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Vol. 5 No. 1 (2025): Volume 5, Issue 1, Year 2025

Articles

Development and Validation of A New Anthropometric Predictive Equation For Estimating Fat Mass In Elite Male Soccer Players

  • Francesco Campa,
  • Alessio Rossi,
  • Giulia Martera,
  • Athos Trecroci,
  • Tindaro Bongiovanni
Francesco Campa
Department of Biomedical Sciences, University of Padua, Padua, Italy
Alessio Rossi
Computer Science, University of Pisa, Pisa, Italy and National Research Council (CNR), Institute of Information Science and Technologies (ISTI), Pisa, Italy
Giulia Martera
Department of Performance Nutrition, Spezia Calcio, La Spezia, Italy
Athos Trecroci
Department of Biomedical Science for Health, University of Milan, Milan, Italy
Tindaro Bongiovanni
Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
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DOI: https://doi.org/10.34256/ijk2519

Published 14-04-2025

Keywords

  • Anthropometry,
  • Body Composition,
  • Body Fat,
  • DXA,
  • Sport,
  • Skinfolds
    • ...More
    Less

How to Cite

Campa, F., Rossi, A., Martera, G., Trecroci, A., & Bongiovanni, T. (2025). Development and Validation of A New Anthropometric Predictive Equation For Estimating Fat Mass In Elite Male Soccer Players. International Journal of Kinanthropometry, 5(1), 83–94. https://doi.org/10.34256/ijk2519

Copyright (c) 2025 Francesco Campa, Alessio Rossi, Giulia Martera, Athos Trecroci, Tindaro Bongiovanni

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Abstract

Introduction: The present study aimed i) to develop and validate an anthropometric soccer-specific equation for predicting fat mass (FM) using dual energy X-ray absorptiometry (DXA) as a reference method; ii) to assess the performance of existing soccer-specific predictive equations. Methods: Eighty male soccer players (aged 24.4±5.4 years, BMI 23.7±1.2 kg/m2) participating in the first Italian league underwent anthropometric measurements and DXA scan during the in-season period. The participants were divided into development and validation groups. The validation group returned for a second assessment three months later and was included in an analysis of longitudinal validity. Results: The best developed model was: FM (kg)= -9.905 + (sum of triceps, iliac crest, abdominal, and front thigh skinfolds (mm) × 0.175) + (thigh girth (cm) × 0.258) - (ethnicity × 1.577) - (age (years) × 0.068), R2=0.73, standard error of estimation (SEE)=1.01 kg, where ethnicity is 1 for black and 0 for white. Cross-sectional validation showed r2 values ranging from 0.71 to 0.72 with SEE equal to 0.80 kg and 0.86 kg for the baseline and the second assessments, respectively. Concordance correlation coefficients (CCC) were 0.84 at baseline and 0.86 at the second visit. The agreement analysis showed no mean bias at any time (p>0.05) and lower 95% limits of agreement (LoA) ranging from -1.5 kg to 1.8 kg. Longitudinal validation demonstrated a high accuracy at both group (r2= 0.80, SEE= 0.37 kg, CCC= 0.90) and individual (mean bias= 0.04 kg, 95%LoA= -0.7 kg to 0.8 kg, r= 0.117) levels. In contrast, the FM estimated from existing predictive equations differed from DXA for all the cross-sectional and longitudinal assessments, showing less accuracy compared to the new equation. Conclusions: This study presents a new soccer-specific predictive equation based on four skinfolds and a girth, allowing for a valid and sport-specific assessment of FM across the competitive season.

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