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Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults
AIM: To develop predictive equations of lean body mass (LBM) suitable for healthy southern Chinese adults with a large sample. LBM measured by dual-energy X-ray absorptiometry (DXA) are considered as the standard ones. METHODS: Retrospective analysis was conducted on the consecutive people who did t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612995/ https://www.ncbi.nlm.nih.gov/pubmed/31341889 http://dx.doi.org/10.1155/2019/1757954 |
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author | Li, Jinhua Shang, Jingjie Guo, Bin Gong, Jian Xu, Hao |
author_facet | Li, Jinhua Shang, Jingjie Guo, Bin Gong, Jian Xu, Hao |
author_sort | Li, Jinhua |
collection | PubMed |
description | AIM: To develop predictive equations of lean body mass (LBM) suitable for healthy southern Chinese adults with a large sample. LBM measured by dual-energy X-ray absorptiometry (DXA) are considered as the standard ones. METHODS: Retrospective analysis was conducted on the consecutive people who did total body measurement with DXA from July 2005 to October 2015. People with diseases that might affect LBM were excluded and overall 12,194 subjects were included in this study. Information about the 10,683 subjects (2,987 males and 7,696 females) from July 2005 to November 2014 was used to establish equations. These subjects were grouped by sex and then subdivided according to their body mass index (BMI). The female group was divided into another two subgroups: the premenopausal and postmenopausal subgroups. Equations were developed through stepwise multilinear regression analysis of height, weight, age, and BMI. Information about the 1,511 subjects (395 males and 1116 females) from December 2014 to October 2015 was used to verify the established equations. RESULTS: BMI, height, weight, and age were introduced into the equations as independent variables in the male group, while age was proved to have no influence on LBM in the female group. Regrouping according to BMI or menopause did not increase the predictive ability of equations. Good agreement between LBM evaluated by equation (LBM_PE) and LBM measured by DXA (LBM_DXA) was observed in both the male and female groups. CONCLUSION: Predictive equations of LBM suitable for healthy southern Chinese adults are established with a large sample. BMI was related to LBM content; however, there is no need for further group based on BMI or menopause while developing LBM questions. |
format | Online Article Text |
id | pubmed-6612995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-66129952019-07-24 Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults Li, Jinhua Shang, Jingjie Guo, Bin Gong, Jian Xu, Hao Biomed Res Int Research Article AIM: To develop predictive equations of lean body mass (LBM) suitable for healthy southern Chinese adults with a large sample. LBM measured by dual-energy X-ray absorptiometry (DXA) are considered as the standard ones. METHODS: Retrospective analysis was conducted on the consecutive people who did total body measurement with DXA from July 2005 to October 2015. People with diseases that might affect LBM were excluded and overall 12,194 subjects were included in this study. Information about the 10,683 subjects (2,987 males and 7,696 females) from July 2005 to November 2014 was used to establish equations. These subjects were grouped by sex and then subdivided according to their body mass index (BMI). The female group was divided into another two subgroups: the premenopausal and postmenopausal subgroups. Equations were developed through stepwise multilinear regression analysis of height, weight, age, and BMI. Information about the 1,511 subjects (395 males and 1116 females) from December 2014 to October 2015 was used to verify the established equations. RESULTS: BMI, height, weight, and age were introduced into the equations as independent variables in the male group, while age was proved to have no influence on LBM in the female group. Regrouping according to BMI or menopause did not increase the predictive ability of equations. Good agreement between LBM evaluated by equation (LBM_PE) and LBM measured by DXA (LBM_DXA) was observed in both the male and female groups. CONCLUSION: Predictive equations of LBM suitable for healthy southern Chinese adults are established with a large sample. BMI was related to LBM content; however, there is no need for further group based on BMI or menopause while developing LBM questions. Hindawi 2019-06-24 /pmc/articles/PMC6612995/ /pubmed/31341889 http://dx.doi.org/10.1155/2019/1757954 Text en Copyright © 2019 Jinhua Li et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Jinhua Shang, Jingjie Guo, Bin Gong, Jian Xu, Hao Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults |
title | Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults |
title_full | Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults |
title_fullStr | Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults |
title_full_unstemmed | Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults |
title_short | Establishment of Prediction Equations of Lean Body Mass Suitable for Chinese Adults |
title_sort | establishment of prediction equations of lean body mass suitable for chinese adults |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612995/ https://www.ncbi.nlm.nih.gov/pubmed/31341889 http://dx.doi.org/10.1155/2019/1757954 |
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