Background/objectives: Sarcopenia involves the loss of muscle mass along with a decrease in muscle strength and physical performance. The aim of this paper was to compare the already published BIA equations for the estimation of Appendicular Skeletal Muscle Mass (ASMM) and Fat-Free Mass (FFM) with dual X-ray densitometer DXA estimations in order to determine whether Bioelectrical Impedance Analysis (BIA) could be a feasible application on a general population for the detection of low muscle mass and sarcopenia. Methods: Seventy-nine healthy women aged 40-70 years were included. Assessments involved BIA and DXA evaluations and anthropometric measurements. Results: DXA and BIA estimations showed great agreement, particularly the ones introduced by Scafoglieri et al. (2017) for ASMM (mean difference 1.81 kg) and Kanellakis et al. (2020) equation for FFM (mean difference 0.52 kg) resulted in the best fit for the cohort in analysis. BIA could intercept a low muscle mass condition which can be linked to sarcopenia. Conclusions: This study showed how the use of BIA represents an effective and reliable method in the evaluation of sarcopenia.

Appendicular Skeletal Muscle Mass (ASMM) and Fat-Free Mass (FFM) DXA-BIA Estimations for the Early Identification of Sarcopenia/Low Muscle Mass in Middle-Aged Women

Gasparri, Clara;Perna, Simone;Rondanelli, Mariangela;
2024-01-01

Abstract

Background/objectives: Sarcopenia involves the loss of muscle mass along with a decrease in muscle strength and physical performance. The aim of this paper was to compare the already published BIA equations for the estimation of Appendicular Skeletal Muscle Mass (ASMM) and Fat-Free Mass (FFM) with dual X-ray densitometer DXA estimations in order to determine whether Bioelectrical Impedance Analysis (BIA) could be a feasible application on a general population for the detection of low muscle mass and sarcopenia. Methods: Seventy-nine healthy women aged 40-70 years were included. Assessments involved BIA and DXA evaluations and anthropometric measurements. Results: DXA and BIA estimations showed great agreement, particularly the ones introduced by Scafoglieri et al. (2017) for ASMM (mean difference 1.81 kg) and Kanellakis et al. (2020) equation for FFM (mean difference 0.52 kg) resulted in the best fit for the cohort in analysis. BIA could intercept a low muscle mass condition which can be linked to sarcopenia. Conclusions: This study showed how the use of BIA represents an effective and reliable method in the evaluation of sarcopenia.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1511424
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