ArticleNature communications2026
Longitudinal digital phenotyping of activity rhythms and biological aging using commercial wearables.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Disrupted rest-activity rhythms have been associated with aging and chronic disease, yet longitudinal evidence from free-living populations has been lacking. Here we integrate multi-year Fitbit activity data from the All of Us Research Program with clinical biomarker-derived PhenoAge from 2,222 participants (8,447 person-years). Through high-dimensional digital phenotyping, we show that circadian rest-activity rhythm intensity, timing, and stability are associated with biological aging trajectories. Higher rhythm intensity was associated with 26-46% lower odds of accelerated aging. Associations of timing and regularity were stronger in females. In males, accelerated aging followed a biphasic instability pattern with early-morning surges and late-evening rebounds. These findings provide large-scale longitudinal evidence that consumer wearable-derived rest-activity rhythms may serve as digital biomarkers of aging trajectories. By linking population-scale digital phenotyping to biological aging, this work highlights the potential of scalable digital measures for aging-related risk assessment and future healthy-aging research.
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