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How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study

Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass in...

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Autores principales: Thelwell, Michael, Chiu, Chuang-Yuan, Bullas, Alice, Hart, John, Wheat, Jon, Choppin, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376175/
https://www.ncbi.nlm.nih.gov/pubmed/32699270
http://dx.doi.org/10.1038/s41598-020-69099-4
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author Thelwell, Michael
Chiu, Chuang-Yuan
Bullas, Alice
Hart, John
Wheat, Jon
Choppin, Simon
author_facet Thelwell, Michael
Chiu, Chuang-Yuan
Bullas, Alice
Hart, John
Wheat, Jon
Choppin, Simon
author_sort Thelwell, Michael
collection PubMed
description Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass index (BMI), the waist-hip-ratio (WHR) and waist-by-height(0.5) ratio (WHT.5R). Three-dimensional (3D) imaging systems capture detailed and accurate measures of external human form and have the potential to surpass traditional measures in health applications. The aim of this study was to investigate how shape measurement can complement existing anthropometric techniques in the assessment of human form. Geometric morphometric methods and principal components analysis were used to extract independent, scale-invariant features of torso shape from 3D scans of 43 male participants. Linear regression analyses were conducted to determine whether novel shape measures can complement anthropometric indices when estimating waist skinfold thickness measures. Anthropometric indices currently used in practice explained up to 52.2% of variance in waist skinfold thickness, while a combined regression model using WHT.5R and shape measures explained 76.5% of variation. Measures of body shape provide additional information regarding external human form and can complement traditional measures currently used in anthropometric practice to estimate central adiposity.
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spelling pubmed-73761752020-07-24 How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study Thelwell, Michael Chiu, Chuang-Yuan Bullas, Alice Hart, John Wheat, Jon Choppin, Simon Sci Rep Article Manual anthropometrics are used extensively in medical practice and epidemiological studies to assess an individual's health. However, traditional techniques reduce the complicated shape of human bodies to a series of simple size measurements and derived health indices, such as the body mass index (BMI), the waist-hip-ratio (WHR) and waist-by-height(0.5) ratio (WHT.5R). Three-dimensional (3D) imaging systems capture detailed and accurate measures of external human form and have the potential to surpass traditional measures in health applications. The aim of this study was to investigate how shape measurement can complement existing anthropometric techniques in the assessment of human form. Geometric morphometric methods and principal components analysis were used to extract independent, scale-invariant features of torso shape from 3D scans of 43 male participants. Linear regression analyses were conducted to determine whether novel shape measures can complement anthropometric indices when estimating waist skinfold thickness measures. Anthropometric indices currently used in practice explained up to 52.2% of variance in waist skinfold thickness, while a combined regression model using WHT.5R and shape measures explained 76.5% of variation. Measures of body shape provide additional information regarding external human form and can complement traditional measures currently used in anthropometric practice to estimate central adiposity. Nature Publishing Group UK 2020-07-22 /pmc/articles/PMC7376175/ /pubmed/32699270 http://dx.doi.org/10.1038/s41598-020-69099-4 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Thelwell, Michael
Chiu, Chuang-Yuan
Bullas, Alice
Hart, John
Wheat, Jon
Choppin, Simon
How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
title How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
title_full How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
title_fullStr How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
title_full_unstemmed How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
title_short How shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
title_sort how shape-based anthropometry can complement traditional anthropometric techniques: a cross-sectional study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376175/
https://www.ncbi.nlm.nih.gov/pubmed/32699270
http://dx.doi.org/10.1038/s41598-020-69099-4
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