Consistency of sleep timing and duration are associated with more physical activity and favorable heart rate metrics in a naturalistic cohort
Komilian, K.; Lee, I.; Goparaju, B.; Bianchi, M. T.
Show abstract
Background: Regularity of sleep patterns over time has increasingly gained traction as an important axis of sleep health. Since sleep habits are under some degree of behavioral control, understanding such patterns in naturalistic settings is particularly important. We quantified sleep variability and tested the hypothesis that regularity correlates with physical activity, resting heart rate (rHR), and heart rate variability (HRV). Methods: We analyzed real-world digital health data from over 81,000 participants (over 18 million nights) who provided informed consent to participate in the Apple Heart and Movement Study and elected to contribute sleep, activity, and heart rate data to the study. Variability was quantified using the standard deviation (SD) computed from total sleep time (TST), sleep start time (S-start), end time (S-end), and midpoint time (MP), as well as the Sleep Regularity Index (SRI). Results: The SD-based variability metrics correlated with one another (R values 0.74-0.92), and with the SRI metric (R values 0.62-0.64). More consistent sleep, by any metric, was associated with more activity and better rHR and HRV. The most consistent tertile for TST variability had higher median TST (6.9 vs 5.9 hours), more daily exercise (32.8 vs 20.4 minutes), lower rHR (62.4 vs 65.6 beats per minute), and higher HRV (40.6 vs 37.3), all p<1e-100. The findings were similar when variability was defined by S-start SD, S-end SD, MP SD, or SRI. Conclusion: Sleep consistency metrics are highly correlated with each other, and consistency by any metric was associated with more activity, lower rHR, and higher HRV. While causality cannot be established, the results of this large, naturalistic observational cohort are consistent with the growing literature on the potential positive health associations of sleep consistency.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Novel Digital Markers of Sleep Dynamics: A Causal Inference Approach Revealing Age and Gender Phenotypes in Obstructive Sleep Apnea 96%
- Sleep Regularity Index as a Novel Indicator of Sleep Disturbance in Stroke Survivors: A Secondary Data Analysis 95%
- Topographical relocation of adolescent sleep spindles reveals a new maturational pattern of the human brain 95%
Similar papers in this journal
- Evaluation of Dreem headband for sleep staging and EEG spectral analysis in people living with Alzheimer’s and older adults 95%
- Performance of an Electroencephalography-Measuring Headband or Actigraphy Compared with Polysomnography in Older Adults with Sleep Disturbances 95%
- Sustained polyphasic sleep restriction abolishes human growth hormone release 95%
Similar papers in this journal
- The potential of ensemble-based automated sleep staging on single-channel EEG signal from a wearable device 96%
- The effects of daylight saving time clock changes on accelerometer-measured sleep duration in the UK Biobank 96%
- Respiration-Triggered Olfactory Stimulation ReducesObstructive Sleep Apnea Symptoms Severity: A Prospective Pilot Study 95%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.