Estimation of skeletal muscle mass by bioelectrical impedance analysis

TLDR

The study aimed to develop and cross‑validate predictive equations for estimating skeletal muscle mass using bioelectrical impedance analysis. Using MRI‑derived whole‑body skeletal muscle mass as the reference, the authors derived and cross‑validated BIA‑based regression equations from 388 multiethnic adults across two laboratories, then pooled the data to produce a final model incorporating height, resistance, gender, and age. The final equation explained 86 % of the variance (r² = 0.86) with a 2.7 kg (9 %) standard error, performed well in Hispanics and African‑Americans, but underestimated muscle mass in Asians, indicating that BIA provides valid estimates in healthy adults of varying age and adiposity.

Abstract

The purpose of this study was to develop and cross-validate predictive equations for estimating skeletal muscle (SM) mass using bioelectrical impedance analysis (BIA). Whole body SM mass, determined by magnetic resonance imaging, was compared with BIA measurements in a multiethnic sample of 388 men and women, aged 18–86 yr, at two different laboratories. Within each laboratory, equations for predicting SM mass from BIA measurements were derived using the data of the Caucasian subjects. These equations were then applied to the Caucasian subjects from the other laboratory to cross-validate the BIA method. Because the equations cross-validated (i.e., were not different), the data from both laboratories were pooled to generate the final regression equation[Formula: see text] [Formula: see text] where Ht is height in centimeters; R is BIA resistance in ohms; for gender, men = 1 and women = 0; and age is in years. The r 2 and SE of estimate of the regression equation were 0.86 and 2.7 kg (9%), respectively. The Caucasian-derived equation was applicable to Hispanics and African-Americans, but it underestimated SM mass in Asians. These results suggest that the BIA equation provides valid estimates of SM mass in healthy adults varying in age and adiposity.