Key result
Relative Fat Mass correlates most strongly with overall metabolic burden, outperforming BMI in overweight adults.
Why the study?
As the prevalence of obesity increases, more precise stratification tools beyond BMI are needed to assess metabolic health.
Do waist-based and alternative anthropometric indices (RFM, WHtR, ABSI, BRI, CI, WWI) show stronger associations with composite metabolic laboratory burden than BMI in adults with BMI > 25 kg/m²?
Cross-Sectional (n=401)
No
Do waist-based and alternative anthropometric indices (RFM, WHtR, ABSI, BRI, CI, WWI) show stronger associations with composite metabolic laboratory burden than BMI in adults with BMI > 25 kg/m²?
Answers are grounded in this paper and cite their sources.
Waist-based anthropometric indices, particularly Relative Fat Mass (RFM) and waist-to-height ratio (WHtR), are more strongly associated with overall, lipid, and hepatic metabolic laboratory burden than BMI in routine outpatient obesity care.
Background and aim : Body mass index (BMI) is the cornerstone of obesity classification. As the prevalence of obesity as a chronic disease increases, more precise stratification tools are being explored. The aim of this study is to compare established and alternative anthropometric parameters in terms of their association with metabolic health indices in adults with BMI > 25 kg/m 2 . Materials and methods : Cross-sectional analysis was performed on first-visit assessment data of 401 individuals from an outpatient endocrinology clinic. Weight, height, and waist circumference values were used to calculate the following anthropometrics: waist-to-height ratio (WHtR), Body Shape Index (ABSI), Body Roundness Index (BRI), Conicity Index (CI), Weight-adjusted Waist Index (WWI), and Relative Fat Mass (RFM). The outcomes of interest were metabolic laboratory indices of glycemia (FPG, HbA1c), lipid metabolism (LDL, TG), and hepatic enzymes (ALT, GGT). After log-transformation, they were standardized and combined into glycemic, lipid, hepatic, and overall metabolic burden composite scores. Hierarchical linear regression models adjusted for age and sex were used to measure the association between each anthropometric index and the composite scores. Incremental explained variance (ΔR2) and regression coefficients were compared. Results : The strongest association with the overall metabolic composite was shown by RFM (β = 0.480, 95% Cl = 0.269-0.692; ΔR 2 = 0.085), followed by WHtR (ΔR 2 = 0.080), BMI (ΔR 2 = 0.076), and BRI (ΔR 2 = 0.076). ABSI, Cl, and WWI showed no significant incremental contributions. BMI showed the largest ΔR 2 for the glycemic composite, whereas RFM ranked highest for lipid and hepatic composites. Conclusion : Waist-based indices – particularly RFM and WHtR – were most consistently associated with composite metabolic laboratory burden in routine outpatient practice.
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Ivanov et al. (2026) conducted a cross-sectional in Overweight or obesity (BMI > 25 kg/m²) (n=401). Relative Fat Mass (RFM) and alternative anthropometric indices (WHtR, ABSI, BRI, CI, WWI) vs. Body Mass Index (BMI) was evaluated on Overall metabolic burden composite score (mean of standardized log-transformed glycemic [FPG, HbA1c], lipid [LDL-C, TG], and hepatic [ALT, GGT] domain scores) (β = 0.480 (ΔR² = 0.085), 95% CI 0.269-0.692, p=<0.001). Relative Fat Mass showed the strongest association with overall metabolic burden (β = 0.480, 95% CI 0.269-0.692, p < 0.001; ΔR² = 0.085), outperforming BMI (ΔR² = 0.076) in adults with BMI > 25 kg/m².
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