<p>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 (<i>R</i>), reactance (<i>X</i>_c), phase angle (PhA), and impedance (<i>Z</i>). The vectors, <i>R</i> and <i>X</i>_c, were adjusted for height and projected on the <i>RX</i>_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 <i>R</i>/<i>H</i> 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 <i>RX</i>_c graph was able to identify LMM subjects, with clustering on the right side: area of low cellularity, high <i>R</i>/<i>H</i> and low-phase angle. Traditional anthropometric indices were the least effective in identifying LMM-O. The BIVA approach, PhA, <i>R</i> and <i>R</i>/<i>H</i> are effective in the screening of LMM and LMM-O, irrespective of age, gender, intra- and extracellular hydration status</p>