Vitamin D concentrations and COVID-19 infection in UK Biobank

Hastie, C. E. et al. (2020) Vitamin D concentrations and COVID-19 infection in UK Biobank. Diabetes and Metabolic Syndrome: Clinical Research and Reviews, 14(4), pp. 561-565. (doi: 10.1016/j.dsx.2020.04.050) (PMID:32413819) (PMCID:PMC7204679)

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Abstract

Background and aims: COVID-19 and low levels of vitamin D appear to disproportionately affect black and minority ethnic individuals. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 risk, and whether it explained the higher incidence of COVID-19 in black and South Asian people. Methods: UK Biobank recruited 502,624 participants aged 37–73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration and ethnicity, were linked to COVID-19 test results. Univariable and multivariable logistic regression analyses were performed for the association between 25(OH)D and confirmed COVID-19, and the association between ethnicity and both 25(OH)D and COVID-19. Results: Complete data were available for 348,598 UK Biobank participants. Of these, 449 had confirmed COVID-19 infection. Vitamin D was associated with COVID-19 infection univariably (OR = 0.99; 95% CI 0.99–0.999; p = 0.013), but not after adjustment for confounders (OR = 1.00; 95% CI = 0.998–1.01; p = 0.208). Ethnicity was associated with COVID-19 infection univariably (blacks versus whites OR = 5.32, 95% CI = 3.68–7.70, p-value<0.001; South Asians versus whites OR = 2.65, 95% CI = 1.65–4.25, p-value<0.001). Adjustment for 25(OH)D concentration made little difference to the magnitude of the association. Conclusions: Our findings do not support a potential link between vitamin D concentrations and risk of COVID-19 infection, nor that vitamin D concentration may explain ethnic differences in COVID-19 infection.

Item Type:Articles
Additional Information:A correction to this article is available at https://doi.org/10.1016/j.dsx.2020.07.021.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Katikireddi, Professor Vittal and Jani, Dr Bhautesh and Celis, Dr Carlos and Hastie, Dr Claire and Gray, Professor Stuart and Gill, Professor Jason and Ho, Dr Frederick and Welsh, Professor Paul and Pell, Professor Jill and Mackay, Professor Daniel and Sattar, Professor Naveed and Mair, Professor Frances and Niedzwiedz, Dr Claire and O'Donnell, Professor Kate
Authors: Hastie, C. E., Mackay, D. F., Ho, F., Celis-Morales, C. A., Katikireddi, S. V., Niedzwiedz, C. L., Jani, B. D., Welsh, P., Mair, F. S., Gray, S. R., O'Donnell, C. A., Gill, J. M.R., Sattar, N., and Pell, J. P.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > General Practice and Primary Care
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Mental Health and Wellbeing
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health
Journal Name:Diabetes and Metabolic Syndrome: Clinical Research and Reviews
Publisher:Elsevier
ISSN:1871-4021
ISSN (Online):1878-0334
Published Online:07 May 2020
Copyright Holders:Copyright © 2020 Diabetes India
First Published:First published in Diabetes and Metabolic Syndrome: Clinical Research and Reviews 14(4): 561-565
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172690Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiOffice of the Chief Scientific Adviser (CSO)SCAF/15/02SHW - Public Health
727651Measuring and Analysing Socioeconomic Inequalities in HealthAlastair LeylandMedical Research Council (MRC)MC_UU_12017/13HW - MRC/CSO Social and Public Health Sciences Unit
727651Measuring and Analysing Socioeconomic Inequalities in HealthAlastair LeylandOffice of the Chief Scientific Adviser (CSO)SPHSU13HW - MRC/CSO Social and Public Health Sciences Unit
302182A machine learning approach to understanding comorbidity between mental and physical health conditionsClaire NiedzwiedzMedical Research Council (MRC)MR/R024774/1SHW - Public Health
303944BHF Centre of ExcellenceRhian TouyzBritish Heart Foundation (BHF)RE/18/6/34217CAMS - Cardiovascular Science