Correlates of poor sleep based upon wrist actigraphy data in bipolar disorder

Abstract

Background: Wrist-worn actigraphy can objectively measure sleep, and has advantages over self-report, particularly for people with Bipolar Disorder (BD) for whom self-reports might be influenced by affect. Clinically useful data reduction approaches are needed to explore these complex data. Methods: We created a composite score of sleep metrics in BD based on 51 BD and 80 healthy comparison (HC) participants. Subjects wore an actigraph for up to 14 consecutive 24-h periods, and we assessed total sleep time (TST), wake after sleep onset (WASO), percent sleep (PS), and number of awakenings (NA). We focused on participants who had at least 5 nights of actigraphy data. We computed z-scores for within-person means of sleep measures for BD subjects versus HCs, which were averaged to create a composite measure. We correlated this composite with participant characteristics, and used LASSO regression to identify sleep measures best explaining variability in identified correlates. Results: Sleep measures and the composite did not differ between BDs and HCs; however, there was considerable variability in z-scores among those with BD. In BDs, the composite score was higher in women (t(49) = 2.28, p = 0.027) and those who were employed (t(34) = 2.34, p = 0.025), and positively correlated with medication load (r = 0.41, p = 0.003) while negatively correlated with Young Mania Rating Scale (YMRS; r = -0.35, p = 0.030). In LASSO regression, TST and NA best explained medication load while PS best explained employment and YMRS. Conclusion: While a composite score of sleep metrics may provide useful information about sleep quality globally, our findings suggest that selection of theory-driven sleep measures may be more clinically meaningful.