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Updated: Jun 17, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
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Characterizing device-measured sleep in observational health research using compositional data analysis: a systematic

Christine W St Laurent1, Guilherme Moraes Balbim2, Denver M Y Brown3

  • 1Department of Kinesiology, University of Massachusetts Amherst, Amherst, Massachusetts, USA. cstlaurent@umass.edu.

The International Journal of Behavioral Nutrition and Physical Activity
|June 16, 2026
PubMed
Summary
This summary is machine-generated.

This review found inconsistent reporting of device-measured sleep data in compositional data analysis (CoDA) studies. Standardizing sleep measurement and processing is crucial for accurate insights into movement behaviors and health.

Keywords:
ActigraphyNapPhysical activitySedentary behaviorTime-use

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Area of Science:

  • Movement behavior science
  • Public health research
  • Data analysis methodologies

Background:

  • Compositional data analysis (CoDA) is vital for understanding the interplay between movement behaviors (sedentary time, physical activity, sleep) and health.
  • Existing reviews on CoDA reporting standards primarily focus on physical activity and sedentary behavior, neglecting the critical role of sleep data.
  • Standardized reporting of sleep data is essential for advancing CoDA research in health.

Purpose of the Study:

  • To systematically evaluate the measurement, processing, and reporting practices of device-based sleep data in studies employing CoDA.
  • To identify inconsistencies and gaps in sleep data handling within CoDA research examining movement behaviors and health outcomes.
  • To provide recommendations for improving the quality and comparability of sleep data in future CoDA studies.

Main Methods:

  • Conducted a systematic literature search across seven databases, supplemented by citation tracking and expert consultation.
  • Included observational studies published since 2015 that utilized CoDA with isometric log-ratio transformations and device-measured sleep data.
  • Extracted data on sleep actigraphy measurement, processing, and reporting, referencing American Academy of Sleep Medicine guidelines, and assessed study quality using the NIH tool.

Main Results:

  • Of 70 included studies, most reported limited sleep measurement and processing details.
  • A significant majority (67 studies) incorporated only one sleep component into their time-use composition.
  • Fewer than half (29 studies) acknowledged sleep-related limitations, with 10 studies rated as having poor quality.

Conclusions:

  • Significant inconsistencies exist in how device-measured sleep data is measured, processed, and reported in CoDA studies.
  • The variability in sleep data protocols underscores the urgent need for standardized approaches and transparent reporting.
  • Future research must prioritize consistency and transparency to enhance the validity and comparability of findings on sleep within the 24-hour movement behavior framework for health.