Conicity Index and Other Anthropometric Indices in Relation to Visceral Fat Percentage in Adolescents with Overweight or Obesity: A Cross-Sectional Study

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Background Adolescent obesity is an increasing public health concern, particularly in South Asian populations where central adiposity and excess adiposity at relatively lower body mass index (BMI) are frequently observed. Visceral adiposity is a key determinant of cardiometabolic risk, but direct assessment using computed tomography or magnetic resonance imaging is impractical for routine clinical use. Anthropometric indices are therefore widely used as surrogate markers. The conicity index (CI), a composite measure incorporating waist circumference (WC), body weight, and height, has been proposed as an indicator of central fat distribution; however, its utility in overweight and obese adolescents remains uncertain. This study assessed the correlation between the CI and bioelectrical impedance analysis (BIA)-derived visceral fat percentage (VF%) in adolescents who are overweight and obese and compared its predictive performance with that of conventional anthropometric indices. Methods This hospital-based cross-sectional analytical study included 120 adolescents with overweight and obesity aged 10-19 years recruited by consecutive sampling from a tertiary care center in Maharashtra, India. Anthropometric indices, including BMI, WC, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), abdominal volume index (AVI), body adiposity index (BAI), and CI, were calculated using standard formulae. Body composition measurements, including VF%, were estimated using bioelectrical impedance analysis (Omron Karada Scan device, Omron Healthcare Co., Ltd., Kyoto, Japan). Because several variables were non-normally distributed, correlations were assessed using Spearman's rank correlation, and hierarchical multiple linear regression was used to identify independent predictors of VF%. Results The median age of participants was 13.0 years (IQR 10.8-15.0), with a balanced sex distribution. WC and AVI showed the strongest correlations with VF% (ρ = 0.707 each, p < 0.001), followed by BMI (ρ = 0.696, p < 0.001). WHtR and WHR showed moderate correlations, whereas the CI demonstrated only a weak correlation with VF% (ρ = 0.267, p = 0.003). The CI was not significantly correlated with total body fat (BF%), subcutaneous fat (SCF), or fat mass index (FMI). In regression analysis, the base model including age, sex, and BMI explained 53.4% of the variance in VF%. Addition of WC significantly improved model performance (ΔR² = 0.091, p < 0.001; final R² = 0.624), whereas addition of the CI provided a smaller improvement (ΔR² = 0.049, p < 0.001). In the final model, BMI and WC were the only significant independent predictors. Conclusion The CI showed a statistically significant but weak correlation with VF% in this hospital-based cohort of adolescents who were overweight and obese, and its predictive performance was inferior to simpler measures, particularly BMI and WC. WC remains a practical and reliable anthropometric marker of central adiposity in this population. The CI may have a supplementary or research role but appears to provide limited additional value over conventional measures in this population.

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