Development of an Anthropometric Prediction Model for Fat-Free Mass and Muscle Mass in Elite Athletes

Erik Sesbreno; Gary J Slater; Margo Mountjoy; Stuart D R Galloway

doi:10.1123/ijsnem.2019-0232

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Development of an Anthropometric Prediction Model for Fat-Free Mass and Muscle Mass in Elite Athletes

Journal article

Peer reviewed

Development of an Anthropometric Prediction Model for Fat-Free Mass and Muscle Mass in Elite Athletes

Erik Sesbreno, Gary J Slater, Margo Mountjoy and Stuart D R Galloway

International Journal of Sport Nutrition and Exercise Metabolism, Vol.30(2), pp.174-181

2020

DOI: https://doi.org/10.1123/ijsnem.2019-0232

PMID: 32045882

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Abstract

Human Movement and Sports Science

Medical Physiology

body composition

dual-energy X-ray absorptiometry

DXA

fat mass

sports

The monitoring of body composition is common in sports given the association with performance. Surface anthropometry is often preferred when monitoring changes for its convenience, practicality, and portability. However, anthropometry does not provide valid estimates of absolute lean tissue in elite athletes. The aim of this investigation was to develop anthropometric models for estimating fat-free mass (FFM) and skeletal muscle mass (SMM) using an accepted reference physique assessment technique. Sixty-four athletes across 18 sports underwent surface anthropometry and dual-energy X-ray absorptiometry (DXA) assessment. Anthropometric models for estimating FFM and SMM were developed using forward selection multiple linear regression analysis and contrasted against previously developed equations. Most anthropometric models under review performed poorly compared with DXA. However, models derived from athletic populations such as the Withers equation demonstrated a stronger correlation with DXA estimates of FFM (r = .98). Equations that incorporated skinfolds with limb girths were more effective at explaining the variance in DXA estimates of lean tissue (Sesbreno FFM [R2 = .94] and Lee SMM [R2 = .94] models). The Sesbreno equation could be useful for estimating absolute indices of lean tissue across a range of physiques if an accepted option like DXA is inaccessible. Future work should explore the validity of the Sesbreno model across a broader range of physiques common to athletic populations.

Details

Title: Development of an Anthropometric Prediction Model for Fat-Free Mass and Muscle Mass in Elite Athletes
Authors: Erik Sesbreno (Author) - Canadian Sport Institute Ontario, Canada
Gary J Slater (Author) - University of the Sunshine Coast - School of Health and Sport Sciences
Margo Mountjoy (Author) - University of Guelph, Canada
Stuart D R Galloway (Author) - University of Stirling, United Kingdom
Publication details: International Journal of Sport Nutrition and Exercise Metabolism, Vol.30(2), pp.174-181
Publisher: Human Kinetics
Date published: 2020
DOI: 10.1123/ijsnem.2019-0232
ISSN: 1526-484X
PMID: 32045882
Organisation Unit: University of the Sunshine Coast, Queensland; School of Health - Nutrition & Dietetics; School of Health and Sport Sciences - Legacy; School of Health and Behavioural Sciences - Legacy
Language: English
Record Identifier: 99450814302621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Nutrition & Dietetics; Sport Sciences

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