Quantifying bias in psychological and physical health in the UK Biobank imaging sub-sample

Lyall, D. M. , Quinn, T. , Lyall, L. M., Ward, J. , Anderson, J. J. , Smith, D. J. , Stewart, W. , Strawbridge, R. J. , Bailey, M. E.S. and Cullen, B. (2022) Quantifying bias in psychological and physical health in the UK Biobank imaging sub-sample. Brain Communications, 4(3), fcac119. (doi: 10.1093/braincomms/fcac119) (PMID:35651593) (PMCID:PMC9150072)

Abstract

UK Biobank is a prospective cohort study of around half-a-million general population participants, recruited between 2006 and 2010, with baseline studies at recruitment and multiple assessments since. From 2014 to date magnetic resonance imaging (MRI) has been pursued in a participant sub-sample, with the aim to scan around n = 100k. This sub-sample is studied widely and therefore understanding its relative characteristics is important for future reports. We aimed to quantify psychological and physical health in the UK Biobank imaging sub-sample, compared with the rest of the cohort. We used t-tests and chi-squares for continuous/categorical variables respectively, to estimate average differences on a range of cognitive, mental and physical health phenotypes. We contrasted baseline values of participants who attended imaging (vs. had not), and compared their values at the imaging visit vs. baseline values of participants who were not scanned. We also tested the hypothesis that the associations of established risk factors with worse cognition would be underestimated in the (hypothesized) healthier imaging group compared with the full cohort. We tested these interactions using linear regression models. On a range of cognitive, mental health, cardiometabolic, inflammatory and neurological phenotypes we found that the 47,920 participants who were scanned by January 2021 showed consistent statistically significant ‘healthy’ bias compared with the ∼450,000 who were not scanned. These effect sizes were small to moderate based on Cohen’s d/Cramer’s V metrics (range = 0.02 to -0.21 for Townsend, the largest effect size). We found evidence of interaction, where stratified analysis demonstrated that associations of established cognitive risk factors were smaller in the imaging sub-sample compared with the full cohort. Of the ∼100,000 participants who ultimately will undergo MRI assessment within UK Biobank, the first ∼50,000 showed some ‘healthy’ bias on a range of metrics at baseline. Those differences largely remained at the subsequent (first) imaging visit, and we provide evidence that testing associations in the imaging sub-sample alone could lead to potential underestimation of exposure/outcome estimates.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Stewart, Dr William and Smith, Professor Daniel and Anderson, Dr Jana and Cullen, Dr Breda and Lyall, Dr Laura and Bailey, Dr Mark and Ward, Dr Joey and Quinn, Professor Terry and Strawbridge, Dr Rona and Lyall, Dr Donald
• Authors: Lyall, D. M., Quinn, T., Lyall, L. M., Ward, J., Anderson, J. J., Smith, D. J., Stewart, W., Strawbridge, R. J., Bailey, M. E.S., and Cullen, B.
• 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 > Mental Health and Wellbeing; College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health; College of Medical Veterinary and Life Sciences > School of Life Sciences; College of Medical Veterinary and Life Sciences > School of Molecular Biosciences; College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Journal Name: Brain Communications
• Publisher: Oxford University Press
• ISSN: 2632-1297
• ISSN (Online): 2632-1297
• Published Online: 09 May 2022
• Copyright Holders: Copyright © 2022 The Author(s)
• First Published: First published in Brain Communications 4(3): fcac119
• Publisher Policy: Reproduced under a Creative Commons License