Racial/Ethnic, Biomedical, and Sociodemographic Risk Factors for COVID-19 Positivity and Hospitalization in the San Francisco Bay Area

J Racial Ethn Health Disparities. 2023 Aug;10(4):1653-1668. doi: 10.1007/s40615-022-01351-1. Epub 2022 Jul 19.

Abstract

Background: The COVID-19 pandemic has uncovered clinically meaningful racial/ethnic disparities in COVID-19-related health outcomes. Current understanding of the basis for such an observation remains incomplete, with both biomedical and social/contextual variables proposed as potential factors.

Purpose: Using a logistic regression model, we examined the relative contributions of race/ethnicity, biomedical, and socioeconomic factors to COVID-19 test positivity and hospitalization rates in a large academic health care system in the San Francisco Bay Area prior to the advent of vaccination and other pharmaceutical interventions for COVID-19.

Results: Whereas socioeconomic factors, particularly those contributing to increased social vulnerability, were associated with test positivity for COVID-19, biomedical factors and disease co-morbidities were the major factors associated with increased risk of COVID-19 hospitalization. Hispanic individuals had a higher rate of COVID-19 positivity, while Asian persons had higher rates of COVID-19 hospitalization. The excess hospitalization risk attributed to Asian race was not explained by differences in the examined biomedical or sociodemographic variables. Diabetes was an important risk factor for COVID-19 hospitalization, particularly among Asian patients, for whom diabetes tended to be more frequently undiagnosed and higher in severity.

Conclusion: We observed that biomedical, racial/ethnic, and socioeconomic factors all contributed in varying but distinct ways to COVID-19 test positivity and hospitalization rates in a large, multi-racial, socioeconomically diverse metropolitan area of the United States. The impact of a number of these factors differed according to race/ethnicity. Improving overall COVID-19 health outcomes and addressing racial and ethnic disparities in COVID-19 outcomes will likely require a comprehensive approach that incorporates strategies that target both individual-specific and group contextual factors.

Keywords: Asian; COVID-19; Diabetes mellitus; Racial health disparities; Risk factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Asian / statistics & numerical data
  • COVID-19* / epidemiology
  • COVID-19* / ethnology
  • Hispanic or Latino / statistics & numerical data
  • Hospitalization
  • Humans
  • Pandemics / statistics & numerical data
  • Risk Factors
  • San Francisco / epidemiology
  • United States