To examine the associations between accelerometer-based sleep-wake cycle measures and incident dementia, and to assess whether these measures improve the prediction of dementia risk in the UK Biobank cohort.
Approach:
Data Collection: Participants wore accelerometers continuously for several days to collect detailed data on sleep-wake cycles, including metrics such as total sleep duration and activity levels.
Key Findings:
High-resolution accelerometers can measure sleep-wake cycles across multiple dimensions.
Disruptions in sleep-wake cycles may serve as early markers for dementia risk.
Existing studies have shown inconsistent associations between sleep-wake cycle measures and dementia risk.
Interpretation:
The study aims to clarify the role of sleep-wake cycle indicators in predicting dementia.
Limitations:
The study's findings may not be generalizable due to the predominantly self-reported White race of participants, which may not represent the broader population.
Conclusion:
The study seeks to provide insights into the predictive value of sleep-wake cycle measures for dementia risk.
by Clémence Cavaillès, Ian Meneghel Danilevicz, Sam Vidil, Aurore Fayosse, Mathilde Chen, Vincent van Hees, Mika Kivimäki, Aline Dugravot, Archana Singh-Manoux, Séverine Sabia
