Estimation of skeletal muscle mass by bioimpedance and differences among skeletal muscle mass indices for assessing sarcopenia

Abstract

It is crucial to assess age-related muscle mass changes and derived indices differences in geriatric medicine. We aimed to develop and validate four bioimpedance analysis (BIA) prediction equations against dual-energy X-ray absorptiometry (DEXA) and magnetic resonance image (MRI) in estimating skeletal muscle mass and to compare the differences among skeletal muscle mass indices, cutoff values, and corresponding prevalence rates of low muscle mass for assessing sarcopenia in Chinese adults. We measured the height (Ht), weight (Wt), appendicular lean mass (ALM) or skeletal muscle mass (ASM), total lean body mass (LBM) or skeletal muscle mass (TSM) obtained using DEXA or MRI, and a multi-frequency BIA (BCA II;50, 250kHz), in 371 adults aged 18.0-87.0 years. We also collected gender, age, Ht, Wt, and impedance indexes (Ht2/R50, Ht2/R250, R50/Ht2, R250/Ht2) from 30,500 adults aged 18-96 years living in China. Multiple regression analyses were used to derive four prediction equations by BIA, and double cross-validation techniques and Bland-Altman analyses were used to test agreement. Various muscle mass indices and prevalence rates were depicted by line plots in regard to age trends. Satisfactory results were found in the four prediction models as they had the larger R2 (0.833-0.930) values and low SEE (1.409-2.335kg) values. The predictive variables included impedance indexes (Ht2/R50, R50/Ht2, R250/Ht2), gender, age, Wt, and Ht. The corresponding prevalence rates of low muscle mass exhibited significant differences according to the various muscle mass indices adjusted for Ht, Wt, or body mass index (BMI), in addition to the cutoff values based on two standard deviations (2SD) of young people or the lower 20% of the study group. The BIA equations have the potential to be applied as a practical method of quantifying skeletal muscle mass in Chinese adults. However, the operational methods that are most appropriate for determining the degree of low muscle mass that actually contributes to sarcopenia remains inconclusive.