Frontiers in public health · 2026
Association between body mass index and physical fitness index among middle and high school students aged 13-18 in Shanxi Province: a cross-sectional study.
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Zhou Shaochen, Zhao Dingyu, Luo Hao
Аннотация
OBJECTIVE: To investigate the relationship between Body Mass Index (BMI) and Physical Fitness Index (PFI) among middle and high school students aged 13-18 in Shanxi Province, and to provide a reference for adolescent physical health promotion.
METHODS: A total of 3,600 middle and high school students aged 13-18 (1,800 boys and 1,800 girls) from Shanxi Province who participated in the 2025 National Physical Fitness and Health Survey were selected as the study subjects. They were divided into underweight, normal weight, overweight, and obese groups based on the Chinese screening standards for overweight, obesity, and malnutrition in school-age children and adolescents. The Z-score method was used to calculate the Z-scores for each physical fitness indicator, which were then summed to obtain the Physical Fitness Index (PFI), comprehensively reflecting physical fitness status. Differences in physical fitness indicators among students of different genders and different BMI groups were compared, and the association between BMI and PFI was examined using a quadratic polynomial regression model, in which age was included as a covariate and BMI was centered to minimize multicollinearity.
RESULTS: Analysis of data from middle and high school students aged 13-18 revealed significant differences in PFI among different BMI groups (P < 0.05). The normal weight group had the highest PFI (boys: 0.37 ± 3.61, girls: 0.15 ± 3.33), while the underweight and obese groups had significantly lower PFI. BMI and PFI showed an inverted "U"-shaped distribution. Furthermore, except for vital capacity and grip strength, most physical fitness indicators were optimal in the normal weight group. Overweight and obese groups performed poorly in endurance running and standing long jump, among other events. With increasing age, BMI and most physical fitness indicators significantly improved (P < 0.01). Gender comparison showed boys had advantages in strength and explosive power events, while girls had better flexibility, with significant differences (P < 0.01). Regression analysis showed that, after controlling for age, the regression coefficient of BMI_C2 was negative (boys: B = -0.036, P < 0.01; girls: B = -0.026, P < 0.01), indicating that PFI is a quadratic function of BMI, with PFI first increasing and then decreasing as BMI increases.
CONCLUSION: Based on the 2025 physical fitness survey data from Shanxi Province, this study found an inverted U-shaped association between BMI and PFI among middle and high school students aged 13-18, with the normal weight range corresponding to the peak PFI, while both underweight and overweight/obesity were associated with lower PFI. This association remained significant after controlling for age, but had limited explanatory power in girls. It is recommended that school physical education programs address both underweight and overweight/obese students with targeted interventions, and consider gender differences when developing intervention strategies. Future studies should include variables such as physical activity, dietary habits, and body fat percentage, and adopt longitudinal designs to verify the directionality of the association.
METHODS: A total of 3,600 middle and high school students aged 13-18 (1,800 boys and 1,800 girls) from Shanxi Province who participated in the 2025 National Physical Fitness and Health Survey were selected as the study subjects. They were divided into underweight, normal weight, overweight, and obese groups based on the Chinese screening standards for overweight, obesity, and malnutrition in school-age children and adolescents. The Z-score method was used to calculate the Z-scores for each physical fitness indicator, which were then summed to obtain the Physical Fitness Index (PFI), comprehensively reflecting physical fitness status. Differences in physical fitness indicators among students of different genders and different BMI groups were compared, and the association between BMI and PFI was examined using a quadratic polynomial regression model, in which age was included as a covariate and BMI was centered to minimize multicollinearity.
RESULTS: Analysis of data from middle and high school students aged 13-18 revealed significant differences in PFI among different BMI groups (P < 0.05). The normal weight group had the highest PFI (boys: 0.37 ± 3.61, girls: 0.15 ± 3.33), while the underweight and obese groups had significantly lower PFI. BMI and PFI showed an inverted "U"-shaped distribution. Furthermore, except for vital capacity and grip strength, most physical fitness indicators were optimal in the normal weight group. Overweight and obese groups performed poorly in endurance running and standing long jump, among other events. With increasing age, BMI and most physical fitness indicators significantly improved (P < 0.01). Gender comparison showed boys had advantages in strength and explosive power events, while girls had better flexibility, with significant differences (P < 0.01). Regression analysis showed that, after controlling for age, the regression coefficient of BMI_C2 was negative (boys: B = -0.036, P < 0.01; girls: B = -0.026, P < 0.01), indicating that PFI is a quadratic function of BMI, with PFI first increasing and then decreasing as BMI increases.
CONCLUSION: Based on the 2025 physical fitness survey data from Shanxi Province, this study found an inverted U-shaped association between BMI and PFI among middle and high school students aged 13-18, with the normal weight range corresponding to the peak PFI, while both underweight and overweight/obesity were associated with lower PFI. This association remained significant after controlling for age, but had limited explanatory power in girls. It is recommended that school physical education programs address both underweight and overweight/obese students with targeted interventions, and consider gender differences when developing intervention strategies. Future studies should include variables such as physical activity, dietary habits, and body fat percentage, and adopt longitudinal designs to verify the directionality of the association.