Abstract

Objective : To examine sex-specific nonlinear associations between anthropometric measures and physical fitness performance in Chinese college students, and to evaluate whether menstrual health indicators contribute to women’s fitness models. Methods : This cross-sectional study included 2,468 Chinese college students (men: 1,644; women: 824). Anthropometric measures (body mass index [BMI], waist-to-hip ratio [WHR], and arm span) were collected for all participants. Women additionally reported menstrual health characteristics, including age at menarche, cycle length, menstruation duration, menstrual regularity, dysmenorrhea, and severity of common menstrual symptoms (CMSS). Fitness performance was assessed using shared tests (50-m sprint, sit-and-reach, standing long jump) and sex-specific tests (men: pull-ups and 1,000-m run; women: one-minute sit-ups and 800-m run). For each fitness outcome, linear and quadratic regression models were compared using nested model tests; women’s models additionally included menstrual health indicators. Results: In men, quadratic models provided better fit than linear-only models across all fitness outcomes. BMI showed curvilinear associations with 50-m sprint and 1,000-m run times, with model-derived turning points around BMI ≈ 20.5 kg/m ² ; BMI also demonstrated nonlinear patterns for sit-and-reach (turning point ≈ 26.7), standing long jump ( ≈ 19.0), and pull-ups ( ≈ 18.2). WHR exhibited curvilinear associations with 50-m sprint, standing long jump, pull-ups, and sit-and-reach, with turning points clustered around WHR ≈ 0.73 – 0.76. Arm span showed a curvilinear association with sit-and-reach in men (turning point ≈ 171.5 cm). In women, evidence of nonlinearity was more selective: quadratic terms improved model fit for the 50-m sprint and 800-m run, with BMI turning points at ≈ 16.0 and ≈ 18.2, respectively, whereas linear models were adequate for sit-and-reach, standing long jump, and one-minute sit-ups. In women ’ s models, age at menarche showed a curvilinear association with 50-m sprint performance (turning point ≈ 12.2 years), and greater CMSS severity was independently associated with poorer one-minute sit-up performance. Conclusions: Anthropometric measures were associated with fitness performance in an outcome-specific and sex-dependent manner, with nonlinearity evident particularly in men and in women’s running outcomes. Menstrual health indicators contributed additional explanatory value in women, highlighting the importance of considering menstrual health when interpreting fitness performance and designing sex-sensitive health promotion strategies. Model-derived turning points should be interpreted within the observed data range and warrant confirmation in prospective and interventional studies.