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06.12.2024 | Invited Review

Anthropometric-based predictive equations developed with multi-component models for estimating body composition in athletes

verfasst von: Sofia Serafini, Davide Charrier, Pascal Izzicupo, Francisco Esparza-Ros, Raquel Vaquero-Cristóbal, Cristian Petri, Malek Mecherques-Carini, Nicolas Baglietto, Francis Holway, Grant Tinsley, Antonio Paoli, Francesco Campa

Erschienen in: European Journal of Applied Physiology

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Abstract

Purpose

Body composition can be estimated using anthropometric-based regression models, which are population-specific and should not be used interchangeably. However, the widespread availability of predictive equations in the literature makes selecting the most valid equations challenging. This systematic review compiles anthropometric-based predictive equations for estimating body mass components, focusing on those developed specifically for athletes using multicomponent models (i.e. separation of body mass into ≥ 3 components).

Methods

Twenty-nine studies published between 2000 and 2024 were identified through a systematic search of international electronic databases (PubMed and Scopus). Studies using substandard procedures or developing predictive equations for non-athletic populations were excluded.

Results

A total of 40 equations were identified from the 29 studies. Of these, 36 were applicable to males and 17 to females. Twenty-six equations were developed to estimate fat mass, 10 for fat-free mass, three for appendicular lean soft tissue, and one for skeletal muscle mass. Thirteen equations were designed for mixed athletes, while others focused on specific contexts: soccer (n = 8); handball and rugby (n = 3 each); jockeys, swimming, and Gaelic football (n = 2 each); and futsal, padel, basketball, volleyball, American football, karate, and wheelchair athletes (n = 1 each).

Conclusions

This review presented high-standards anthropometric-based predictive equations for assessing body composition in athletes and encourages the development of new equations for underrepresented sports in the current literature.

Graphical abstract

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Titel: Anthropometric-based predictive equations developed with multi-component models for estimating body composition in athletes
verfasst von: Sofia Serafini
Davide Charrier
Pascal Izzicupo
Francisco Esparza-Ros
Raquel Vaquero-Cristóbal
Cristian Petri
Malek Mecherques-Carini
Nicolas Baglietto
Francis Holway
Grant Tinsley
Antonio Paoli
Francesco Campa
Publikationsdatum: 06.12.2024
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Applied Physiology
Print ISSN: 1439-6319
Elektronische ISSN: 1439-6327
DOI: https://doi.org/10.1007/s00421-024-05672-3

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