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

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.