Literature DB >> 33487268

Relative fat mass is a better tool to diagnose high adiposity when compared to body mass index in young male adults: A cross-section study.

Cinthia Rejane Corrêa1, Natália Paludo Silveira Formolo2, Talissa Dezanetti3, Guilherme Fleury Fina Speretta4, Everson Araújo Nunes5.   

Abstract

BACKGROUND AND AIM: Relative fat mass (RFM) is a new method to estimate whole-body fat percentage in adults using an anthropometric linear equation. We aimed to assess the association between RFM and body fat (BF), evaluated by dual x-ray absorptiometry (DXA) or bioelectrical impedance (BIA), in young male adults.
METHODS: Eighty-one young males were assessed for BF fat and free fat mass (by BIA and DXA), waist circumference. BMI and RFM were then calculated from data collected from the subjects. The agreement between BMI and RFM or BIA/DXA was assessed by Pearson's Correlation and Kappa index. Univariate and multivariate linear regression were applied.
RESULTS: Analyzing all the participants together, the correlation between RFM and DXA (rDXA = 0.90) or RFM and BIA (rBIA = 0.88) were slightly higher than the correlation between BMI and DXA (rDXA = 0.79) or BMI and BIA (rBIA: 0.82). When analyzed by BF, low BF (LBF) individuals showed a much higher correlation with RFM (rDXA = 0.58; rBIA = 0.73) than BMI (rDXA = 0.24; rBIA: 0.46). However, subjects with excess BF (EBF) presented similar correlations when comparing RFM (rDXA = 0.80; rBIA = 0.64) and BMI (rDXA = 0.78; rBIA = 0.64). In general, RFM presented a higher strength of agreement with DXA and BIA (kDXA = 0.75; kBIA = 0.67) than BMI (kDXA = 0.63; kBIA = 0.60). Multivariable linear regression also revealed high associations between RFM and DXA or RFM and BIA (r2DXA = 0.85; r2BIA = 0.81).
CONCLUSION: Our findings suggest that RFM shows a good correlation and association with BF measured by DXA and BIA in young male adults. Furthermore, RFM seems to be better correlated to BF in LBF individuals when compared to BMI. Therefore, further studies investigating RFM as a tool to assess BF and obesity are motivated.
Copyright © 2020 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Adiposity; Anthropometric indicators; Body composition; Fat mass; RFM

Year:  2021        PMID: 33487268     DOI: 10.1016/j.clnesp.2020.12.009

Source DB:  PubMed          Journal:  Clin Nutr ESPEN        ISSN: 2405-4577


  3 in total

1.  Relative fat mass assessment estimates changes in adiposity among female older adults with obesity after a 12-month exercise and diet intervention.

Authors:  Katelyn E Senkus; Kristi M Crowe-White; Julie L Locher; Jamy D Ard
Journal:  Ann Med       Date:  2022-12       Impact factor: 5.348

2.  Development and Validation of a Novel Waist Girth-Based Equation to Estimate Fat Mass in Young Colombian Elite Athletes (F20CA Equation): A STROSA-Based Study.

Authors:  Diego A Bonilla; Leidy T Duque-Zuluaga; Laura P Muñoz-Urrego; Katherine Franco-Hoyos; Alejandra Agudelo-Martínez; Maximiliano Kammerer-López; Jorge L Petro; Richard B Kreider
Journal:  Nutrients       Date:  2022-09-29       Impact factor: 6.706

3.  Changes in Novel Anthropometric Indices of Abdominal Obesity during Weight Loss with Selected Obesity-Associated Single-Nucleotide Polymorphisms: A Small One-Year Pilot Study.

Authors:  Katarzyna Iłowiecka; Paweł Glibowski; Justyna Libera; Wojciech Koch
Journal:  Int J Environ Res Public Health       Date:  2022-09-19       Impact factor: 4.614

  3 in total

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