Authors
Han Chen, Jiahe Wei, Jonathan Cedernaes, Christian Benedict, Athanasios Tsanas, Zhi Cao, Xiao Tan
Published in
Advanced science (Weinheim, Baden-Wurttemberg, Germany). Pages e76217. Jun 19, 2026. Epub Jun 19, 2026.
Abstract
Circadian rhythms coordinate physiology with the 24 h light-dark cycle, and their disruption contributes to diseases spanning metabolic, cardiovascular, and neuropsychiatric domains. Whether the temporal coherence between wearable-derived activity and temperature rhythms predicts long-term health outcomes in free-living humans remains unknown. Here, analyzing week-long concurrent wrist-worn acceleration and device temperature recordings from approximately 90,000 UK Biobank participants (median age 63 years), we decompose the circular cross-correlation between behavioral and device temperature signals into three alignment features, including 24 h coupling strength (M24), phase deviation from expected antiphase (D24), and 12 h harmonic magnitude (M12). Over 7-11 years of prospective follow-up, higher M24 is associated with lower risk of type 2 diabetes, cardiovascular disease, depression, sleep apnea, and all-cause mortality, whereas higher D24 is associated with increased cardiometabolic risk. Higher M12 was associated with a lower risk of gastrointestinal and psychiatric conditions. Technical replication in the SHARE cohort supported the portability of the feature-extraction framework across device protocols. These findings highlight wearable-derived cross-domain diurnal alignment as a scalable, prospective predictor of disease risk, with potential implications for population health surveillance.
PMID:
42318644
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.
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