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Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?

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  • Clark, Stephen
  • Birkin, Mark
  • Lomax, Nik
  • Morris, Michelle

Abstract

In this short communication we demonstrate how an individual level classification built using a Whole Systems approach to an understanding of obesity can be used to profile individual’s exposure, treatment and mortality for COVID-19. The cohort is the UK Biobank and the information on COVID-19 test outcomes, hospitalisations and mortality are provided as part of this research initiative. We find that the cohort profiles accurately against the understood heightened risk factors for COVID-19, namely age, gender, ethnicity, obesity and deprivation. This confidence in these data then allows us to profile the participants in each of the classification clusters for these COVID-19 outcomes. We see that there is a large degree of differentiation between the classes. The article finishes by highlighting how this classification can help in prioritising care, treatments and vaccine delivery.

Suggested Citation

  • Clark, Stephen & Birkin, Mark & Lomax, Nik & Morris, Michelle, 2020. "Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?," OSF Preprints 2568p, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:2568p
    DOI: 10.31219/osf.io/2568p
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