Raw bioelectrical impedance parameters and vector analysis in the screening of low muscle mass and low muscle mass associated with obesity in adult healthy subjects

• Published in: Internal and emergency medicine Vol. 20; no. 3; pp. 709 - 722
• Main Authors: Bennouar, Salam, Bachir Cherif, Abdelghani, Raaf, Nabil, Hani, Hadda Meroua, Kessira, Amel, Abdi, Samia
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.04.2025; Springer Nature B.V
• Subjects: Adult; Anthropometry; Body composition; Body Composition - physiology; Body fat; Body Mass Index; Body water; Cross-Sectional Studies; Electric Impedance - therapeutic use; Female; Healthy Volunteers; Humans; Im - Original; Internal Medicine; Male; Mass Screening - methods; Medicine; Medicine & Public Health; Middle Aged; Muscle, Skeletal; Obesity; Obesity - complications; Obesity - physiopathology; ROC Curve; Skeletal muscle; Women; Low muscle mass; Low muscle mass–obesity; BIVA; Anthropometry; graph; Bioelectrical impedance; RX c graph
• ISSN: 1828-0447; 1970-9366; 1970-9366
• DOI: 10.1007/s11739-025-03857-y

The aim was to estimate the prevalence of low muscle mass (LMM) and low muscle mass associated with obesity (LMM-O) in healthy adult, and to verify the performance of raw bioelectrical impedance parameters (BIA) and vector analysis (BIVA) in the screening of this tow conditions. This is a cross-sectional study including 1025 healthy adults. Body composition was assessed by the BIA technique. The appendicular skeletal muscle mass index (ASMMI) and body fat percentage (BF%) were used for the screening of LMM and LMM-O. The raw BIA parameters were: resistance ( R ), reactance ( X c ), phase angle (PhA), and impedance ( Z ). The vectors, R and X c , were adjusted for height and projected on the RX c graph. Associations were checked by the correlation test, binary logistic regression, adjusted for age and body water, and ROC curve. LMM was found in 30.8% of the subjects, and 20.9 and 21.4% of the men and women were with LMM-O. PhA and R / H were the most powerful discriminators of LMM with a sensitivity of 62–100% and a specificity of 71–90%. Cutoff values of PhA ranged between 4.95° and 5.75° for women and men. The RX c graph was able to identify LMM subjects, with clustering on the right side: area of low cellularity, high R / H and low-phase angle. Traditional anthropometric indices were the least effective in identifying LMM-O. The BIVA approach, PhA, R and R / H are effective in the screening of LMM and LMM-O, irrespective of age, gender, intra- and extracellular hydration status