The association between a lifestyle score, socioeconomic status, and COVID-19 outcomes within the UK Biobank cohort

Foster, H. M.E. et al. (2022) The association between a lifestyle score, socioeconomic status, and COVID-19 outcomes within the UK Biobank cohort. BMC Infectious Diseases, 22, 273. (doi: 10.1186/s12879-022-07132-9) (PMID:35351028) (PMCID:PMC8964028)

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Background: Infection with SARS-CoV-2 virus (COVID-19) impacts disadvantaged groups most. Lifestyle factors are also associated with adverse COVID-19 outcomes. To inform COVID-19 policy and interventions, we explored effect modification of socioeconomic-status (SES) on associations between lifestyle and COVID-19 outcomes. Methods: Using data from UK-Biobank, a large prospective cohort of 502,536 participants aged 37–73 years recruited between 2006 and 2010, we assigned participants a lifestyle score comprising nine factors. Poisson regression models with penalised splines were used to analyse associations between lifestyle score, deprivation (Townsend), and COVID-19 mortality and severe COVID-19. Associations between each exposure and outcome were examined independently before participants were dichotomised by deprivation to examine exposures jointly. Models were adjusted for sociodemographic/health factors. Results: Of 343,850 participants (mean age > 60 years) with complete data, 707 (0.21%) died from COVID-19 and 2506 (0.76%) had severe COVID-19. There was evidence of a nonlinear association between lifestyle score and COVID-19 mortality but limited evidence for nonlinearity between lifestyle score and severe COVID-19 and between deprivation and COVID-19 outcomes. Compared with low deprivation, participants in the high deprivation group had higher risk of COVID-19 outcomes across the lifestyle score. There was evidence for an additive interaction between lifestyle score and deprivation. Compared with participants with the healthiest lifestyle score in the low deprivation group, COVID-19 mortality risk ratios (95% CIs) for those with less healthy scores in low versus high deprivation groups were 5.09 (1.39–25.20) and 9.60 (4.70–21.44), respectively. Equivalent figures for severe COVID-19 were 5.17 (2.46–12.01) and 6.02 (4.72–7.71). Alternative SES measures produced similar results. Conclusions: Unhealthy lifestyles are associated with higher risk of adverse COVID-19, but risks are highest in the most disadvantaged, suggesting an additive influence between SES and lifestyle. COVID-19 policy and interventions should consider both lifestyle and SES. The greatest public health benefit from lifestyle focussed COVID-19 policy and interventions is likely to be seen when greatest support for healthy living is provided to the most disadvantaged groups.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Katikireddi, Professor Vittal and Celis, Dr Carlos and Hastie, Dr Claire and Jani, Dr Bhautesh and Gill, Professor Jason and Ho, Dr Frederick and Anderson, Dr Jana and Foster, Dr Hamish and Pell, Professor Jill and Nicholl, Dr Barbara and Mair, Professor Frances and Sattar, Professor Naveed and Niedzwiedz, Dr Claire and O'Donnell, Professor Kate
Authors: Foster, H. M.E., Ho, F. K., Mair, F. S., Jani, B. D., Sattar, N., Katikireddi, S. V., Pell, J. P., Niedzwiedz, C. L., Hastie, C. E., Anderson, J. J., Nicholl, B. I., Gill, J. M.R., Celis-Morales, C., and O'Donnell, C. A.
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 > Public Health
Journal Name:BMC Infectious Diseases
Publisher:BioMed Central
ISSN (Online):1741-7015
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in BMC Medicine 22: 273
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
305234Using Big-data to Understand the Interactions between Lifestyle, Deprivation and health outcomes to support Intervention Development in deprived areas (BUILD): a mixed methods programmeCatherine O'DonnellMedical Research Council (MRC)MR/T001585?1HW - General Practice and Primary Care
172690Understanding the impacts of welfare policy on health: A novel data linkage studySrinivasa KatikireddiOffice of the Chief Scientific Adviser (CSO)SCAF/15/02HW - Public Health
3048231Inequalities in healthAlastair LeylandMedical Research Council (MRC)MC_UU_00022/2HW - MRC/CSO Social and Public Health Sciences Unit
3048231Inequalities in healthAlastair LeylandChief Scientist Office (CSO)SPHSU17HW - 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/R024774/1HW - Public Health