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

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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.

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Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Fei Zhou, Ting Yu, Ronghui Du … (2020)

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

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Demographic science aids in understanding the spread and fatality rates of COVID-19

Jennifer Dowd, Liliana Andriano, David M. Brazel … (2020)

Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.

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Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis

Robert W Aldridge, Alistair Story, Stephen Hwang … (2018)

Summary Background Inclusion health focuses on people in extremely poor health due to poverty, marginalisation, and multimorbidity. We aimed to review morbidity and mortality data on four overlapping populations who experience considerable social exclusion: homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals. Methods For this systematic review and meta-analysis, we searched MEDLINE, Embase, and the Cochrane Library for studies published between Jan 1, 2005, and Oct 1, 2015. We included only systematic reviews, meta-analyses, interventional studies, and observational studies that had morbidity and mortality outcomes, were published in English, from high-income countries, and were done in populations with a history of homelessness, imprisonment, sex work, or substance use disorder (excluding cannabis and alcohol use). Studies with only perinatal outcomes and studies of individuals with a specific health condition or those recruited from intensive care or high dependency hospital units were excluded. We screened studies using systematic review software and extracted data from published reports. Primary outcomes were measures of morbidity (prevalence or incidence) and mortality (standardised mortality ratios [SMRs] and mortality rates). Summary estimates were calculated using a random effects model. Findings Our search identified 7946 articles, of which 337 studies were included for analysis. All-cause standardised mortality ratios were significantly increased in 91 (99%) of 92 extracted datapoints and were 11·86 (95% CI 10·42–13·30; I 2=94·1%) in female individuals and 7·88 (7·03–8·74; I 2=99·1%) in men. Summary SMR estimates for the International Classification of Diseases disease categories with two or more included datapoints were highest for deaths due to injury, poisoning, and other external causes, in both men (7·89; 95% CI 6·40–9·37; I 2=98·1%) and women (18·72; 13·73–23·71; I 2=91·5%). Disease prevalence was consistently raised across the following categories: infections (eg, highest reported was 90% for hepatitis C, 67 [65%] of 103 individuals for hepatitis B, and 133 [51%] of 263 individuals for latent tuberculosis infection), mental health (eg, highest reported was 9 [4%] of 227 individuals for schizophrenia), cardiovascular conditions (eg, highest reported was 32 [13%] of 247 individuals for coronary heart disease), and respiratory conditions (eg, highest reported was 9 [26%] of 35 individuals for asthma). Interpretation Our study shows that homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals experience extreme health inequities across a wide range of health conditions, with the relative effect of exclusion being greater in female individuals than male individuals. The high heterogeneity between studies should be explored further using improved data collection in population subgroups. The extreme health inequity identified demands intensive cross-sectoral policy and service action to prevent exclusion and improve health outcomes in individuals who are already marginalised. Funding Wellcome Trust, National Institute for Health Research, NHS England, NHS Research Scotland Scottish Senior Clinical Fellowship, Medical Research Council, Chief Scientist Office, and the Central and North West London NHS Trust.

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Author and article information

Contributors

S. Vittal Katikireddi:

ORCID: http://orcid.org/0000-0001-6593-9092

vittal.katikireddi@glasgow.ac.uk

Journal

Journal ID (nlm-ta): BMC Med

Journal ID (iso-abbrev): BMC Med

Title: BMC Medicine

Publisher: BioMed Central (London )

ISSN (Electronic): 1741-7015

Publication date (Electronic): 29 May 2020

Publication date PMC-release: 29 May 2020

Publication date Collection: 2020

Volume: 18

Electronic Location Identifier: 160

Affiliations

[1 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, Institute of Health & Wellbeing, College of Medical, Veterinary and Life Sciences, , University of Glasgow, ; Glasgow, G12 8RZ UK

[2 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, General Practice and Primary Care, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, , University of Glasgow, ; 1 Horselethill Road, Glasgow, G12 9LX UK

[3 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, MRC/CSO Social & Public Health Sciences Unit, , University of Glasgow, ; Top floor, 200 Renfield Street, Glasgow, G2 3QB UK

[4 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, , University of Glasgow, ; Glasgow, G12 8TA UK

[5 ]Public Health Scotland, Meridian Court, 5 Cadogan Street, Glasgow, G2 6QE UK

Author information

S. Vittal Katikireddi http://orcid.org/0000-0001-6593-9092

Article

Publisher ID: 1640

DOI: 10.1186/s12916-020-01640-8

PMC ID: 7255908

PubMed ID: 32466757

SO-VID: 3f7bcf68-c362-4945-9dc7-2c780c471b0c

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Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 24 April 2020

Date accepted : 18 May 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;

Award ID: MC_UU_12017/13

Award ID: MR/R024774/1

Award Recipient : Claire L. Niedzwiedz

Funded by: FundRef http://dx.doi.org/10.13039/501100000589, Chief Scientist Office;

Award ID: SCAF/15/02

Award ID: SPHSU13

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ScienceOpen disciplines: Medicine

Keywords: ethnicity,inequality,coronavirus,covid-19,sars-cov-2,health inequality,infectious disease,social factors,pandemic

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ScienceOpen disciplines: Medicine

Keywords: ethnicity, inequality, coronavirus, covid-19, sars-cov-2, health inequality, infectious disease, social factors, pandemic

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

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Most cited references 16

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Demographic science aids in understanding the spread and fatality rates of COVID-19

Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis

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