Body fat estimation in the Mexican women's national soccer team: a cross-sectional agreement study between a derived Mexican Football Federation anthropometric equation and dual-energy X-ray absorptiometry.

内容摘要

Precise assessment of body composition is fundamental for monitoring training adaptations, guiding nutritional strategies, and informing performance-related decision-making in elite female soccer. Dual-energy X-ray absorptiometry (DXA) is considered a reference method; however, its limited accessibility restricts routine use in high-performance settings. Existing anthropometric equations often lack population-specific validation, particularly for elite Mexican female soccer players. This study aimed to derive and internally validate an anthropometric equation for estimating body fat percentage (%BF) and to evaluate its agreement with DXA. Twenty-seven elite players from the Mexican Women's National Team underwent DXA assessment and International Society for the Advancement of Kinanthropometry (ISAK)-standardized anthropometry during a training camp. Sample-size adequacy was assessed a posteriori. A multiple linear regression model was derived using the sum of eight skinfolds (Σ8SF) and waist girth (WG) as predictors. Regression assumptions were verified through residual diagnostics, and multicollinearity was assessed using variance inflation factors. Predictive performance was evaluated using mean absolute error (MAE), root mean square error (RMSE), and standard error of estimate (SEE). Agreement with DXA was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Internal validation was performed using leave-one-out cross-validation (LOOCV). The six historical anthropometric equations were additionally refitted to the present sample to enable a like-for-like comparison of predictor structures. The Mexican Footbal Federation equation (%BF = 0.12 × Σ8SF +0.39 × WG - 17.0) demonstrated moderate agreement with DXA (ICC = 0.71; mean bias: -0.05%; 95% LOA: -4.61% to +4.70%). The model explained 54% of the variance in DXA %BF (R² = 0.54; R²-adjusted = 0.50) and showed acceptable predictive performance (LOOCV Q² = 0.50; RMSE = 2.33%; MAE = 1.86%; SEE = 2.47%). After refitting each of the six historical anthropometric equations to the present sample, the Mexican Footbal Federation predictor combination retained the lowest RMSE (2.33% vs. 2.55-2.93%) and the highest ICC (0.71 vs. 0.44-0.63), supporting that the model's advantage stems from its predictor structure rather than calibration on the test data. The Mexican Football Federation equation provides a population-specific, field-applicable tool for estimating %BF in elite Mexican female soccer players. External validation in larger and more diverse cohorts is required before its widespread application.