Relative Associations of Behavioural and Physiological Risks for Cardiometabolic Disease with Cognition in Bipolar Disorder: Findings from the UK Biobank

Abstract

Background: Cardiometabolic disease risk factors are disproportionately prevalent in bipolar disorder (BD) and are associated with cognitive impairment. It is, however, unknown which health risk factors for cardiometabolic disease are relevant to cognition in BD. This study aimed to identify the cardiometabolic disease risk factors that are the most important correlates of cognitive impairment in BD; and to examine whether the nature of the relationships vary between mid and later life.Methods: Data from the UK Biobank were available for 966 participants with BD. Individual cardiometabolic disease risk factors were initially regressed onto a global cognition score in separate models for the following risk factor domains; 1) health risk behaviours (physical activity, sedentary behaviour, smoking, sleep) and 2) physiological risk factors, stratified into 2a) anthropometric and clinical risk (handgrip strength, body composition, blood pressure), and 2b) cardiometabolic disease risk biomarkers (CRP, lipid profile). A final combined multivariate regression model for global cognition was then fitted, including only the predictor variables that were significantly associated with cognition in the previous models.Results: In the final combined model, lower mentally-active and higher passive sedentary behaviour, higher levels of physical activity, inadequate sleep duration, higher systolic and lower diastolic blood pressure, and lower handgrip strength were associated with worse global cognition. Conclusions: Health risk behaviours, as well as blood pressure and muscular strength, are associated with cognitive function in BD, whereas other traditional physiological cardiometabolic disease risk factors are not.

Neurocognitive correlates of metabolic dysregulation in individuals with mood disorders: a systematic review and meta-analysis

“…Twenty-seven studies explored the impact of metabolic dysregulation on cognitive outcomes in individuals with BD (Bai et al, 2016;Beunders et al, 2021;Bond et al, 2017;Chang et al, 2022;Dalkner et al, 2021aDalkner et al, , 2021bDepp et al, 2014;Hubenak, Tuma, & Bazant, 2015;Hui et al, 2019;Kadriu et al, 2023;La Montagna et al, 2017;Lackner et al, 2016;Li et al, 2015;Liebing et al, 2023;Mehra, Jagota, Sahoo, & Grover, 2022;Mora et al, 2017;Naiberg, Newton, Collins, Bowie, & Goldstein, 2016a;Naiberg et al, 2016b;Qiu et al, 2022;Reininghaus et al, 2022;Ringin et al, 2023aRingin et al, , 2023bSalvi et al, 2020;Silveira et al, 2014;Tsai, Lee, Chen, & Huang, 2007;Van Rheenen, McIntyre, Balanzá-Martínez, Berk, & Rossell, 2021;Yim et al, 2012), 15 in MDD (Cao et al, 2023;Fourrier et al, 2020;Geraets et al, 2022;Guan et al, 2021;Hidese et al, 2018;Kloiber et al, 2007;Kopchak & Pulyk, 2017;Kraus et al, 2023;Lan et al, 2022;Marijnissen et al, 2017;Péterfalvi et al, 2019;Shao et al, 2017;…”