Bioelectrical impedance parameters associated with metabolic obesity phenotypes and metabolic syndrome: a cross-sectional study

Obesity is metabolically heterogeneous; however, clinically accessible markers to distinguish metabolically healthy (MHO) from metabolically unhealthy (MUO) obesity phenotypes remain scarce. This study aimed to evaluate associations of bioelectrical impedance analysis (BIA)-derived parameters with metabolic obesity phenotypes (MHO and MUO) and with metabolic syndrome (MetS), and to characterize these phenotypes using bioelectrical impedance vector analysis (BIVA). In this retrospective observational study, 1,460 participants aged 16–83 years (BMI range: 19.0–69.4 kg/m²) underwent single-frequency phase-sensitive bioelectrical impedance analysis (BIA). MetS was defined according to NCEP ATP III criteria. The final analysis included 1,033 adults with obesity. Resistance (R), reactance (Xc), and phase angle (PhA) were assessed. R and Xc were normalized for height (R/H and Xc/H) and interpreted using BIVA. Among 1,033 adults with obesity, MetS was present in 645 participants, whereas 657 met the criteria for MUO according to the adopted definition. Compared with individuals with MHO, those with MUO exhibited significantly lower Xc, Xc/H, and PhA values (all p < 0.05), whereas R and R/H did not differ significantly. BIVA demonstrated a significant downward displacement of impedance vectors in participants with MUO, consistent with lower Xc/H values. Lower PhA values were independently associated with both the MUO phenotype and the presence of MetS. Receiver operating characteristic analysis identified PhA thresholds of ≤ 5.2° in men and ≤ 5.6° in women as the optimal cut-off values for identifying participants with metabolic syndrome, although their discriminatory performance was modest. Xc and PhA were associated with metabolic phenotype and MetS, but had modest ability to discriminate between MHO and MUO. When integrated using BIVA, these parameters may provide complementary, non-invasive information on tissue quality for metabolic risk stratification in obesity. However, the modest discriminatory performance suggests that these thresholds should be considered exploratory and require further validation before clinical application.