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24-Hour Movement Behavior and Health-Related Physical Fitness in College Students: A Compositional Data Analysis.

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Title: 24-Hour Movement Behavior and Health-Related Physical Fitness in College Students: A Compositional Data Analysis.
Authors: Yang, Qiushi (AUTHOR), Wang, Junli (AUTHOR), Bai, Jianfei (AUTHOR)
Source: International Journal of Behavioral Medicine. Jun2026, Vol. 33 Issue 3, p441-451. 11p.
Subjects: Cross-sectional method, Health status indicators, Research funding, Human beings, Statistical sampling, Questionnaires, Descriptive statistics, Screen time, Dose-response relationship in biochemistry, Surveys, Health behavior, Physical fitness, Sleep, Body movement, College students, Confidence intervals, Data analysis software, Health promotion, Time, Regression analysis, Physical activity
Geographic Terms: China
Abstract: Background: Sedentary behavior and physical inactivity are primary factors contributing to college students' continued decline in health-related physical fitness (HRPF). This study aims to examine the associations between 24-h movement behavior and HRPF, and explore the dose–response relationship between the reallocation of movement behavior time and HRPF. Method: In total, 1032 college students (649 males and 383 females) aged 19.5 years from China University of Mining and Technology were recruited to participate in the study in October 2023. The 24-h movement behavior was measured using reliable items from the 24-h Movement Behavior Questionnaire (reliability coefficients 0.68 to 0.97). HRPF was assessed using the Fitness Test Battery, which measures BMI, vital capacity, sit-and-reach, stand-long-jump, pull-up/crunches, 50-m sprint, and the 800/1000-m run. The isotemporal substitution model was applied to evaluate the health effects of different movement components. Results: The 24-h movement behavior significantly influenced HRPF (p < 0.01, R2 = 0.16). A positive correlation was found between HRPF and the proportion of moderate-to-vigorous physical activity (MVPA) (βMVPA = 1.03, p < 0.01) and learning sedentary (LSED) (βLSED = 2.41, p < 0.05), while a negative correlation existed with sleep (βSLP = − 3.52, p < 0.01). Significant reallocations of 30 min from sleep to MVPA (+ 0.57, p < 0.05) and from screening sedentary (SSED) to MVPA (+ 0.39, p < 0.05) were observed. No significant associations were found between HRPF and reallocating from light-intensity physical activity to MVPA. Conclusion: In addition to MVPA, it is important to consider the health risks associated with SSED and excessive sleep and to maintain a balanced time structure of 24-h movement behavior to promote health. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Behavioral Medicine is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Background: Sedentary behavior and physical inactivity are primary factors contributing to college students&#39; continued decline in health-related physical fitness (HRPF). This study aims to examine the associations between 24-h movement behavior and HRPF, and explore the dose–response relationship between the reallocation of movement behavior time and HRPF. Method: In total, 1032 college students (649 males and 383 females) aged 19.5 years from China University of Mining and Technology were recruited to participate in the study in October 2023. The 24-h movement behavior was measured using reliable items from the 24-h Movement Behavior Questionnaire (reliability coefficients 0.68 to 0.97). HRPF was assessed using the Fitness Test Battery, which measures BMI, vital capacity, sit-and-reach, stand-long-jump, pull-up/crunches, 50-m sprint, and the 800/1000-m run. The isotemporal substitution model was applied to evaluate the health effects of different movement components. Results: The 24-h movement behavior significantly influenced HRPF (p &lt; 0.01, R2 = 0.16). A positive correlation was found between HRPF and the proportion of moderate-to-vigorous physical activity (MVPA) (βMVPA = 1.03, p &lt; 0.01) and learning sedentary (LSED) (βLSED = 2.41, p &lt; 0.05), while a negative correlation existed with sleep (βSLP = − 3.52, p &lt; 0.01). Significant reallocations of 30 min from sleep to MVPA (+ 0.57, p &lt; 0.05) and from screening sedentary (SSED) to MVPA (+ 0.39, p &lt; 0.05) were observed. No significant associations were found between HRPF and reallocating from light-intensity physical activity to MVPA. Conclusion: In addition to MVPA, it is important to consider the health risks associated with SSED and excessive sleep and to maintain a balanced time structure of 24-h movement behavior to promote health. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of International Journal of Behavioral Medicine is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s12529-025-10360-3
    Languages:
      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 441
    Subjects:
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: Health status indicators
        Type: general
      – SubjectFull: Research funding
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      – SubjectFull: Human beings
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      – SubjectFull: Statistical sampling
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      – SubjectFull: Questionnaires
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Dose-response relationship in biochemistry
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      – SubjectFull: Health behavior
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      – SubjectFull: Physical fitness
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      – SubjectFull: College students
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      – SubjectFull: Confidence intervals
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      – SubjectFull: Physical activity
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      – SubjectFull: China
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      – TitleFull: 24-Hour Movement Behavior and Health-Related Physical Fitness in College Students: A Compositional Data Analysis.
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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