Evidence mapPaperPMID 40045271Full record

ArticleBMC public health2025

Association between daily movement behaviors and optimal physical fitness of university students: a compositional data analysis.

Jiayu Li, Zhendiao Lin, Mengting Zou, Xin Feng, Yuanyue Liu

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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Jiayu Li *College of Teacher Education, Zhejiang Normal University, Jinhua, China.
Zhendiao Lin *College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, China.
Mengting ZouCollege of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, China.
Xin FengSchool of Physical Education, Wuhan University of Technology, Wuhan, China.
Yuanyue LiuCollege of Teacher Education, Zhejiang Normal University, Jinhua, China. yyliu@zjnu.cn.

Funding

The Provincial Teaching Research Program for Higher Education Institutions in Hubei Province Project No.2022123
6 · The paper itself

Abstract

objectiveThis study investigates the relationship between movement behaviors and physical fitness (PF) in university students, and based on the top 5% of model-predicted outcomes for PF to determine the optimal movement behaviors balance.

methodsA total of 463 university students aged 15-24 years from Jinhua City wore accelerometers to measure moderate-to-vigorous physical activity (MVPA), light-intensity physical activity (LPA), and sedentary behavior (SB). Sleep (SLP) was self-reported. The body mass index (BMI), forced vital capacity (FVC), 50-meter dash, standing long jump, sit-and-reach, sit-ups (female), pull-ups (male), 800-meter run (female), and 1000-meter run (male) were used as indicators to assess the physical fitness of university students. Regression analysis was used to examine the relationship between movement behaviors and PF. All possible movement component combinations were investigated to determine the best correlation (top 5%) with each outcome.

resultsFor males, SB (β = 5.05, p < 0.05) was significantly correlated with an increase in BMI. MVPA was significantly correlated with improvements in BMI (β = -1.75, p < 0.05), FVC (β = 494.21, p < 0.05), and endurance qualities (β = -25.77, p < 0.05). For females, MVPA was significantly correlated with improvements in BMI (β = -1.03, p < 0.05), FVC (β = 176.05, p < 0.05), speed capability (β = -0.26, p < 0.05), and endurance qualities (β = -16.38, p < 0.05). LPA was associated with improvements in endurance qualities (β = -24.10, p < 0.05). SB was significantly correlated with a decline in endurance qualities (β = 24.25, p < 0.05). The average (range) optimal combination of time use was as follows: For males, MVPA = 142 min/day, SB = 534 min/day, LPA = 295 min/day, and SLP = 469 min/day. For females, MVPA = 115 min/day, SB = 536 min/day, LPA = 306 min/day, and SLP = 482 min/day.

conclusionFor both males and females, increased MVPA and reduced sedentary time were associated with improved endurance and strength, while optimal sleep duration contributed to overall fitness. These findings highlight the importance of a balanced daily movement schedule for university students.

Indexed as

ExercisePhysical FitnessStudentsAccelerometryAdolescentBody Mass IndexChinaData AnalysisFemaleHumansMaleSedentary BehaviorUniversitiesYoung AdultCompositional data analysisIsotemporal substitutionMovement behaviorsPhysical fitnessStudents

Identifiers

PMID40045271
PMCPMC11884011

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LicenceCC BY-NC-ND
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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 Socratic graph.