disparities in COVID-19 mortality outcomes across the intersection of these demographic dimensions. Here, we analyze a publicly available dataset from the National Center for Health Statistics comprising COVID-19 death counts stratified by race/ethnicity, sex, and age for the year 2020, calculating mortality rates for each race/ethnicity-sex-age stratum and age-adjusted mortality rates for each race/ethnicity-sex stratum, quantifying disparities in terms of mortality rate ratios and rate differences. Our results reveal persistently higher COVID-19 age-adjusted mortality rates for males compared to females within every racial/ethnic group, with notable variation in the magnitudes of the sex disparity by race/ethnicity. However, non-Hispanic Black, Hispanic, and non-Hispanic American Indian or Alaska Native females have higher age-adjusted mortality rates than non-Hispanic White and non-Hispanic Asian/Pacific Islander males. Moreover, persistent racial/ethnic disparities are observed among both males and females, with higher COVID-19 age-adjusted mortality rates observed for non-Hispanic Blacks, Hispanics, and non-Hispanic American Indian or Alaska Natives relative to non-Hispanic Whites.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.29.21262775: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableThe sex categories are male and female, and the following 7 racial/ethnic groups are recorded: non-Hispanic White (NH White), non-Hispanic Black (NH Black), Hispanic, non-Hispanic Asian (NH Asian), non-Hispanic American Indian or Alaska Native (NH AIAN), non-Hispanic Native Hawaiian or Other Pacific Islander (NH NHOPI), and Unknown.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    The sex categories are male and female, and the following 7 racial/ethnic groups are recorded: non-Hispanic White (NH White), non-Hispanic Black (NH Black), Hispanic, non-Hispanic Asian (NH Asian), non-Hispanic American Indian or Alaska Native (NH AIAN), non-Hispanic Native Hawaiian or Other Pacific Islander (NH NHOPI), and Unknown.
    non-Hispanic White
    suggested: None

    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:
    This study highlights some of the limitations of previous analyses quantifying population-level disparities that relied on public datasets reporting limited socio-demographic characteristics associated with COVID-19 outcomes. Such low-dimensional data inherently limits our ability to understand of the nature of disparities in COVID-19 outcomes between population subgroups and does little to inform how such disparities might be reduced or eliminated. Sophisticated disparities research is only possible with COVID-19 data disaggregated by multiple key variables, but such publicly available datasets in the U.S. have been and continue to be limited. Examples of stratifying variables of practical interest include but are not limited to race/ethnicity, sex, age, educational attainment, occupation, income, religious affiliation, household composition, underlying medical conditions, and geographical residence. We urge U.S. federal, state, and local governmental and health authorities to prioritize the public availability of accurate, detailed, and real-time multi-dimensional data on socially-relevant patient/decedent characteristics associated with COVID-19 outcomes to facilitate research illuminating health disparities between population subgroups so that they can be addressed.

    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.
    • No protocol registration statement was detected.

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

    About SciScore

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  2. Version published to 10.1101/2021.08.29.21262775v1 on medRxiv