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Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men

INTRODUCTION: Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard me...

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Autores principales: Sager, Roman, Güsewell, Sabine, Rühli, Frank, Bender, Nicole, Staub, Kaspar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289400/
https://www.ncbi.nlm.nih.gov/pubmed/32525949
http://dx.doi.org/10.1371/journal.pone.0234552
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author Sager, Roman
Güsewell, Sabine
Rühli, Frank
Bender, Nicole
Staub, Kaspar
author_facet Sager, Roman
Güsewell, Sabine
Rühli, Frank
Bender, Nicole
Staub, Kaspar
author_sort Sager, Roman
collection PubMed
description INTRODUCTION: Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements. METHODS: We analysed 104 men aged 19–23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken. RESULTS: Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r(2) up to 0.92) and absolute fat mass (AFM, r(2) up to 0.87) but not for SMM (r(2) up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r(2) up to 0.99) was achieved with models including 49 scanner measurements. CONCLUSION: The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.
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spelling pubmed-72894002020-06-15 Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men Sager, Roman Güsewell, Sabine Rühli, Frank Bender, Nicole Staub, Kaspar PLoS One Research Article INTRODUCTION: Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements. METHODS: We analysed 104 men aged 19–23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken. RESULTS: Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r(2) up to 0.92) and absolute fat mass (AFM, r(2) up to 0.87) but not for SMM (r(2) up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r(2) up to 0.99) was achieved with models including 49 scanner measurements. CONCLUSION: The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models. Public Library of Science 2020-06-11 /pmc/articles/PMC7289400/ /pubmed/32525949 http://dx.doi.org/10.1371/journal.pone.0234552 Text en © 2020 Sager 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, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sager, Roman
Güsewell, Sabine
Rühli, Frank
Bender, Nicole
Staub, Kaspar
Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men
title Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men
title_full Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men
title_fullStr Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men
title_full_unstemmed Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men
title_short Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men
title_sort multiple measures derived from 3d photonic body scans improve predictions of fat and muscle mass in young swiss men
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289400/
https://www.ncbi.nlm.nih.gov/pubmed/32525949
http://dx.doi.org/10.1371/journal.pone.0234552
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