The University of Southampton
University of Southampton Institutional Repository

Association between household size and COVID-19: A UK Biobank observational study

Association between household size and COVID-19: A UK Biobank observational study
Association between household size and COVID-19: A UK Biobank observational study

Objective: To assess the association between household size and risk of non-severe or severe COVID-19. Design: A longitudinal observational study. Setting: This study utilised UK Biobank linked to national SARS-CoV-2 laboratory test data. Participants: 401,910 individuals with available data on household size in UK Biobank. Main outcome measures: Household size was categorised as single occupancy, two-person households and households of three or more. Severe COVID-19 was defined as a positive SARS-CoV-2 test on hospital admission or death with COVID-19 recorded as the underlying cause; and non-severe COVID-19 as a positive test from a community setting. Logistic regression models were fitted to assess associations, adjusting for potential confounders. Results: Of 401,910 individuals, 3612 (1%) were identified as having suffered from a severe COVID-19 infection and 11,264 (2.8%) from a non-severe infection, between 16 March 2020 and 16 March 2021. Overall, the odds of severe COVID-19 was significantly higher among individuals living alone (adjusted odds ratio: 1.24 [95% confidence interval: 1.14 to 1.36], or living in a household of three or more individuals (adjusted odds ratio: 1.28 [1.17 to 1.39], when compared to individuals living in a household of two. For non-severe COVID-19 infection, individuals living in a single-occupancy household had lower odds compared to those living in a household of two (adjusted odds ratio: 0.88 [0.82 to 0.93]. Conclusions: Odds of severe or non-severe COVID-19 infection were associated with household size. Increasing understanding of why certain households are more at risk is important for limiting spread of the infection.

Infectious diseases, epidemiologic studies, housing and health, public health, social conditions and disease
0141-0768
138-144
Gillies, Clare L
fc26555a-79f4-4d0e-9a34-1dc4fbda4be9
Rowlands, Alex V
881cca19-ef16-40b6-880e-4de367a2ade8
Razieh, Cameron
1f2cef7c-20b4-4edc-9533-c34fed0bfc13
Nafilyan, Vahé
bae04e8d-af87-4def-965c-3d59e2017a9b
Chudasama, Yogini
8026abd3-900a-4b96-8d5f-2ef59496929e
Islam, Nazrul
e5345196-7479-438f-b4f6-c372d2135586
Zaccardi, Francesco
8d31a980-3db1-4477-9514-c18087cf886a
Ayoubkhani, Daniel
cfd1b0e2-6685-4edb-a53f-299582b89280
Lawson, Claire
631da820-36df-4ffd-ab81-a76953a83eb2
Davies, Melanie J
f23a2532-1297-4ee3-93d1-8387ab98e151
Yates, Tom
6a3cb2f6-ab68-4729-a105-24983ae2acf0
Khunti, Kamlesh
3e64e5f4-0cc9-4524-aa98-3c74c25101c3
Gillies, Clare L
fc26555a-79f4-4d0e-9a34-1dc4fbda4be9
Rowlands, Alex V
881cca19-ef16-40b6-880e-4de367a2ade8
Razieh, Cameron
1f2cef7c-20b4-4edc-9533-c34fed0bfc13
Nafilyan, Vahé
bae04e8d-af87-4def-965c-3d59e2017a9b
Chudasama, Yogini
8026abd3-900a-4b96-8d5f-2ef59496929e
Islam, Nazrul
e5345196-7479-438f-b4f6-c372d2135586
Zaccardi, Francesco
8d31a980-3db1-4477-9514-c18087cf886a
Ayoubkhani, Daniel
cfd1b0e2-6685-4edb-a53f-299582b89280
Lawson, Claire
631da820-36df-4ffd-ab81-a76953a83eb2
Davies, Melanie J
f23a2532-1297-4ee3-93d1-8387ab98e151
Yates, Tom
6a3cb2f6-ab68-4729-a105-24983ae2acf0
Khunti, Kamlesh
3e64e5f4-0cc9-4524-aa98-3c74c25101c3

Gillies, Clare L, Rowlands, Alex V, Razieh, Cameron, Nafilyan, Vahé, Chudasama, Yogini, Islam, Nazrul, Zaccardi, Francesco, Ayoubkhani, Daniel, Lawson, Claire, Davies, Melanie J, Yates, Tom and Khunti, Kamlesh (2022) Association between household size and COVID-19: A UK Biobank observational study. Journal of the Royal Society of Medicine, 115 (4), 138-144. (doi:10.1177/01410768211073923).

Record type: Article

Abstract

Objective: To assess the association between household size and risk of non-severe or severe COVID-19. Design: A longitudinal observational study. Setting: This study utilised UK Biobank linked to national SARS-CoV-2 laboratory test data. Participants: 401,910 individuals with available data on household size in UK Biobank. Main outcome measures: Household size was categorised as single occupancy, two-person households and households of three or more. Severe COVID-19 was defined as a positive SARS-CoV-2 test on hospital admission or death with COVID-19 recorded as the underlying cause; and non-severe COVID-19 as a positive test from a community setting. Logistic regression models were fitted to assess associations, adjusting for potential confounders. Results: Of 401,910 individuals, 3612 (1%) were identified as having suffered from a severe COVID-19 infection and 11,264 (2.8%) from a non-severe infection, between 16 March 2020 and 16 March 2021. Overall, the odds of severe COVID-19 was significantly higher among individuals living alone (adjusted odds ratio: 1.24 [95% confidence interval: 1.14 to 1.36], or living in a household of three or more individuals (adjusted odds ratio: 1.28 [1.17 to 1.39], when compared to individuals living in a household of two. For non-severe COVID-19 infection, individuals living in a single-occupancy household had lower odds compared to those living in a household of two (adjusted odds ratio: 0.88 [0.82 to 0.93]. Conclusions: Odds of severe or non-severe COVID-19 infection were associated with household size. Increasing understanding of why certain households are more at risk is important for limiting spread of the infection.

Text
01410768211073923 - Version of Record
Available under License Creative Commons Attribution.
Download (977kB)

More information

Accepted/In Press date: 30 December 2021
e-pub ahead of print date: 4 February 2022
Published date: 1 April 2022
Keywords: Infectious diseases, epidemiologic studies, housing and health, public health, social conditions and disease

Identifiers

Local EPrints ID: 469999
URI: http://eprints.soton.ac.uk/id/eprint/469999
ISSN: 0141-0768
PURE UUID: d1da0667-84ef-45ab-ad7e-74f5fa65c992
ORCID for Nazrul Islam: ORCID iD orcid.org/0000-0003-3982-4325

Catalogue record

Date deposited: 29 Sep 2022 17:00
Last modified: 17 Mar 2024 04:15

Export record

Altmetrics

Contributors

Author: Clare L Gillies
Author: Alex V Rowlands
Author: Cameron Razieh
Author: Vahé Nafilyan
Author: Yogini Chudasama
Author: Nazrul Islam ORCID iD
Author: Francesco Zaccardi
Author: Daniel Ayoubkhani
Author: Claire Lawson
Author: Melanie J Davies
Author: Tom Yates
Author: Kamlesh Khunti

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×