BMI and future risk for COVID-19 infection and death across sex, age and ethnicity: Preliminary findings from UK biobank
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Abstract
Abstract We examined the link between BMI and risk of a positive test for SARS-CoV-2 and risk of COVID-19-related death among UK Biobank participants. Among 4855 participants tested for SARS-CoV-2 in hospital, 839 were positive and of these 189 died from COVID-19. Poisson models with penalised thin plate splines were run relating exposures of interest to test positivity and case-fatality, adjusting for confounding factors. BMI was associated strongly with positive test, and risk of death related to COVID-19. The gradient of risk in relation to BMI was steeper in those under 70, compared with those aged 70 years or older for COVID-19 related death (Pinteraction=0.03). BMI was more strongly related to test positivity (P interaction =0.010) and death (P interaction =0.002) in non-whites, compared with whites. These data add support for adiposity being more strongly linked to COVID-19-related deaths in younger people and non-white ethnicities. If future studies confirm causality, lifestyle interventions to improve adiposity status may be important to reduce the risk of COVID-19 in all, but perhaps particularly, non-white communities.
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Empagliflozin (EMPA) exhibits potential therapeutic benefits for liver steatosis.
“Empagliflozin (EMPA), a highly selective inhibitor of sodium-glucose co-transporter 2 (SGLT2), exhibits potential therapeutic benefits for liver steatosis; however, the underlying mechanism remains incompletely elucidated.”
From SGLT2 inhibitor promotes ketogenesis to improve MASH by suppressing CD8+ T cell activation (2024) · cites this paper as [20]
The Conclusions (page unavailable) discuss BMI, adiposity, and COVID-19 risk, not treatment of liver steatosis. Searches for empagliflozin, SGLT2 inhibition, and steatosis found no passage addressing the claimed therapeutic benefit. (LLM, conf=0.78)
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“When taken in context with other emerging data [2,3,5], our results support the need for public health campaigns to help and support individuals across different ethnic groups who are overweight or obese to lose weight to lessen their chances of severe COVID-19.”
Factors associated with COVID-19-related death using OpenSAFELY
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- Authors
- Sattar, N., Ho, F. K., Gill, J. M., Ghouri, N., Gray, S. R., Celis-Morales, C. A., Katikireddi, S. V., Berry, C., Pell, J. P., McMurray, J. J., & Welsh, P.
- Affiliations
- University of Glasgow (GB)
- Corresponding author
- Sattar, Naveed
- ORCID
- Venue
- Diabetes & Metabolic Syndrome: Clinical Research & Reviews
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 14
- Issue
- 5
- Pages
- 1149-1151
- ISSN
- 1871-4021 (ISSN-L)
- PMC
- PMC7326434
- OpenAlex
- W3039633474
- Cited by
- 104
- References
- 5
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 6 · 2023: 18 · 2022: 26 · 2021: 36 · 2020: 14
- FWCI
- 3.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetes & Metabolic Syndrome Clinical Research & Reviews (publishedVersion, cc-by)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- Funders
- NS
- British Heart Foundation (RE/18/6/34217)
- Dasman Diabetes Institute
- NRS Senior Clinical Fellowship (SCAF/15/02)
- Medical Research Council (MC_UU_12017/13)
- Scottish Government
- Chief Scientist Office (SPHSU13)
- Amgen
- AstraZeneca
- Lilly
- Novo Nordisk
- Pfizer
- Sanofi
- Boehringer Ingelheim
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- body mass index, adiposity, COVID-19 pandemic, COVID-19 mortality, case fatality, sex differences, age differences, ethnicity, South Asians, Afro-Caribbean, UK Biobank
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Age Factors, Ethnicity, Female, United Kingdom, Humans, Male, Pneumonia, Viral, Prognosis, Risk Factors, Sex Factors, Body Mass Index, Survival Rate, Biological Specimen Banks, Coronavirus Infections, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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