Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?
Journal
International journal of obesity (2005)
ISSN: 1476-5497
Titre abrégé: Int J Obes (Lond)
Pays: England
ID NLM: 101256108
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
received:
01
03
2021
accepted:
23
06
2021
revised:
28
05
2021
pubmed:
8
7
2021
medline:
2
10
2021
entrez:
7
7
2021
Statut:
ppublish
Résumé
COVID-19 is a disease that has been shown to have outcomes that vary by certain socio-demographic and socio-economic groups. It is increasingly important that an understanding of these outcomes should be derived not from the consideration of one aspect, but by a more multi-faceted understanding of the individual. In this study use is made of a recent obesity driven classification of participants in the United Kingdom Biobank (UKB) to identify trends in COVID-19 outcomes. This classification is informed by a recently created obesity systems map, and the COVID-19 outcomes are: undertaking a test, a positive test, hospitalisation and mortality. It is demonstrated that the classification is able to identify meaningful differentials in these outcomes. This more holistic approach is recommended for identification and prioritisation of COVID-19 risk and possible long-COVID determination.
Identifiants
pubmed: 34230579
doi: 10.1038/s41366-021-00891-6
pii: 10.1038/s41366-021-00891-6
pmc: PMC8259102
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2281-2285Subventions
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Informations de copyright
© 2021. The Author(s).
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