  Objective: This study aimed to explore the associations between depression
severity and wearable-measured circadian rhythms, accounting for seasonal
impacts and quantifying seasonal changes in circadian rhythms.Materials and
Methods: Data used in this study came from a large longitudinal mobile health
study. Depression severity (measured biweekly using the 8-item Patient Health
Questionnaire [PHQ-8]) and behaviors (monitored by Fitbit) were tracked for up
to two years. Twelve features were extracted from Fitbit recordings to
approximate circadian rhythms. Three nested linear mixed-effects models were
employed for each feature: (1) incorporating the PHQ-8 score as an independent
variable; (2) adding the season variable; and (3) adding an interaction term
between season and the PHQ-8 score. Results: This study analyzed 10,018 PHQ-8
records with Fitbit data from 543 participants. Upon adjusting for seasonal
effects, higher PHQ-8 scores were associated with reduced activity, irregular
behaviors, and delayed rhythms. Notably, the negative association with daily
step counts was stronger in summer and spring than in winter, and the positive
association with the onset of the most active continuous 10-hour period was
significant only during summer. Furthermore, participants had shorter and later
sleep, more activity, and delayed circadian rhythms in summer compared to
winter. Discussion and Conclusions: Our findings underscore the significant
seasonal impacts on human circadian rhythms and their associations with
depression and indicate that wearable-measured circadian rhythms have the
potential to be the digital biomarkers of depression.
