Predicting circadian phase in community‐dwelling later‐life adults using actigraphy data

• DOI: 10.1111/jsr.14425
• Publication Date: 2024-12-09T01:09:43Z
• Authors: Caleb Mayer; Dae Wook Kim; Meina Zhang; Minki P. Lee; Daniel B. Forger; Helen J. Burgess; Chooza Moon
• Keywords: Entrainment (biomusicology)

Summary The accurate estimation of circadian phase in the real‐world has a variety applications, including chronotherapeutic drug delivery, reduction fatigue, and optimal jet lag or shift work scheduling. Recent developed adapted algorithms to predict time‐consuming costly laboratory measurements using mathematical models with actigraphy other wearable data. Here, we validate extend these results home‐based cohort later‐life adults, ranging age from 58 86 years. Analysis this population serves as valuable extension our understanding prediction, since key features timekeeping (including amplitude, response light stimuli, susceptibility misalignment) may become altered older populations when observed real‐life settings. We assessed ability four ground truth dim melatonin onset, found that all could generate predictions mean absolute errors approximately 1.4 h below actigraph activity Simulations model performed well better than light‐based modelling predictions, validating previous findings novel cohort. Interestingly, comparably actigraph‐derived sleep metrics, higher‐order nonphotic activity‐based particular demonstrating superior performance. This provides evidence rhythms can be reasonably estimated adults living home settings through data devices.