ASSESSMENT OF NUTRITIONAL AND METABOLIC STATUS: Edited by Dwight E. Matthews and Kristina NormanBioelectrical impedance analysis in the assessment of sarcopeniaGonzalez, M. Cristinaa,c; Barbosa-Silva, Thiago G.b; Heymsfield, Steven B.cAuthor Information aPostgraduate Program in Health and Behavior, Catholic University of Pelotas bPostgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil cPennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA Correspondence to M. Cristina Gonzalez, Postgraduate Program in Health and Behavior, Catholic University of Pelotas, R. Gonçalves Chaves, 377 Room 411, CEP 96015-560 Pelotas, RS, Brazil. Tel: +55 53 99982 1328; fax: 55 53 2128 8229; e-mail: email@example.com Current Opinion in Clinical Nutrition and Metabolic Care: September 2018 - Volume 21 - Issue 5 - p 366-374 doi: 10.1097/MCO.0000000000000496 Buy Metrics Abstract Purpose of review Bioelectrical impedance analysis (BIA) is an accepted technique to estimate low muscle mass for sarcopenia diagnosis. However, muscularity assessment from BIA relies on prediction equations, estimating different compartments according to the calibration method. Low muscle mass can be defined using different approaches. Recent findings There is a lack of standardization on how low muscularity is defined in the context of sarcopenia. Recent studies have shown discrepant results for the estimation of low muscle mass when different prediction equations are used in the same BIA device. Different sarcopenia prevalence rates are observed if different definitions are used to identify low muscle mass. Most of the studies using BIA for diagnosing sarcopenia use the incorrect combination of specific population cut-off or a different device from the original equation. Summary The lack of standardization of BIA use for assessing muscularity results in a wide range of sarcopenia prevalence rates among studies, even when conducted in the same population. As BIA equations and cut-off values are population and device-specific, results should be interpreted with caution when data from different devices are applied in equations or using cut-off values from a different population. Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.