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Correlates of sleep variability in a mobile EEG-based volunteer study
Péter Przemyslaw Ujma1, Róbert Bódizs2
1Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary. ujma.peter@semmelweis.hu.
Scientific Reports
|October 30, 2024
Summary
Younger age, late chronotypes, and napping increase sleep variability. Avoiding daytime naps is key for more regular sleep patterns, highlighting age and sleep habits as primary drivers of sleep inconsistency.
Area of Science:
- Sleep Science
- Chronobiology
- Neuroscience
Background:
- Variable sleep patterns are recognized disease risk factors.
- Understanding individual differences in sleep variability is crucial but poorly understood.
Purpose of the Study:
- To identify demographic, mental health, personality, chronotype, and sleep characteristic predictors of sleep variability.
- To analyze factors influencing detailed sleep macrostructure variability using a novel dataset.
Main Methods:
- Utilized the BSETS dataset, comprising 1901 nights of mobile EEG recordings from 267 participants.
- Employed extensive phenotyping and analyzed sleep macrostructure metrics to assess variability.
- Controlled for age to evaluate the influence of other psychosocial variables.
Main Results:
- Young age, late chronotype, and napping were robustly associated with increased sleep variability.
- Other factors like student status, personality, and mental health showed correlations that diminished after accounting for age.
- Age and sleep habits influencing sleep pressure were the primary drivers of sleep variability.
Conclusions:
- Age and sleep habits, particularly daytime napping, are key determinants of sleep variability.
- Avoiding daytime naps is the most promising modifiable behavior for enhancing sleep regularity.
- Psychosocial variables play a lesser role in sleep variability compared to age and sleep habits.
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