Wearable activity rhythms and biomarker-based biological aging in 2,222 All of Us participants
In 2,222 All of Us participants, multi-year Fitbit rest-activity rhythm intensity, timing and stability were associated with biomarker-derived PhenoAge aging trajectories; higher rhythm intensity was linked to 26–46% lower odds of accelerated aging. These are associations, not causes. [1]
Automatic summary · not editorially reviewed
The key findings
Multi-year Fitbit data from 2,222 All of Us participants (8,447 person-years) were linked with clinical biomarker-derived PhenoAge. [1]
Higher circadian rest-activity rhythm intensity was associated with 26–46% lower odds of accelerated aging. [1]
The authors propose wearable-derived rest-activity rhythms as possible digital biomarkers of aging trajectories. [1]
The source at a glance
- Study type / format
- Longitudinal observational analysis of wearable activity data and biomarker-derived biological age (abstract).
- Population / context
- 2,222 participants in the All of Us Research Program with multi-year Fitbit data and clinical biomarker-derived PhenoAge.
- Summary based on
- Study abstract
- Original publication
- August 22, 2026
Fitbit rhythms and PhenoAge in All of Us
The abstract describes a longitudinal analysis linking multi-year Fitbit activity data from the All of Us Research Program with clinical biomarker-derived PhenoAge in 2,222 participants, covering 8,447 person-years. The authors call this high-dimensional digital phenotyping. They report that circadian rest-activity rhythm intensity, timing and stability were associated with biological aging trajectories. The abstract does not report how PhenoAge was calculated or how often it was measured.
Supporting source [1]
Lower odds with higher rhythm intensity
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. The abstract does not explain what these surges and rebounds mean biologically. Because this is an observational analysis, these links do not show that changing rhythm intensity, timing or regularity would change biological aging.
Supporting source [1]
Digital biomarkers proposed, not proven
The authors conclude that consumer wearable-derived rest-activity rhythms may serve as digital biomarkers of aging trajectories. They describe the work as large-scale longitudinal evidence and highlight the potential of scalable digital measures for aging-related risk assessment and future healthy-aging research. This is a proposal about possible use, not a validated or approved tool. The abstract does not report effect sizes for timing or regularity, adjustment for confounders, or whether the full text was reviewed.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. The abstract does not report how PhenoAge was calculated or measured over time, effect sizes for timing and regularity, confounder adjustment, or whether the associations are causal. The biomarker use is proposed, not validated.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Shim J, Onnela JP. · europepmc.org · August 22, 2026