• Salam Bennouar, Abdelghani Bachir Cherif, Nabil Raaf, Hadda Meroua Hani, Amel Kessira, and Samia Abdi.
• Central Laboratory of Clinical Biology, Frantz Fanon Hospital, University Hospital Center of Blida, 9000, Blida, Algeria. salambennouar@gmail.com.
• Intern Emerg Med. 2025 Jan 15.

AbstractThe 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 (Xc), phase angle (PhA), and impedance (Z). The vectors, R and Xc, were adjusted for height and projected on the RXc 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 RXc 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.© 2025. The Author(s), under exclusive licence to Società Italiana di Medicina Interna (SIMI).

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