Ethnic disparities in hospitalisation for COVID-19 in England: The role of socioeconomic factors, mental health, and inflammatory and pro-inflammatory factors in a community-based cohort study

Abstract

Background: Differentials in COVID-19 hospitalisations and mortality according to ethnicity have been reported but their origin is uncertain. We examined the role of socioeconomic, mental health, and pro-inflammatory factors in a community-based sample.

Methods: We used data on 340,966 men and women (mean age 56.2 years) from the UK Biobank study, a prospective cohort study with linkage to hospitalisation for COVID-19. Logistic regression models were used to estimate associations between ethnicity and hospitalisation for COVID-19.

Results: There were 640 COVID-19 cases (571/324,306 White, 31/4,485 Black, 21/5,732 Asian, 17/5,803 Other). Compared to the White study members and after adjusting for age and sex, Black individuals had over a 4-fold increased risk of COVID-19 infection (odds ratio; 95% confidence interval: 4.32; 3.00-6.23), and there was a doubling of risk in the Asian group (2.12; 1.37, 3.28) and the 'other' non-white group (1.84; 1.13, 2.99). After controlling for potential explanatory factors which included neighbourhood deprivation, household crowding, smoking, body size, inflammation, glycated haemoglobin, and mental illness, these effect estimates were attenuated by 33% for Blacks, 52% for Asians and 43% for Other, but remained raised for Blacks (2.66; 1.82, 3.91), Asian (1.43; 0.91, 2.26) and other non-white groups (1.41; 0.87, 2.31).

Conclusions: There were clear ethnic differences in risk of COVID-19 hospitalisation and these do not appear to be fully explained by measured factors. If replicated, our results have implications for health policy, including the targeting of prevention advice and vaccination coverage.

Keywords: COVID-19; Ethnicity; Inflammatory factors.

Fig. 1

Association between ethnicity and hospitalisation for COVID-19 in UK Biobank (640 cases / 340,966 people at risk). Covariates included in each model. (1) Biomarkers: age, sex, log-CRP, log-HbA1c and total cholesterol. (2) Comorbidities: age, sex, cardiovascular disease, hypertension, diabetes, chronic bronchitis, body mass index and wait to hip ratio. (3) Lifestyle: age, sex, alcohol intake, physical activity, smoking. (4) Socioeconomic status: age, sex, Townsend deprivation index, education, number in household. (5) All: age, sex, Townsend deprivation index, education, number in household, alcohol intake, physical activity, smoking, cardiovascular disease, hypertension, chronic bronchitis, body mass index and wait to hip ratio, log-CRP, log-HbA1c, total cholesterol. Attenuation of coefficients was as follows: Black 1) −14.1%, 2) −9.6%, 3) −6.3%, 4) −24.4%, 5) –33.0%; Asian: 1) −28.7%, 2) −9.2%, 3) −14.1%, 4) –32.9%, 5) −52.2%; Others 1) −13.9%, 2) −3.4%, 3) −20.2%, 4) −30.0%, 5) −43.0%.