tetano
Editor, Senior Moderator
J Clin Epidemiol
. 2023 Jun 27;S0895-4356(23)00161-0.
doi: 10.1016/j.jclinepi.2023.06.014. Online ahead of print. Revisiting ethnic discrepancies in Covid-19 hospitalised cohorts: a correction for collider bias
Annastazia E Learoyd[SUP] 1 [/SUP], Jennifer Nicholas[SUP] 2 [/SUP], Nicholas Hart[SUP] 3 [/SUP], Abdel Douiri[SUP] 4 [/SUP]
Affiliations
Objective: 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 potential driven by bias from analysing hospitalised 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 were examined using regression models. Three iterations of each model were completed: 1) an unadjusted analysis, 2) adjusting for covariates (medical history and deprivation), 3) adjusting for covariates and bias induced by conditioning on hospitalisation.
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 hospitalisation. However, wave-specific effects demonstrate significant differences between ethnic groups until bias from using a hospitalised cohort was corrected for.
Conclusion: Worsened Covid-19 outcomes in minority ethnicities may be minimised by correcting for bias induced by conditioning on hospitalisation. Consideration of this bias should be a key component of study design.
Keywords: Collider bias; Covid-19; Epidemiology; Ethnicity; Inequalities; Statistical methods.
. 2023 Jun 27;S0895-4356(23)00161-0.
doi: 10.1016/j.jclinepi.2023.06.014. Online ahead of print. Revisiting ethnic discrepancies in Covid-19 hospitalised cohorts: a correction for collider bias
Annastazia E Learoyd[SUP] 1 [/SUP], Jennifer Nicholas[SUP] 2 [/SUP], Nicholas Hart[SUP] 3 [/SUP], Abdel Douiri[SUP] 4 [/SUP]
Affiliations
- PMID: 37385305
- DOI: 10.1016/j.jclinepi.2023.06.014
Objective: 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 potential driven by bias from analysing hospitalised 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 were examined using regression models. Three iterations of each model were completed: 1) an unadjusted analysis, 2) adjusting for covariates (medical history and deprivation), 3) adjusting for covariates and bias induced by conditioning on hospitalisation.
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 hospitalisation. However, wave-specific effects demonstrate significant differences between ethnic groups until bias from using a hospitalised cohort was corrected for.
Conclusion: Worsened Covid-19 outcomes in minority ethnicities may be minimised by correcting for bias induced by conditioning on hospitalisation. Consideration of this bias should be a key component of study design.
Keywords: Collider bias; Covid-19; Epidemiology; Ethnicity; Inequalities; Statistical methods.