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Prediction Equations of the Multifrequency Standing and Supine Bioimpedance for Appendicular Skeletal Muscle Mass in Korean Older Peopleopen access

Authors
Jeon, Kwon ChanKim, So-YoungJiang, Fang LinChung, SochungAmbegaonkar, Jatin P.Park, Jae-HyeonKim, Young-JooKim, Chul-Hyun
Issue Date
Aug-2020
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Keywords
multifrequency bioelectrical impedance analysis (MF-BIA); dual-energy X-ray absorptiometry (DXA); clinical diagnosis; sarcopenia; appendicular skeletal muscle mass
Citation
International Journal of Environmental Research and Public Health, v.17, no.16
Journal Title
International Journal of Environmental Research and Public Health
Volume
17
Number
16
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/2603
DOI
10.3390/ijerph17165847
ISSN
1661-7827
1660-4601
Abstract
Bioimpedance analysis (BIA) has been demanded for the assessment of appendicular skeletal muscle mass (ASM) in clinical and epidemiological settings. This study aimed to validate BIA equations for predicting ASM in the standing and supine positions; externally to cross-validate the new and published and built-in BIA equations for group and individual predictive accuracy; and to assess the overall agreement between the measured and predicted ASM index as sarcopenia diagnosis. In total, 199 healthy older adults completed the measurements of multifrequency BIA (InBody770 and InBodyS10) and dual-energy X-ray absorptiometry (DXA). Multiple regression analysis was used to validate the new multifrequency bioelectrical impedance analysis (MF-BIA) prediction equations. Each MF-BIA equation in the standing and supine position developed in the entire group included height(2)/resistance, sex, and reactance as predictors (R-2= 92.7% and 92.8%, SEE = 1.02 kg and 1.01 kg ASM for the standing and supine MF-BIA). The new MF-BIA equations had a specificity positive predictive value and negative predictive value of 85% or more except for a sensitivity of about 60.0%. The new standing and supine MF-BIA prediction equation are useful for epidemiological and field settings as well as a clinical diagnosis of sarcopenia. Future research is needed to improve the sensitivity of diagnosis of sarcopenia using MF-BIA.
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