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A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study

BACKGROUND: Dual-energy X-ray absorptiometry (DXA) provides separate measurements of fat mass, fat-free mass and bone mass, and is a quick, accurate, and safe technique, yet one that is not readily available in routine clinical practice. Consequently, we aimed to develop statistical formulas to pred...

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Autores principales: Cortés-Castell, Ernesto, Juste, Mercedes, Palazón-Bru, Antonio, Monge, Laura, Sánchez-Ferrer, Francisco, Rizo-Baeza, María Mercedes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410155/
https://www.ncbi.nlm.nih.gov/pubmed/28462041
http://dx.doi.org/10.7717/peerj.3238
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author Cortés-Castell, Ernesto
Juste, Mercedes
Palazón-Bru, Antonio
Monge, Laura
Sánchez-Ferrer, Francisco
Rizo-Baeza, María Mercedes
author_facet Cortés-Castell, Ernesto
Juste, Mercedes
Palazón-Bru, Antonio
Monge, Laura
Sánchez-Ferrer, Francisco
Rizo-Baeza, María Mercedes
author_sort Cortés-Castell, Ernesto
collection PubMed
description BACKGROUND: Dual-energy X-ray absorptiometry (DXA) provides separate measurements of fat mass, fat-free mass and bone mass, and is a quick, accurate, and safe technique, yet one that is not readily available in routine clinical practice. Consequently, we aimed to develop statistical formulas to predict fat mass (%) and fat mass index (FMI) with simple parameters (age, sex, weight and height). METHODS: We conducted a retrospective observational cross-sectional study in 416 overweight or obese patients aged 4–18 years that involved assessing adiposity by DXA (fat mass percentage and FMI), body mass index (BMI), sex and age. We randomly divided the sample into two parts (construction and validation). In the construction sample, we developed formulas to predict fat mass and FMI using linear multiple regression models. The formulas were validated in the other sample, calculating the intraclass correlation coefficient via bootstrapping. RESULTS: The fat mass percentage formula had a coefficient of determination of 0.65. This value was 0.86 for FMI. In the validation, the constructed formulas had an intraclass correlation coefficient of 0.77 for fat mass percentage and 0.92 for FMI. CONCLUSIONS: Our predictive formulas accurately predicted fat mass and FMI with simple parameters (BMI, sex and age) in children with overweight and obesity. The proposed methodology could be applied in other fields. Further studies are needed to externally validate these formulas.
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spelling pubmed-54101552017-05-01 A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study Cortés-Castell, Ernesto Juste, Mercedes Palazón-Bru, Antonio Monge, Laura Sánchez-Ferrer, Francisco Rizo-Baeza, María Mercedes PeerJ Drugs and Devices BACKGROUND: Dual-energy X-ray absorptiometry (DXA) provides separate measurements of fat mass, fat-free mass and bone mass, and is a quick, accurate, and safe technique, yet one that is not readily available in routine clinical practice. Consequently, we aimed to develop statistical formulas to predict fat mass (%) and fat mass index (FMI) with simple parameters (age, sex, weight and height). METHODS: We conducted a retrospective observational cross-sectional study in 416 overweight or obese patients aged 4–18 years that involved assessing adiposity by DXA (fat mass percentage and FMI), body mass index (BMI), sex and age. We randomly divided the sample into two parts (construction and validation). In the construction sample, we developed formulas to predict fat mass and FMI using linear multiple regression models. The formulas were validated in the other sample, calculating the intraclass correlation coefficient via bootstrapping. RESULTS: The fat mass percentage formula had a coefficient of determination of 0.65. This value was 0.86 for FMI. In the validation, the constructed formulas had an intraclass correlation coefficient of 0.77 for fat mass percentage and 0.92 for FMI. CONCLUSIONS: Our predictive formulas accurately predicted fat mass and FMI with simple parameters (BMI, sex and age) in children with overweight and obesity. The proposed methodology could be applied in other fields. Further studies are needed to externally validate these formulas. PeerJ Inc. 2017-04-27 /pmc/articles/PMC5410155/ /pubmed/28462041 http://dx.doi.org/10.7717/peerj.3238 Text en ©2017 Cortés-Castell et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Drugs and Devices
Cortés-Castell, Ernesto
Juste, Mercedes
Palazón-Bru, Antonio
Monge, Laura
Sánchez-Ferrer, Francisco
Rizo-Baeza, María Mercedes
A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
title A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
title_full A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
title_fullStr A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
title_full_unstemmed A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
title_short A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
title_sort simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study
topic Drugs and Devices
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410155/
https://www.ncbi.nlm.nih.gov/pubmed/28462041
http://dx.doi.org/10.7717/peerj.3238
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