Ethnic and socioeconomic differences in SARS-CoV-2 infection: prospective cohort study using UK Biobank

Abstract

Background: Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. Methods: The UK Biobank study recruited 40-70-year-olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including area-level socioeconomic deprivation and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health. Results: Amongst 392,116 participants in England, 2658 had been tested for SARS-CoV-2 and 948 tested positive (726 in hospital) between 16 March and 3 May 2020. Black and south Asian groups were more likely to test positive (RR 3.35 (95% CI 2.48-4.53) and RR 2.42 (95% CI 1.75-3.36) respectively), with Pakistani ethnicity at highest risk within the south Asian group (RR 3.24 (95% CI 1.73-6.07)). These ethnic groups were more likely to be hospital cases compared to the white British. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 2.19 for most deprived quartile vs least (95% CI 1.80-2.66) and RR 2.00 for no qualifications vs degree (95% CI 1.66-2.42)). Conclusions: Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study, which was not accounted for by differences in socioeconomic conditions, baseline self-reported health or behavioural risk factors. An urgent response to addressing these elevated risks is required.

Estimating Risk of Mechanical Ventilation and Mortality Among Adult COVID-19 patients Admitted to Mass General Brigham: The VICE and DICE Scores

“…We also observed that the factors used to construct each risk score were different, demonstrating that it is beneficial to consider risks of ventilation need and mortality separately. Interestingly, and in contrast to previous reports, we did not observe worse outcomes in COVID-19 patients from minority ethnic backgrounds [10][11][12][13] In fact, we actually presented data suggesting worse mortality rates in white patients, even when removing patients with a DNI status. However, we found no difference in outcomes after adjusting for individual DICE scores.…”

“…Previous reports have highlighted a marked increase in risk of developing severe illness in COVID-19 in Asians and African Americans. [10][11][12][13] We found it interesting, therefore, that we did not observe this in our univariate analyses (Table 1), with the data even pointing to worse mortality rates in white patients. We therefore investigated if patients from white backgrounds were in poorer health on admission to hospital by analyzing their DICE scores.…”

Racial/Ethnic Disparities in Hospital Admissions from COVID-19 and Determining the Impact of Neighborhood Deprivation and Primary Language

“…Both U.K. studies assessed COVID-19 patients and found that Black andAsian patients were at an increased odds of hospitalization. Similar to our findings, after controlling for areas of deprivation and comorbidities, the risk for racial and ethnic minority patients persisted (21,22).…”

“…median income, number of dependents, % with complete plumbing) , and employment status. ADI (20) and other indices (21)(22)(23) have been used to estimate the effects of these socioeconomic variables in aggregate on outcomes, including in COVID-19.…”

„Health in All Policies“ und gesundheitliche Chancengleichheit: COVID-19 als Fallstudie

“…Erste empirische Befunde legen nahe, dass dieser Effekt auch bei COVID-19 aufgetreten ist [5][6][7]. Studien aus Großbritannien berichten beispielsweise von höheren Infektionsraten bei Menschen mit niedriger Bildung [8] und von höheren COVID-19 Hospitalisierungsraten bei Menschen mit geringem Einkommen [9]. Hinzu kommt, dass auch die indirekten gesundheitlichen Folgen der Maßnahmen des Infektionsschutzes sozial ungleich verteilt sein dürften [10].…”