Prediction of muscle mass in arms and legs based on 3D laser-based photonic body scans’ standard dimensions in a homogenous sample of young men

Abstract

ABSTRACT Reliably identifying muscle mass from external anthropometric measurements can provide valuable information about a person’s health conditions and related outcomes. A potential tool for easily predicting muscle mass is three-dimensional (3D) body scans, but accurate validation data are missing. The aim of our study was to predict skeletal muscle mass (SMM) as assessed by Bioelectrical Impedance Analysis (BIA) from 3D body scanner data. We aimed to examine which 3D body scan standard parameters of the upper and lower limbs best predict skeletal muscle mass measured by BIA in a cross-sectional and homogenous sample of N = 100 young men. In both arms and legs, Spearman’s rank correlation coefficients with SMM were generally high for girths and volumes, and lower for lengths. The volumes of the forearm (R = 0.80–0.82) and calf (R = 0.87) correlated best with SMM. For the longitudinal follow-up of N = 45 young men, the Wilcoxon signed-rank test showed that, on average, the longitudinally followed-up increased in weight, height, BMI as well as relative/absolute fat mass. The best single predictors for individual differences in SMM were deltas for upper arm girth of both arms (adjusted R2 0.17 and 0.17) and deltas for calf girth of both legs (0.37 and 0.45). Although 3D body scan girth measures can predict SMM in upper and lower limbs satisfying, adding volumes and lengths to the equations increase the precision of the estimations fairly.