Evidence map›Paper›PMID 41732290›Full record

ArticleJournal of exercise science and fitness2026

Profiles of 24-h movement behaviors and physical fitness among preschool children: a latent profile analysis.

Bin Yang, Long Yin, Zongyu Yang, Pan Liu, Fang Li, Yi Feng Chen, Xiaoming Liu

Abstract read
In one paragraph

Article in Journal of exercise science and fitness, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Bin YangCollege of Physical Education, Hunan Normal University, Changsha, China.
Long YinCollege of Physical Education, Hunan Normal University, Changsha, China.
Zongyu YangCollege of Physical Education, Hunan Normal University, Changsha, China.
Pan LiuSchool of Physical Education, Hunan University of Technology, Zhuzhou, China.
Fang LiSchool of Physical Education, Hunan First Normal University, Changsha, China.
Yi Feng ChenCollege of Physical Education, Hunan Normal University, Changsha, China.
Xiaoming LiuCollege of Physical Education, Hunan Normal University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to identify the 24-h movement behavior patterns of preschool children using Latent Profile Analysis based on Compositional Data Analysis (CoDA), and to examine their associations with physical fitness. Methods: The study employs a cross-sectional design. A total of 329 healthy children aged 4-6 years were selected. Accelerometers (ActiGraph wGT3-BT, Pensacola, FL, USA) were used to measure light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sedentary behavior (SB), while sleep was assessed through parent and teacher questionnaires. The assessment of physical fitness was conducted in accordance with the "Chinese National Physical Fitness Test Standards" (Preschooler Section). To address the multicollinearity problems among components of physical activity (PA), CoDA was first applied, subsequently, Latent Profile Analysis was utilized to categorize 24-h movement behavior patterns, while a Generalized Ordered Logit Model (GOLM) was applied to investigate their associations with physical fitness. Results: Three distinct behavioral patterns emerged from the analysis: the "brown bear group" (moderate PA and SB, high SP, N = 176, 53.5%), the "cheetah group" (high PA/MVPA, low SB, moderate SP, N = 102, 31%), and the "koala group" (low PA, high SB, lower SP, N = 51, 15.5%). After adjusting for potential confounding factors, it was found that compared with the "koala group", the "brown bear group" and the "cheetah group" exhibited higher levels of physical fitness, with the probability of improving their physical fitness rating being 3.69 times and 6.36 times that of the "koala group," respectively. Conclusion: This study highlights the significant impact of active and healthy activity patterns on the physical fitness of preschool children, providing a foundation for formulating personalized preventive and interventional approaches in early childhood.

Indexed as

24-h movement behaviorsLatent profile analysisPhysical activityPhysical fitnessPreschoolerSedentary behaviorSleep

Identifiers

PMID41732290
PMCPMC12925150

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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.