Bioelectrical impedance analysis for diagnosing sarcopenia and cachexia: what are we really estimating?. Issue 2 (31st January 2017)

• Record Type: Journal Article
• Authors: Gonzalez, Maria Cristina; Heymsfield, Steven B.
• Is Part Of: Journal of cachexia, sarcopenia and muscle. Volume 8:Issue 2(2017)
• Page Start: 187
• Page End: 189
• Publication Date: 2017-01-31
• Subjects: bioelectrical impedance analysis -- sarcopenia -- cachexia -- body composition -- muscularity; Cachexia -- Periodicals; Muscles -- Aging -- Periodicals; Muscles -- Periodicals; Cachexia; Sarcopenia; Muscles; Cachexia; Muscles; Muscles -- Aging; Periodicals; Periodicals; 616
• DOI: 10.1002/jcsm.12159
• Languages: English
• ISSNs: 2190-5991

Abstract

Abstract: As reference methods are not available for identifying low skeletal muscle mass in clinical practice, the European Group on Sarcopenia in Older People the Asian Working Group for Sarcopenia and the International Consensus for Cancer Cachexia guidelines accept bioelectrical impedance analysis (BIA) as an option for sarcopenia and cachexia assessment. Using different BIA equations, several components that represent 'muscularity' can be assessed. Total skeletal muscle mass or appendicular skeletal muscle mass normalized in relation to height (skeletal muscle mass index or appendicular skeletal muscle index, respectively) is the most common term used in the consensus. These terms are similar, but they should not be used as synonymous. Both terms can be used to define sarcopenia, but adequate equations and cut‐off values should be used according to the studied population. However, there is a disagreement between the sarcopenia definition assessed by using BIA from the European Group on Sarcopenia in Older People and Cachexia Consensus, and this can lead to an overestimation of sarcopenia and, consequently, cachexia. An effort should be made to standardize the terminology employed by the Societies to define low muscularity and sarcopenia by using BIA. Future validation studies may show the need for specific cut‐off values for each population using this method.