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Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults

Non-invasive and easy alternative methods to indicate skeletal muscle mass index (SMI) have not been established when dual energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) cannot be performed. This study aims to construct a prediction model including gastrocnemius thicknes...

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Autores principales: Yuguchi, Satoshi, Asahi, Ryoma, Kamo, Tomohiko, Azami, Masato, Ogihara, Hirofumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8998399/
https://www.ncbi.nlm.nih.gov/pubmed/35409723
http://dx.doi.org/10.3390/ijerph19074042
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author Yuguchi, Satoshi
Asahi, Ryoma
Kamo, Tomohiko
Azami, Masato
Ogihara, Hirofumi
author_facet Yuguchi, Satoshi
Asahi, Ryoma
Kamo, Tomohiko
Azami, Masato
Ogihara, Hirofumi
author_sort Yuguchi, Satoshi
collection PubMed
description Non-invasive and easy alternative methods to indicate skeletal muscle mass index (SMI) have not been established when dual energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) cannot be performed. This study aims to construct a prediction model including gastrocnemius thickness using ultrasonography for skeletal muscle mass index (SMI). Total of 193 Japanese aged ≥65 years participated. SMI was measured by BIA, and subcutaneous fat thickness and gastrocnemius thickness in the medial gastrocnemius were measured by using ultrasonography, and age, gender and body mass index (BMI), grip strength, and gait speed were collected. The stepwise multiple regression analysis was conducted, which incorporated SMI as a dependent variable and age, gender, BMI, gastrocnemius thickness, and other factors as independent variables. Gender, BMI, and gastrocnemius thickness were included as significant factors, and the formula: SMI = 1.27 × gender (men: 1, women: 0) + 0.18 × BMI + 0.09 × gastrocnemius thickness (mm) + 1.3 was shown as the prediction model for SMI (R = 0.89, R(2) = 0.8, adjusted R(2) = 0.8, p < 0.001). The prediction model for SMI had high accuracy and could be a non-invasive and easy alternative method to predict SMI in Japanese older adults.
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spelling pubmed-89983992022-04-12 Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults Yuguchi, Satoshi Asahi, Ryoma Kamo, Tomohiko Azami, Masato Ogihara, Hirofumi Int J Environ Res Public Health Article Non-invasive and easy alternative methods to indicate skeletal muscle mass index (SMI) have not been established when dual energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) cannot be performed. This study aims to construct a prediction model including gastrocnemius thickness using ultrasonography for skeletal muscle mass index (SMI). Total of 193 Japanese aged ≥65 years participated. SMI was measured by BIA, and subcutaneous fat thickness and gastrocnemius thickness in the medial gastrocnemius were measured by using ultrasonography, and age, gender and body mass index (BMI), grip strength, and gait speed were collected. The stepwise multiple regression analysis was conducted, which incorporated SMI as a dependent variable and age, gender, BMI, gastrocnemius thickness, and other factors as independent variables. Gender, BMI, and gastrocnemius thickness were included as significant factors, and the formula: SMI = 1.27 × gender (men: 1, women: 0) + 0.18 × BMI + 0.09 × gastrocnemius thickness (mm) + 1.3 was shown as the prediction model for SMI (R = 0.89, R(2) = 0.8, adjusted R(2) = 0.8, p < 0.001). The prediction model for SMI had high accuracy and could be a non-invasive and easy alternative method to predict SMI in Japanese older adults. MDPI 2022-03-29 /pmc/articles/PMC8998399/ /pubmed/35409723 http://dx.doi.org/10.3390/ijerph19074042 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yuguchi, Satoshi
Asahi, Ryoma
Kamo, Tomohiko
Azami, Masato
Ogihara, Hirofumi
Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults
title Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults
title_full Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults
title_fullStr Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults
title_full_unstemmed Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults
title_short Prediction Model including Gastrocnemius Thickness for the Skeletal Muscle Mass Index in Japanese Older Adults
title_sort prediction model including gastrocnemius thickness for the skeletal muscle mass index in japanese older adults
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8998399/
https://www.ncbi.nlm.nih.gov/pubmed/35409723
http://dx.doi.org/10.3390/ijerph19074042
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