Evidence map›Paper›PMID 42298642›Full record

SynthesisThe international journal of behavioral nutrition and physical activity2026

Characterizing device-measured sleep in observational health research using compositional data analysis: a systematic review.

Christine W St Laurent, Guilherme Moraes Balbim, Denver M Y Brown, Chelsea L Kracht, Christopher D Pfledderer, Claire I Groves, Carah D Holesovsky, Griffin A T Randolph, Katrina Rodheim, Sarah Burkart

Abstract readSystematic ReviewReview
In one paragraph

Synthesis in The international journal of behavioral nutrition and physical activity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Christine W St LaurentDepartment of Kinesiology, University of Massachusetts Amherst, Amherst, Massachusetts, USA. cstlaurent@umass.edu.
Guilherme Moraes BalbimDepartment of Physical Therapy, The University of British Columbia, Vancouver, British Columbia, Canada.
Denver M Y BrownSchool of Health Sciences, Kansas State University, Manhattan, Kansas, USA.
Chelsea L KrachtDepartment of Internal Medicine, Medical Center, University of Kansas, Kansas City, Kansas, USA.
Christopher D PfleddererThe University of Texas Health Science Center Houston, School of Public Health in Austin, Austin, Texas, USA.
Claire I GrovesDepartment of Psychology, University of Texas at San Antonio, San Antonio, Texas, USA.
Carah D HolesovskySchool of Health Sciences, Kansas State University, Manhattan, Kansas, USA.
Griffin A T RandolphUniversity of South Carolina, Arnold School of Public Health, Columbia, South Carolina, USA.
Katrina RodheimDepartment of Kinesiology, University of Massachusetts Amherst, Amherst, Massachusetts, USA.
Sarah BurkartUniversity of South Carolina, Arnold School of Public Health, Columbia, South Carolina, USA.

Funding

longitudinal assessment of stress and stress-related concepts across a behavioral weight loss interventionP20GM144269 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI John P Thyfault, STEVEN A WEINMAN · 2022 to 2026
$14.9M
Targeting Behavioral Adjustment and Healthy Lifestyle in Preschool-Age Children Using an Integrated Family-Based InterventionP20GM130420 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI PRINZ, RONALD J · 2020 to 2024
$11.2M
NIGMS NIH HHS P20 GM130420NIGMS NIH HHS P20GM130420NIGMS NIH HHS P20 GM144269NIGMS NIH HHS P20GM144269
6 · The paper itself

Abstract

Compositional data analysis (CoDA) is widely used to examine the associations between one's balance of movement behaviors (sedentary behavior, physical activity, and sleep) and health outcomes. Existing reviews have primarily focused on reporting standards for physical activity and sedentary behavior, but have not considered the contribution of sleep reporting to our understanding of CoDA.Purpose To characterize device-based sleep data measurement, processing, and reporting in studies using CoDA to examine associations between movement behaviors and health indicators.Methods A systematic search was conducted in seven databases, along with supplemental strategies (forward and backward citation searches and expert review). Observational studies published since 2015 that employed CoDA approaches using isometric log-ratio transformations to examine the associations between movement behavior compositions utilizing device-based measures of sleep and health outcomes were included. Data extraction included items based on sleep actigraphy measurement, processing, and reporting practices recommended by the American Academy of Sleep Medicine. The National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-sectional Studies was used to assess study quality.Results Among the 70 included studies (n = 60 cross-sectional, n = 10 longitudinal), few articles reported key sleep measurement and processing information. Most articles (n = 67) included only one sleep component in the time-use composition, and less than half of the articles (n = 29) acknowledged sleep-related limitations. Reports were classified as having good (n = 60) or poor (n = 10) study quality.Conclusions This review identified inconsistencies in the measurement, processing, and reporting of device-measured sleep in studies using CoDA. Varying protocols and reporting on sleep data processing highlight the need for adoption of current standardized approaches and reporting practices. Future research should prioritize transparency and consistency to improve the validity and comparability of findings on sleep's role as a key component of the integrative 24-h approach to health.

Indexed as

ActigraphyData AnalysisObservational Studies as TopicSleepExerciseHumansSedentary BehaviorSleep DurationActigraphyNapPhysical activitySedentary behaviorTime-use

Identifiers

PMID42298642
PMCPMC13501660

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.