Frontiers in medicine · 2026
Hierarchical regression analysis of physical fitness and BMI in primary school students in Sichuan Province.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Zhang Defa, Zhao Wennan, Wu Jingtao, Hu Jun, Zhao Xinjuan
Аннотация
BACKGROUND: The increasing prevalence of childhood obesity has made Body Mass Index (BMI) a crucial indicator for assessing children's physical health. Despite extensive research, the correlation between BMI and physical fitness among China's ethnically diverse youth remains poorly understood. This study investigates the associations between BMI and physical fitness indicators among primary school students in Sichuan Province, with particular attention to differences by gender, ethnicity, and age.
METHODS: The study analyzed physical fitness data from 36,092 primary school students aged 7-12 in Sichuan Province. Multivariate analysis of variance, correlation analysis, and hierarchical multiple regression analysis were employed to examine the associations between BMI and physical fitness indicators. Because data on several potential confounders, including diet, socioeconomic status, physical activity, and sleep, were unavailable, these variables were not included in the adjusted models.
RESULTS: The study revealed significant differences in BMI across different ethnicities, genders, and age groups. Han students had an average BMI of 17.07, which was significantly higher than the Yi students' average of 16.90 (F = 31.942, p < 0.001); boys had an average BMI of 17.18, significantly higher than girls' average of 16.85 (F = 131.733, p < 0.001); BMI increased significantly with age, with the 12-year-old group having the highest average (M = 18.08). BMI was negatively correlated with 50-meter run performance (r = -0.266, p < 0.01) and lung capacity (r = -0.186, p < 0.01). Hierarchical regression analysis showed that several demographic variables, physical fitness indicators, and interaction terms were statistically associated with BMI; however, most effect sizes were small, and the final model explained only a modest proportion of BMI variance (R 2 = 0.110).
CONCLUSION: BMI in primary school students in Sichuan Province was significantly associated with gender, ethnicity, age, and multiple physical fitness indicators. However, because several potential confounding variables were not adjusted for, these findings should be interpreted cautiously as observational associations. The findings provide context-specific evidence that may inform future hypothesis-driven research and regionally targeted public health planning; however, given the generally small effect sizes, their practical significance at the individual level may be limited.
METHODS: The study analyzed physical fitness data from 36,092 primary school students aged 7-12 in Sichuan Province. Multivariate analysis of variance, correlation analysis, and hierarchical multiple regression analysis were employed to examine the associations between BMI and physical fitness indicators. Because data on several potential confounders, including diet, socioeconomic status, physical activity, and sleep, were unavailable, these variables were not included in the adjusted models.
RESULTS: The study revealed significant differences in BMI across different ethnicities, genders, and age groups. Han students had an average BMI of 17.07, which was significantly higher than the Yi students' average of 16.90 (F = 31.942, p < 0.001); boys had an average BMI of 17.18, significantly higher than girls' average of 16.85 (F = 131.733, p < 0.001); BMI increased significantly with age, with the 12-year-old group having the highest average (M = 18.08). BMI was negatively correlated with 50-meter run performance (r = -0.266, p < 0.01) and lung capacity (r = -0.186, p < 0.01). Hierarchical regression analysis showed that several demographic variables, physical fitness indicators, and interaction terms were statistically associated with BMI; however, most effect sizes were small, and the final model explained only a modest proportion of BMI variance (R 2 = 0.110).
CONCLUSION: BMI in primary school students in Sichuan Province was significantly associated with gender, ethnicity, age, and multiple physical fitness indicators. However, because several potential confounding variables were not adjusted for, these findings should be interpreted cautiously as observational associations. The findings provide context-specific evidence that may inform future hypothesis-driven research and regionally targeted public health planning; however, given the generally small effect sizes, their practical significance at the individual level may be limited.