Development and validation of new bioimpedance equations to estimate skeletal muscle mass percentage in a white, healthy population.

Abstract

Background & aims: Skeletal muscle mass (SMM) plays a crucial role in overall health, especially in the aging population, and increased fat deposition elevate the risk of frailty and metabolic disorders. Accurate and accessible SMM assessment is essential for identifying and monitoring these risks. Bioelectrical impedance analysis (BIA) devices, widely used for body composition assessment, provide a non-invasive, practical solution; however, the accuracy of BIA measurements can vary significantly compared to dual-energy X-ray absorptiometry (DXA), particularly across different device types and demographic groups. Given the physiological and lifestyle changes that can influence muscle mass across the adult lifespan, there is a growing need for precise, reliable tools to evaluate SMM in a broad adult population. Methods: We developed novel equations for estimating SMM percentage in a white, healthy population using two different BIA technologies: foot-to-hand device (Akern 101) and hand-to-hand device (TELELAB). These equations were developed to enhance the precision of SMM measurements, calibrating the output to align more closely with DXA values. A sample of 211 individuals (100 women, 111 men) aged 18–65 years was divided into a development group and a validation group to establish and test the predictive reliability of the proposed equations. Results: Bland–Altman analyses revealed minimal fixed bias for both new equations compared to DXA, with substantially reduced mean bias values and lower standard deviations than those observed with use of the original manufacturer's equations. Conclusions: The new equations effectively minimize the overestimation observed when using the manufacturer's equations, demonstrating an average bias close to zero and enhanced consistency across age and ethnic groups. These optimized equations offer a robust, practical solution for accurate SMM assessment in clinical and research settings across diverse adult populations.