Coronavirus disease 2019 mortality: a multivariate ecological analysis in relation to ethnicity, population density, obesity, deprivation and pollution.


Journal

Public health
ISSN: 1476-5616
Titre abrégé: Public Health
Pays: Netherlands
ID NLM: 0376507

Informations de publication

Date de publication:
Aug 2020
Historique:
received: 06 05 2020
revised: 22 06 2020
accepted: 28 06 2020
pubmed: 22 7 2020
medline: 28 8 2020
entrez: 22 7 2020
Statut: ppublish

Résumé

There is emerging evidence about characteristics that may increase the risk of coronavirus disease 2019 (COVID-19) mortality, but they are highly correlated. An ecological analysis was used to estimate associations between these variables and age-standardised COVID-19 mortality rates at the local authority level. Ethnicity, population density and overweight/obesity were all found to have strong independent associations with COVID-19 mortality, at the local authority level. This analysis provides some preliminary evidence about which variables are independently associated with COVID-19 mortality and suggests that others (deprivation and pollution) are not directly linked. It highlights the importance of multivariate analyses to understand the factors that increase vulnerability to COVID-19.

Sections du résumé

BACKGROUND BACKGROUND
There is emerging evidence about characteristics that may increase the risk of coronavirus disease 2019 (COVID-19) mortality, but they are highly correlated.
METHODS METHODS
An ecological analysis was used to estimate associations between these variables and age-standardised COVID-19 mortality rates at the local authority level.
RESULTS RESULTS
Ethnicity, population density and overweight/obesity were all found to have strong independent associations with COVID-19 mortality, at the local authority level.
DISCUSSION CONCLUSIONS
This analysis provides some preliminary evidence about which variables are independently associated with COVID-19 mortality and suggests that others (deprivation and pollution) are not directly linked. It highlights the importance of multivariate analyses to understand the factors that increase vulnerability to COVID-19.

Identifiants

pubmed: 32693249
pii: S0033-3506(20)30294-8
doi: 10.1016/j.puhe.2020.06.056
pmc: PMC7340023
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

261-263

Informations de copyright

Copyright © 2020 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Références

Environ Pollut. 2015 Mar;198:201-10
pubmed: 25622242
JMIR Public Health Surveill. 2020 Apr 15;6(2):e18811
pubmed: 32252023
BMJ. 2020 Apr 20;369:m1548
pubmed: 32312785
Clin Obes. 2020 Jun;10(3):e12365
pubmed: 32342637

Auteurs

I Bray (I)

Centre for Public Health and Wellbeing, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY, UK. Electronic address: issy.bray@uwe.ac.uk.

A Gibson (A)

Centre for Public Health and Wellbeing, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY, UK. Electronic address: andy.gibson@uwe.ac.uk.

J White (J)

Centre for Public Health and Wellbeing, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY, UK. Electronic address: jo.white@uwe.ac.uk.

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