Evidence map›Paper›PMID 40181250›Full record

ArticleBMC sports science, medicine & rehabilitation2025

Accuracy of anthropometric-based predictive equations for tracking fat mass over a competitive season in elite female soccer players: a validation study.

Giulia Baroncini, Francesco Campa, Priscilla Castellani Tarabini, Alberto Sala, Lorenzo Boldrini, Stefano Mazzoni, Antonio Paoli

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Article in BMC sports science, medicine & rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Giulia Baroncini *Milan Lab Department, AC Milan, Milan, Italy.
Francesco Campa *Department of Biomedical Sciences, University of Padua, Padua, Italy. Francesco.campa@unipd.it.
Priscilla Castellani TarabiniMilan Lab Department, AC Milan, Milan, Italy.
Alberto SalaMilan Lab Department, AC Milan, Milan, Italy.
Lorenzo BoldriniMilan Lab Department, AC Milan, Milan, Italy.
Stefano MazzoniMilan Lab Department, AC Milan, Milan, Italy.
Antonio PaoliDepartment of Biomedical Sciences, University of Padua, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsBody fat is a key body composition parameter monitored in soccer. Identifying reliable alternatives to laboratory techniques for assessing body fat during the competitive period is essential. This study aimed to evaluate the cross-sectional and longitudinal validity of anthropometric prediction equations in elite female soccer players.

methodsEighteen female soccer players (age: 26.6 [3.8] years; height: 168 [6.3] cm; body mass: 64.1 [7.4] kg; body mass index: 22.7 [1.9] kg/m²) from an Italian Serie A team were assessed at four time points during a competitive season. Fat mass was estimated using anthropometric equations by Evans and Warner and compared to dual-energy X-ray absorptiometry (DXA), which served as the reference method.

resultsCross-sectional agreement analysis revealed a bias of -4.5% with Warner's equation, while Evans's equation showed no bias compared to DXA, with coefficient of determination (R²) values of 0.69 and 0.70, respectively. Both methods showed a negative association (Evans: r = -0.53, Warner: r = -0.63) when the difference between the values and the mean with DXA were correlated. Longitudinal agreement analysis showed no significant differences in fat mass changes between the anthropometric equations and DXA, with R² values ranging from 0.68 to 0.83. The 95% limits of agreement between the methods for individual changes in fat mass ranged from - 3.3 to 3.2%. Furthermore, no significant changes (p > 0.05) in fat mass were observed over the season with any method.

conclusionsAt the group level, Evans's equation provides valid estimates of fat mass, whereas it may overestimate values in players with low body fat and underestimate them in those with high fat mass. The Warner equation showed the same trend as Evans at the individual level, also resulting in poor accuracy at the group level. Despite this, both anthropometric equations are valid alternatives to DXA for monitoring fat mass changes during the season, with Evans's equation showing superior overall performance.

Indexed as

AnthropometryBody compositionDXAFat massFemale athletesSoccer

Identifiers

PMID40181250
PMCPMC11967043

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