Frontiers in public health · 2026
Between-class variation and compositional correlates of physical fitness, and the concordance of composite scores with BMI-defined abnormality: a multilevel analysis of annual surveillance records from one Chinese university.
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Bu Yan, Zhu Junhui, Zhao Mingling, Xu Ling, Song Zhongming
Аннотация
INTRODUCTION: This repeated cross-sectional retrospective study examined between-class variation in university students' physical-fitness scores and whether annual composite-score trends were concordant with changes in BMI-defined abnormality.
METHODS: Annual surveillance records collected from 2020 to 2024 at one public university in Sichuan Province, China, were analysed. The dataset included 106,461 records from 2,591 class-year units (44,240 male, 62,221 female; mean age 20.67 ± 1.54 years; mean BMI 21.64 ± 3.52 kg/m2). Multilevel models quantified between-class variation and examined individual- and class-compositional correlates, with calendar year entered categorically. A complementary temporal analysis compared annual composite scores with the prevalence of underweight, overweight, or obesity using Chinese national cut-points.
RESULTS: The null-model intraclass correlation coefficient was 0.178, indicating meaningful between-class clustering. After adjustment, higher within-class BMI, older age, and male sex were associated with lower composite scores. At the class level, higher mean BMI was associated with lower scores, whereas the class-size association was statistically significant but practically negligible. The within-class BMI-fitness association varied across class-year units, although heterogeneity was modest and the association was negative in almost all units. Composite scores increased in 2021, declined in 2022, and increased again in 2023-2024. In contrast, BMI-defined abnormality rose every year, from 23.3% in 2020 to 31.4% in 2024.
DISCUSSION: University fitness data have a meaningful clustered structure, and improvement in a weighted composite score does not necessarily imply parallel improvement in the BMI distribution. Surveillance reports should therefore account for clustering and present composite scores alongside BMI categories and component-specific outcomes.
METHODS: Annual surveillance records collected from 2020 to 2024 at one public university in Sichuan Province, China, were analysed. The dataset included 106,461 records from 2,591 class-year units (44,240 male, 62,221 female; mean age 20.67 ± 1.54 years; mean BMI 21.64 ± 3.52 kg/m2). Multilevel models quantified between-class variation and examined individual- and class-compositional correlates, with calendar year entered categorically. A complementary temporal analysis compared annual composite scores with the prevalence of underweight, overweight, or obesity using Chinese national cut-points.
RESULTS: The null-model intraclass correlation coefficient was 0.178, indicating meaningful between-class clustering. After adjustment, higher within-class BMI, older age, and male sex were associated with lower composite scores. At the class level, higher mean BMI was associated with lower scores, whereas the class-size association was statistically significant but practically negligible. The within-class BMI-fitness association varied across class-year units, although heterogeneity was modest and the association was negative in almost all units. Composite scores increased in 2021, declined in 2022, and increased again in 2023-2024. In contrast, BMI-defined abnormality rose every year, from 23.3% in 2020 to 31.4% in 2024.
DISCUSSION: University fitness data have a meaningful clustered structure, and improvement in a weighted composite score does not necessarily imply parallel improvement in the BMI distribution. Surveillance reports should therefore account for clustering and present composite scores alongside BMI categories and component-specific outcomes.