Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study
Objectives: This study aimed to investigate the factors associated with physical fitness and disparities in population segments among older adults, using data from the National Physical Fitness Surveilling Survey of China. Study design: A cross-sectional study. Methods: A total of 13524 older adults...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Journal of Exercise Science & Fitness |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1728869X25000012 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832087855933947904 |
|---|---|
| author | Yuqin Rao Jingjing Wang Kai Li Fanhui Zheng Ying Chen Bo Zhai Jintao Hong Chen Wang Bao Liu Dao Wang |
| author_facet | Yuqin Rao Jingjing Wang Kai Li Fanhui Zheng Ying Chen Bo Zhai Jintao Hong Chen Wang Bao Liu Dao Wang |
| author_sort | Yuqin Rao |
| collection | DOAJ |
| description | Objectives: This study aimed to investigate the factors associated with physical fitness and disparities in population segments among older adults, using data from the National Physical Fitness Surveilling Survey of China. Study design: A cross-sectional study. Methods: A total of 13524 older adults aged 60–79 years were involved in the study. Participants completed physical fitness assessments encompassing body fat percentage, lung capacity, high leg raise in place, grip strength, seated forward bending, 30-s sit-to-stand test, single-leg standing with eyes closed, and choice reaction time. A profile analysis model was constructed by feature extraction, label design and clustering using principal component analysis and k-prototypes. Factors associated with physical fitness were analyzed using ordered probit regression, and within-group differences were evaluated through the bootstrap method. Results: The older adults were categorized into four clusters based on the clustering results (Cluster I: n = 2728, Cluster II: n = 6067, Cluster III: n = 4189, Cluster IV: n = 540). Significant positive associations were identified between moderate-to-vigorous transport-related activities (α = 0.001, p < 0.05), moderate-to-vigorous household chores (α = 0.003, p < 0.01), work-related physical activity (α = 0.001, p < 0.01), exercise (α = 0.002, p < 0.01) and physical fitness levels. Conversely, the number of illnesses (α = -0.089, p < 0.01) and sedentary behavior (α = -0.002, p < 0.05) were negatively associated with physical fitness. Inflection points were observed, indicating shifts from lower level to higher physical fitness levels as the volume of diverse moderate-to-vigorous physical activities increased. Disparities in factors associated with physical fitness were identified across the different clusters. The associations of household chores, transport-related activities, and work-related physical activity with physical fitness lacked robustness during heterogeneity processing. In contrast, exercise consistently demonstrated a facilitating role across all clusters. Furthermore, greater marginal effects on achieving higher physical fitness test scores were observed among individuals classified as inactive when engaging in more moderate-to-vigorous activities and exercise. Conclusion: The findings demonstrate that engagement in moderate-to-vigorous physical activities and exercise is associated with a significantly higher probability of achieving better physical fitness among older adults. Participating in physical activities and exercise should be encouraged based on population segments for precise and quantitative interventions to improve physical fitness. |
| format | Article |
| id | doaj-art-e5edd58b14334f448496ab277751e95f |
| institution | Kabale University |
| issn | 1728-869X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Exercise Science & Fitness |
| spelling | doaj-art-e5edd58b14334f448496ab277751e95f2025-02-06T05:11:24ZengElsevierJournal of Exercise Science & Fitness1728-869X2025-01-012316976Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional studyYuqin Rao0Jingjing Wang1Kai Li2Fanhui Zheng3Ying Chen4Bo Zhai5Jintao Hong6Chen Wang7Bao Liu8Dao Wang9Department of Health Economics, School of Public Health, Fudan University, 130 Dong'an Road, Shanghai, 200032, China; Key Laboratory of Health Technology Assessment (Fudan University), National Health Commission, 130 Dong'an Road, Shanghai, 200032, ChinaShanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, ChinaDepartment of Health Economics, School of Public Health, Fudan University, 130 Dong'an Road, Shanghai, 200032, China; Key Laboratory of Health Technology Assessment (Fudan University), National Health Commission, 130 Dong'an Road, Shanghai, 200032, ChinaShanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, ChinaShanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, ChinaShanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, ChinaShanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, ChinaShanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, China; Corresponding author.Department of Health Economics, School of Public Health, Fudan University, 130 Dong'an Road, Shanghai, 200032, China; Key Laboratory of Health Technology Assessment (Fudan University), National Health Commission, 130 Dong'an Road, Shanghai, 200032, China; Corresponding author. Department of Health Economics, School of Public Health, Fudan University, 130 Dong'an Road, Shanghai, 200032, China.Shanghai Research Institute of Sports Science (SHRlSS), No. 87, Wuxing Road, Shanghai, 200031, China; Corresponding author.Objectives: This study aimed to investigate the factors associated with physical fitness and disparities in population segments among older adults, using data from the National Physical Fitness Surveilling Survey of China. Study design: A cross-sectional study. Methods: A total of 13524 older adults aged 60–79 years were involved in the study. Participants completed physical fitness assessments encompassing body fat percentage, lung capacity, high leg raise in place, grip strength, seated forward bending, 30-s sit-to-stand test, single-leg standing with eyes closed, and choice reaction time. A profile analysis model was constructed by feature extraction, label design and clustering using principal component analysis and k-prototypes. Factors associated with physical fitness were analyzed using ordered probit regression, and within-group differences were evaluated through the bootstrap method. Results: The older adults were categorized into four clusters based on the clustering results (Cluster I: n = 2728, Cluster II: n = 6067, Cluster III: n = 4189, Cluster IV: n = 540). Significant positive associations were identified between moderate-to-vigorous transport-related activities (α = 0.001, p < 0.05), moderate-to-vigorous household chores (α = 0.003, p < 0.01), work-related physical activity (α = 0.001, p < 0.01), exercise (α = 0.002, p < 0.01) and physical fitness levels. Conversely, the number of illnesses (α = -0.089, p < 0.01) and sedentary behavior (α = -0.002, p < 0.05) were negatively associated with physical fitness. Inflection points were observed, indicating shifts from lower level to higher physical fitness levels as the volume of diverse moderate-to-vigorous physical activities increased. Disparities in factors associated with physical fitness were identified across the different clusters. The associations of household chores, transport-related activities, and work-related physical activity with physical fitness lacked robustness during heterogeneity processing. In contrast, exercise consistently demonstrated a facilitating role across all clusters. Furthermore, greater marginal effects on achieving higher physical fitness test scores were observed among individuals classified as inactive when engaging in more moderate-to-vigorous activities and exercise. Conclusion: The findings demonstrate that engagement in moderate-to-vigorous physical activities and exercise is associated with a significantly higher probability of achieving better physical fitness among older adults. Participating in physical activities and exercise should be encouraged based on population segments for precise and quantitative interventions to improve physical fitness.http://www.sciencedirect.com/science/article/pii/S1728869X25000012Physical fitnessProfile analysis modelPopulation segmentsOlder adults |
| spellingShingle | Yuqin Rao Jingjing Wang Kai Li Fanhui Zheng Ying Chen Bo Zhai Jintao Hong Chen Wang Bao Liu Dao Wang Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study Journal of Exercise Science & Fitness Physical fitness Profile analysis model Population segments Older adults |
| title | Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study |
| title_full | Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study |
| title_fullStr | Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study |
| title_full_unstemmed | Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study |
| title_short | Factors associated with physical fitness and disparities in population segments among older adults: A cross-sectional study |
| title_sort | factors associated with physical fitness and disparities in population segments among older adults a cross sectional study |
| topic | Physical fitness Profile analysis model Population segments Older adults |
| url | http://www.sciencedirect.com/science/article/pii/S1728869X25000012 |
| work_keys_str_mv | AT yuqinrao factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT jingjingwang factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT kaili factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT fanhuizheng factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT yingchen factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT bozhai factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT jintaohong factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT chenwang factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT baoliu factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy AT daowang factorsassociatedwithphysicalfitnessanddisparitiesinpopulationsegmentsamongolderadultsacrosssectionalstudy |