Revisiting ethnic discrepancies in COVID-19 hospitalized cohorts: a correction for collider bias

Objectives: Studies from the first waves of the coronavirus disease 2019 (COVID-19) pandemic suggest that individuals from minority ethnicities are at an increased risk of worse outcomes. Concerns exist that this relationship is potentially driven by bias from analyzing hospitalized patients only. We investigate this relationship and the possible presence of bias.Study Design and Setting: Using data from South London hospitals across two COVID-19 waves (February 2020 -May 2021), the relationship between ethnicity and COVID-19 outcomes was examined using regression models. Three iterations of each model were completed: 1) an unadjusted analysis, 2) adjusting for covariates (medical history and deprivation), and 3) adjusting for covariates and bias induced by conditioning on hospitalization. Results: Among 3,133 patients, those who were Asian had a two-fold increased risk of death during the hospital stay that was consistent across the two COVID-19 waves and was not affected by correcting for conditioning on hospitalization. However, wave-specific effects demonstrate significant differences between ethnic groups until bias from using a hospitalized cohort was corrected for.Conclusion: Worsened COVID-19 outcomes in minority ethnicities may be minimized by correcting for bias induced by conditioning on hospitalization. Consideration of this bias should be a key component of study design. & COPY; 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Automated summary

Studies show that individuals from minority ethnicities face an increased risk of worse outcomes in the COVID-19 pandemic. There may be bias towards hospitalized patients. Research indicates that correcting for bias induced by conditioning on hospitalization may reduce adverse COVID-19 outcomes in minority ethnicities.