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Characteristics and Factors Associated with COVID-19 Infection, Hospitalization, and Mortality Across Race and Ethnicity

Our take —

This cohort study compared the likelihood SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital mortality by race and ethnicity among 629,953 individuals tested for SARS-CoV-2 from March 1 to December 31, 2020 in a large health system on the West coast of the United States. Unsurprisingly, they found higher odds of SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital mortality in individuals who identified as members of historically marginalized racial and ethnic groups. While their analysis was not able to control for individual-level social determinants of health that may have blunted the relationship between race/ethnicity and adverse outcomes, it provides further evidence that the United States has a tremendous amount of work to do to address systemic and structural inequities that continue to result in persistent racial and ethnic disparities in health outcomes.

Study design

Retrospective Cohort

Study population and setting

This cohort study included 629,953 individuals who were tested for SARS-CoV-2 between March 1 and December 31, 2020 at Providence St. Joseph Health facilities in California, Oregon, and Washington state in the United States. The authors collected data from electronic medical records on participants’ age, sex, race, ethnicity, insurance, zip code, underlying medical conditions (by ICD-10-CM codes from January 1, 2019 to date of testing), Charlson Comorbidity Index, and body mass index. If participants were admitted to the hospital, authors also collected the participants’ presenting vital signs, laboratory results, supplemental oxygen use, hospital diagnoses, length of say, intensive care unit transfer, and disposition at discharge. Participants with more than one SARS-CoV-2 test during the study period were followed until their first positive test. Authors assessed demographic and clinical characteristics by participant race/ethnicity as well as the relationship between race/ethnicity and SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital mortality (through January 31, 2021) using a mixed-effects logistic regression model including random intercepts for each state and SARS-CoV-2 test month. Multiple imputation was conducted for covariates with less than 20% missingness.

Summary of Main Findings

Of the 49,081 (8.6%) individuals with a known race/ethnicity (n = 570,298) who tested positive for SARS-CoV-2, participants who identified as Hispanic (34.3% vs. 13.4%) or Native Hawaiians/Pacific Islanders (1.4% vs. 0.6%) were the most likely to test positive as compared to their likelihood of being tested. Among participants hospitalized with COVID-19, white participants were older and had higher Charlson Comorbidity Indices, but were less likely to have diabetes, hypertension, asthma, kidney disease, and obesity compared to those who identified as Hispanic, Black, Asian, Native Hawaiian/Pacific Islanders, or American Indians/Alaska Natives. After controlling for clinical characteristics, health insurance status, and zip code-derived neighborhood characteristics (median income, crowded housing, English proficiency), patients who identified as members of marginalized communities were more likely to test positive for SARS-CoV-2, be hospitalized with COVID-19, and, in the case of Hispanic participants, die in the hospital from COVID-19 when compared to white participants.

Study Strengths

This large cohort study from a large health system on the west coast of the United States presents SARS-CoV-2 infection data by race/ethnicity that aligns with State-level data, suggesting that the findings are likely generalizable to the region.

Limitations

The authors correctly note that these results are not causal and instead reflect underlying structural forces that likely drive COVID-19-related health inequities. Since they collected data through electronic medical records, information on other potential risk factors for COVID-19, such as occupation, or individual-level data on experienced discrimation or other sequelae of systemic racism in the United States were not included. Although they used zip code-derived neighborhood characteristics in their model, their random effects accounted for state-level, rather than zip code-level interdependence, which may have led to artificially narrow confidence intervals, overestimating the precision and significance of their estimates. Electronic medical record data are also prone to misclassification (for example, missed comorbidities) and, although they allowed for age to be non-linear in their final model, they categorized other linear covariates (body mass index and laboratory values), which complicates effect estimate interpretation and makes some dubious assumptions. Finally, approximately 9.4% of participants had missing race/ethnicity data.

Value added

This large study provides further evidence that individuals who belong to racial and ethinic groups that have been historically marginalized in the United States were disproportionately impacted by the COVID-19 pandemic.

This review was posted on: 26 March 2021