Variability in BIA-Derived Muscle Mass Estimates: Device Choice Impacts Diagnostic Classification

Area of Science:

• Biomedical Engineering
• Clinical Nutrition
• Body Composition Analysis

Background:

• Discrepancies among bioelectrical impedance analysis (BIA) devices are known.
• Clinical relevance of these BIA device discrepancies in vulnerable populations like cancer and obesity patients is unclear.

Purpose of the Study:

• To assess how BIA device selection affects muscle mass classification in cancer and obesity patients.
• To identify factors influencing BIA device variability.

Main Methods:

• Compared BIA data from 224 adults (cancer, obesity) using seca mBCA 515 and InBody 970 devices.
• Analyzed differences in body composition classification against GLIM, ESPEN, and EASO criteria.
• Examined disease type, sex, and age as modifiers of device differences.

Main Results:

• Significant device differences observed for all BIA parameters (p ≤ 0.005), especially skeletal muscle mass (r > 0.8, poor agreement).
• Device choice impacted muscle mass classification (p < 0.001), with seca classifying more patients as having low fat-free mass and sarcopenic obesity.
• Discrepancies were greater in cancer patients and females.

Conclusions:

• BIA-based muscle mass assessment is highly device-dependent, risking clinically relevant misclassification with rigid criteria.
• Individualized interpretation of BIA data and validation in disease-specific groups are necessary.