Bio-impedance analysis for appendicular skeletal muscle mass assessment in (pre-) frail elderly people. Issue 4 (August 2015)

• Record Type: Journal Article
• Authors: van Baar, H.; Hulshof, P.J.M.; Tieland, M.; de Groot, C.P.G.M.
• Is Part Of: Clinical nutrition ESPEN. Volume 10:Issue 4(2015)
• Page Start: e147
• Page End: e153
• Publication Date: 2015-08
• Subjects: Sarcopenia -- Bio-impedance -- Dual-energy X-ray absorptiometry -- Appendicular skeletal muscle mass -- Body composition -- Frailty; Nutritionally induced diseases -- Periodicals; Metabolism -- Disorders -- Periodicals; 616.39005
• DOI: 10.1016/j.clnesp.2015.05.002
• Languages: English
• ISSNs: 2405-4577

Abstract

Summary: Background & aims: Screening populations for skeletal muscle mass (SMM) is important for early detection of sarcopenia. Our aim was to develop an age specific bio-impedance (BI) prediction equation for the assessment of appendicular skeletal muscle mass (ASMM) in (pre-) frail elderly people aged 65 and older. Methods: Anthropometric, BI and dual-energy X-ray absorptiometry (DEXA) measurements from 106 (pre-) frail elderly subjects (61 females and 45 males, aged 65–96 years) were used to derive three ASMM prediction equations using multiple regression analysis: one for single frequency BI measurements at 50 kHz (ASMM50kHz ), one for measurements at the characteristic frequency (ASMMFc ) and one for bioelectrical impedance spectroscopy (ASMMBIS ). The same data was used to evaluate an existing prediction equation. Results: ASMM50kHz had the best fitting model ( r 2 adj = 0.923, SEE = 1.19 and a PRESS value = 163.4), followed by ASMMFc ( r 2 adj = 0.915, SEE = 1.25 and a PRESS value = 175.9) and ASMMBIS ( r 2 adj = 0.915, SEE = 1.26 and a PRESS value = 177.1). Average ASMM measured by DEXA and both ASMM50kHz and ASMMFc were comparable. ASMMBIS tended to underestimate ASMM slightly. An existing prediction equation had a tendency to underestimate ASMM in people with a lower amount of ASMM and overestimate ASMM in people with a higher amount of ASMM. Conclusions: ASMM50kHz was able to measure average ASMM within our population of (pre-) frail elderly in a valid way. However, its predictive power on both individual and population level needs to be confirmed in an independent and larger (pre-) frail elderly population and across multiple institutions and ethnic groups.