Volume 44 Issue 10
Oct.  2023
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Article Contents
FU Jinmei, HUANG Ting, SUN Shunli, CHEN Ruiming, CHEN Delong, JIANG Tianle, HU Xuewen, LYU Wendi, HE Zihao, SU Liqiang, ZHAO Guanggao, ZOU Weilu. Cluster characteristics of physical activities among children inside and outside kindergartens and its relationship with athletic abilities[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(10): 1560-1563. doi: 10.16835/j.cnki.1000-9817.2023.10.027
Citation: FU Jinmei, HUANG Ting, SUN Shunli, CHEN Ruiming, CHEN Delong, JIANG Tianle, HU Xuewen, LYU Wendi, HE Zihao, SU Liqiang, ZHAO Guanggao, ZOU Weilu. Cluster characteristics of physical activities among children inside and outside kindergartens and its relationship with athletic abilities[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2023, 44(10): 1560-1563. doi: 10.16835/j.cnki.1000-9817.2023.10.027

Cluster characteristics of physical activities among children inside and outside kindergartens and its relationship with athletic abilities

doi: 10.16835/j.cnki.1000-9817.2023.10.027
  • Received Date: 2023-05-15
  • Rev Recd Date: 2023-08-23
  • Available Online: 2023-10-27
  • Publish Date: 2023-10-25
  •   Objective  Based on physical activity (PA) and sedentary behavior (SB) variables on weekdays and weekends, the study aims to cluster the physical activities inside and outside kindergartens and to explore the cluster characteristics of different children using physical fitness indicators, so as to provide new strategies and methods for early childhood education and health.  Methods  From March to June 2019, 291 children aged 3-6 years from 6 kindergartens in Nanchang were recruited by a stratified cluster random sampling method. The ActiGraph GT3X-BT triaxial accelerometer was used to measure and analyze the PA and SB levels inside and outside the kindergarten. A two-step clustering algorithm model was employed for cluster analysis. Physical fitness were measured and evaluated according to the "National Physical Fitness Measurement Standard Manual (Preschool Section)". Differences in physical fitness among different clusters of children were compared, and the cluster characteristics of different children were analyzed.  Results  The clustering algorithm model indicated that based on six indicators, including PA and SB inside the kindergarten on weekdays, and PA and SB outside the kindergarten on both weekdays and weekends, children could be divided into three categories: active inside (high PA, low SB inside), active outside (high PA outside), and inactive (low PA, high SB both inside and outside). The average silhouette coefficient of the model was 0.3, indicating good clustering results. Both the active inside and active outside children showed significantly higher PA inside on weekdays, PA outside on weekdays and weekends, daily low-intensity physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) than the inactive children (F=157.91, 80.79, 95.86, 95.52, 124.74, P < 0.05). After adjusting for gender and age, the physical fitness scores of both active outside (19.03±0.47) and active inside (19.11±0.40) were significantly higher than those of the inactive children (17.94±0.31). Additionally, active inside children (3.91±0.14) also showed significantly better performance in continuous double-leg jumps, compared to inactive children (3.45±0.11) (P < 0.05).  Conclusion  Children active inside and those active outside perform well in PA. Future research should focus on the proportion of structured and unstructured PA time to enhance the overall physical fitness of children.
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