Modifiable and non-modifiable risk factors for COVID-19, and comparison to risk factors for influenza and pneumonia: results from a UK Biobank prospective cohort study

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Abstract

Objectives

We aimed to investigate demographic, lifestyle, socioeconomic and clinical risk factors for COVID-19, and compared them to risk factors for pneumonia and influenza in UK Biobank.

Design

Cohort study.

Setting

UK Biobank.

Participants

49–83 year olds (in 2020) from a general population study.

Main outcome measures

Confirmed COVID-19 infection (positive SARS-CoV-2 test). Incident influenza and pneumonia were obtained from primary care data. Poisson regression was used to study the association of exposure variables with outcomes.

Results

Among 235 928 participants, 397 had confirmed COVID-19. After multivariable adjustment, modifiable risk factors were higher body mass index and higher glycated haemoglobin (HbA1C) (RR 1.28 and RR 1.14 per SD increase, respectively), smoking (RR 1.39), slow walking pace as a proxy for physical fitness (RR 1.53), and use of blood pressure medications as a proxy for hypertension (RR 1.33). Higher forced expiratory volume in 1 s (FEV1) and high-density lipoprotein (HDL) cholesterol were both associated with lower risk (RR 0.84 and RR 0.83 per SD increase, respectively). Non-modifiable risk factors included male sex (RR 1.72), black ethnicity (RR 2.00), socioeconomic deprivation (RR 1.17 per SD increase in Townsend Index), and high cystatin C (RR 1.13 per SD increase). The risk factors overlapped with pneumonia somewhat, less so for influenza. The associations with modifiable risk factors were generally stronger for COVID-19, than pneumonia or influenza.

Conclusion

These findings suggest that modification of lifestyle may help to reduce the risk of COVID-19 and could be a useful adjunct to other interventions, such as social distancing and shielding of high risk.

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Most cited references 46

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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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Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

Zunyou Wu, Jennifer M. McGoogan (2020)

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Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area

Safiya Richardson, Jamie Hirsch, Mangala Narasimhan … (2020)

There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19).

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Author and article information

Journal

Journal ID (nlm-ta): BMJ Open

Journal ID (iso-abbrev): BMJ Open

Journal ID (hwp): bmjopen

Journal ID (publisher-id): bmjopen

Title: BMJ Open

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2044-6055

Publication date Collection: 2020

Publication date (Electronic): 19 November 2020

Volume: 10

Issue: 11

Electronic Location Identifier: e040402

Affiliations

[1 ]departmentInstitute of Health and Wellbeing , University of Glasgow , Glasgow, UK

[2 ]departmentInstitute of Cardiovascular and Medical Sciences , University of Glasgow , Glasgow, UK

Author notes

[Correspondence to ] Dr Paul Welsh; Paul.Welsh@ 123456glasgow.ac.uk

Author information

Frederick K Ho http://orcid.org/0000-0001-7190-9025

Stuart R Gray http://orcid.org/0000-0001-8969-9636

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

Claire L Niedzwiedz http://orcid.org/0000-0001-6133-4168

Naveed Sattar http://orcid.org/0000-0002-1604-2593

Article

Publisher ID: bmjopen-2020-040402

DOI: 10.1136/bmjopen-2020-040402

PMC ID: 7678347

PubMed ID: 33444201

SO-VID: b13f8939-b655-46cb-9e00-df4dd756dc7e

License:

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

History

Date received : 12 May 2020

Date revision received : 08 September 2020

Date accepted : 11 October 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation;

Award ID: RE/18/6/34217

Funded by: Scottish Government Chief Scientist Office;

Award ID: SPHSU13

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

Award ID: MC_UU_12017/13

Award ID: MR/R024774/1

Funded by: NRS Senior Clinical Fellowship;

Award ID: SCAF/15/02

Custom metadata

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ScienceOpen disciplines: Medicine

Keywords: epidemiology,cardiology,diabetes & endocrinology

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ScienceOpen disciplines: Medicine

Keywords: epidemiology, cardiology, diabetes & endocrinology

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