Association between phase angle and ECW/TBW ratio with body composition in individuals with central obesity: a cross-sectional study

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Background Central obesity is closely linked with increased metabolic risk, systemic inflammation, and adverse outcomes. Bioelectrical impedance analysis (BIA) provides phase angle (PhA) and extracellular water to total body water (ECW/TBW) ratio—non-invasive biomarkers reflecting cellular integrity and fluid distribution. However, their relationship with detailed body composition in individuals with central obesity remains underexplored. The study aimed to investigate the associations between PhA and ECW/TBW ratio with body composition parameters in individuals with central obesity. Methods This cross-sectional study was conducted at a tertiary teaching hospital from December 2024 to February 2025. A total of 741 centrally obese adults (waist circumference ≥90 cm for men and ≥80 cm for women) were assessed using BIA. Parameters analyzed included PhA, ECW/TBW, skeletal muscle index (SMI), fat-free mass index (FFMI), fat mass index (FMI), and visceral adipose tissue (VAT). Statistical analysis involved Pearson correlation and multiple linear regression, stratified by sex. Results PhA was positively associated with SMI (B = 0.257 in males, B = 0.251 in females; p < 0.001) and FFMI (p < 0.001), and inversely associated with VAT in males (B = −0.082, p = 0.017). ECW/TBW ratio was positively associated with FMI and VAT in both sexes (p < 0.001) and inversely associated with SMI (p = 0.004 in males, p < 0.001 in females). Adjusted R2 values indicated moderate model fits for muscle-related variables. These findings suggest that lower PhA and higher ECW/TBW ratio are indicative of sarcopenic obesity and fluid imbalance. Conclusion PhA and ECW/TBW ratio are associated with distinct components of body composition in central obesity. PhA reflects lean mass and cellular integrity, whereas ECW/TBW ratio captures fluid imbalance and adiposity, though with modest explanatory power. These findings highlight the potential of BIA-derived parameters as complementary tools in nutritional assessment and risk stratification.

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