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.

Keywords: COVID-19; Coronavirus; Ethnicity; Health inequality; Inequality; Infectious disease; Pandemic; SARS-CoV-2; Social factors.

Fig. 1

Risk ratios for associations between broad ethnicity groups (white British as the reference category) and SARS-CoV-2. Model 1: age, sex and assessment centre. Model 2: model 1 + country of birth. Model 3: model 2 + healthcare worker. Model 4: model 3 + social variables (urbanicity, number of people per household, highest education level, deprivation, tenure status, employment status, manual work). Model 5: model 4 + health status variables (self-rated health, number of chronic conditions and longstanding illness) + behavioural risk factors (smoking, alcohol consumption and BMI). Coefficients for the Chinese and other groups are not shown

Fig. 2

Risk ratios for associations between narrow ethnicity groups (white British as the reference category) and SARS-CoV-2. Model 1: age, sex and assessment centre. Model 2: model 1 + country of birth. Model 3: model 2 + healthcare worker. Model 4: model 3 + social variables (urbanicity, number of people per household, highest education level, deprivation, tenure status, employment status, manual work). Model 5: model 4 + health status variables (self-rated health, number of chronic conditions and longstanding illness) + behavioural risk factors (smoking, alcohol consumption and BMI). Coefficients for the white Irish, white other, mixed, Chinese, black other and other groups are not shown

Fig. 3

Risk ratios for associations between Townsend deprivation score quartile (most advantaged as reference category) and SARS-CoV-2. Model 1: age, sex and assessment centre. Model 2: model 1 + ethnicity + country of birth. Model 3: model 2 + social variables (healthcare worker, urbanicity, number of people per household, highest education level, tenure status, employment status, manual work). Model 4: model 3 + health status variables (self-rated health, number of chronic conditions and longstanding illness) + behavioural risk factors (smoking, alcohol consumption and BMI)

Fig. 4

Risk ratios for associations between highest educational level (degree educated as reference category) and SARS-CoV-2. Model 1: age, sex and assessment centre. Model 2: model 1 + ethnicity + country of birth. Model 3: model 2 + social variables (healthcare worker, urbanicity, number of people per household, deprivation, tenure status, employment status, manual work). Model 4: model 3 + health status variables (self-rated health, number of chronic conditions and longstanding illness) + behavioural risk factors (smoking, alcohol consumption and BMI). Coefficient for the other groups are not shown