Disaggregating Asian Race Reveals COVID-19 Disparities Among Asian American Patients at New York City’s Public Hospital System

  1. Roopa Kalyanaraman Marcello
  2. Johanna Dolle
  3. Areeba Tariq
  4. Sharanjit Kaur
  5. Linda Wong
  6. Joan Curcio
  7. Rosy Thachil
  8. Stella S. Yi
  9. Nadia Islam

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Abstract

Data on the health burden of COVID-19 among Asian American people of various ethnic subgroups remain limited. We examined COVID-19 outcomes of people of various Asian ethnic subgroups and other racial and ethnic groups in an urban safety net hospital system.

Methods:

We conducted a retrospective analysis of 85 328 adults aged ≥18 tested for COVID-19 at New York City’s public hospital system from March 1 through May 31, 2020. We examined COVID-19 positivity, hospitalization, and mortality, as well as demographic characteristics and comorbidities known to worsen COVID-19 outcomes. We conducted adjusted multivariable regression analyses examining racial and ethnic disparities in mortality.

Results:

Of 9971 Asian patients (11.7% of patients overall), 48.2% were South Asian, 22.2% were Chinese, and 29.6% were in other Asian ethnic groups. South Asian patients had the highest rates of COVID-19 positivity (30.8%) and hospitalization (51.6%) among Asian patients, second overall only to Hispanic (32.1% and 45.8%, respectively) and non-Hispanic Black (27.5% and 57.5%, respectively) patients. Chinese patients had a mortality rate of 35.7%, highest of all racial and ethnic groups. After adjusting for demographic characteristics and comorbidities, only Chinese patients had significantly higher odds of mortality than non-Hispanic White patients (odds ratio = 1.44; 95% CI, 1.04-2.01).

Conclusions:

Asian American people, particularly those of South Asian and Chinese descent, bear a substantial and disproportionate health burden of COVID-19. These findings underscore the need for improved data collection and reporting and public health efforts to mitigate disparities in COVID-19 morbidity and mortality among these groups.

Article activity feed

  1. Version published to 10.1177/00333549211061313
  2. Rapid Reviews Infectious Diseases

    Ken Teoh

    Review 2: "Disaggregating Asian Race Reveals COVID-19 Disparities among Asian Americans at New York City's Public Hospital System"

    This potentially informative paper shows higher positivity rates/mortality in Asians and Asian sub-populations than other races.The reviewers also suggest some limitations of methods and findings, which contrast with other literature.

  3. Rapid Reviews Infectious Diseases

    Emanuela Taioli

    Review 1: "Disaggregating Asian Race Reveals COVID-19 Disparities among Asian Americans at New York City's Public Hospital System"

    This potentially informative paper shows higher positivity rates/mortality in Asians and Asian sub-populations than other races.The reviewers also suggest some limitations of methods and findings, which contrast with other literature.

  5. ScreenIT

    SciScore for 10.1101/2020.11.23.20233155: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Biomedical Research Alliance of New York Institutional Review Board.
    Consent: Informed consent was not required because of the retrospective nature of this study.
    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

  6. Version published to 10.1101/2020.11.23.20233155v1 on medRxiv