Characteristics and Factors Associated With Coronavirus Disease 2019 Infection, Hospitalization, and Mortality Across Race and Ethnicity

  1. Chengzhen L Dai
  2. Sergey A Kornilov
  3. Ryan T Roper
  4. Hannah Cohen-Cline
  5. Kathleen Jade
  6. Brett Smith
  7. James R Heath
  8. George Diaz
  9. Jason D Goldman
  10. Andrew T Magis
  11. Jennifer J Hadlock

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Abstract

Background

Data on the characteristics of coronavirus disease 2019 (COVID-19) patients disaggregated by race/ethnicity remains limited. We evaluated the sociodemographic and clinical characteristics of patients across racial/ethnic groups and assessed their associations with COVID-19 outcomes.

Methods

This retrospective cohort study examined 629 953 patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a large health system spanning California, Oregon, and Washington between March 1 and December 31, 2020. Sociodemographic and clinical characteristics were obtained from electronic health records. Odds of SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital death were assessed with multivariate logistic regression.

Results

A total of 570 298 patients with known race/ethnicity were tested for SARS-CoV-2, of whom 27.8% were non-White minorities: 54 645 individuals tested positive, with minorities representing 50.1%. Hispanics represented 34.3% of infections but only 13.4% of tests. Although generally younger than White patients, Hispanics had higher rates of diabetes but fewer other comorbidities. A total of 8536 patients were hospitalized and 1246 died, of whom 56.1% and 54.4% were non-White, respectively. Racial/ethnic distributions of outcomes across the health system tracked with state-level statistics. Increased odds of testing positive and hospitalization were associated with all minority races/ethnicities. Hispanic patients also exhibited increased morbidity, and Hispanic race/ethnicity was associated with in-hospital mortality (odds ratio [OR], 1.39; 95% confidence interval [CI], 1.14–1.70).

Conclusion

Major healthcare disparities were evident, especially among Hispanics who tested positive at a higher rate, required excess hospitalization and mechanical ventilation, and had higher odds of in-hospital mortality despite younger age. Targeted, culturally responsive interventions and equitable vaccine development and distribution are needed to address the increased risk of poorer COVID-19 outcomes among minority populations.

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  1. Version published to 10.1093/cid/ciab154
  2. Version published to 10.1101/2020.10.14.20212803v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.10.14.20212803: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The protocol for this study was approved by the PSJH Institutional Review Board (IRB#: STUDY2020000203).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot 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:
    While the large size of this study’s diverse cohort and its multi-state distribution are strengths of this study, there are limitations. This study was limited to a single health system and certain catchment areas within California, Oregon, and Washington. Thus, the results may be less generalizable to other regions. In particular, the racial/ethnicity composition of COVID-19 patients in our study’s may not reflect those in other states and at the national level. For example, Black patients are underrepresented in our study when compared to national-level statistics. At the same time, electronic health records are subject to the quality, consistency, and completeness of entry by providers. Some patients may have also received care at other institutions and therefore certain outcomes or characteristics may be underreported. Our use of ICD-10-CM code may not capture diagnoses that are not billable or represented by a given code. Despite these limitations, however, our results highlight how the impact of COVID-19 vary across race/ethnicity in a large geographical area.

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.10.14.20212803v1 on medRxiv