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Impaired Rest-Activity Rhythm Characteristics Predict Higher Risk of Incident Type 2 Diabetes in UK Biobank
Chris Ho Ching Yeung1, Alison K Wright2,3, Daniel P Windred4
1Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX.
Diabetes Care
|June 26, 2025
Summary
Disrupted rest-activity rhythms are linked to increased type 2 diabetes risk. Actigraphy metrics can predict diabetes incidence, offering potential as digital biomarkers for early detection.
Area of Science:
- Metabolic health and chronobiology research.
- Epidemiology and public health.
Background:
- Circadian rhythms are crucial for metabolic regulation.
- Disruptions in rest-activity patterns are associated with increased diabetes risk.
- Large-scale prospective studies are needed to evaluate various rest-activity metrics for diabetes risk prediction.
Purpose of the Study:
- To investigate the association between multiple rest-activity rhythm metrics and incident type 2 diabetes risk.
- To determine the predictive power of these metrics using advanced statistical models.
Main Methods:
- Analysis of actigraphy data from 83,887 UK Biobank participants.
- Derivation of 13 rest-activity metrics using parametric and nonparametric algorithms.
- Identification of diabetes cases through self-report and health records.
- Application of Cox proportional hazards and random forest models for risk assessment and prediction.
Main Results:
- Several rest-activity characteristics, including lower amplitude and rhythmicity, significantly predicted higher diabetes risk.
- Metrics like relative amplitude and M10 showed strong associations with increased incidence.
- Random forest models identified rest-activity metrics as key predictors, outperforming traditional risk factors.
- Findings were consistent across diverse demographic and occupational subgroups.
Conclusions:
- Actigraphy-derived rest-activity rhythm characteristics show promise as digital biomarkers for type 2 diabetes risk.
- These objective measures can aid in early identification and prevention strategies for diabetes.
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