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

Donald M Lyall; Terry Quinn; Laura M Lyall; Joey Ward; Jana J Anderson; Daniel J Smith; William Stewart; Rona J Strawbridge; Mark E S Bailey; Breda Cullen

doi:10.1093/braincomms/fcac119

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

Brain Commun. 2022 May 9;4(3):fcac119. doi: 10.1093/braincomms/fcac119. eCollection 2022.

Authors

Affiliations

¹ Institute of Health and Wellbeing, University of Glasgow, 1 Lilybank Gardens, Scotland G12 8RZ, UK.
² Institute of Cardiovascular and Medical Sciences, University of Glasgow, Scotland, UK.
³ Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland, UK.
⁴ Department of Neuropathology, Queen Elizabeth University Hospital, Scotland, UK.
⁵ Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
⁶ School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, Scotland, UK.

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 χ² 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 (versus had not), and compared their values at the imaging visit versus 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 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.

Keywords: UK Biobank; bias; epidemiology; imaging; psychological.

Abstract

Grants and funding