Old and new anthropometric indices as insulin resistance predictors in adolescents

Despite the importance of insulin resistance (IR) on chronic diseases development, its diagnosis remains invasive. Thus, it's necessary to develop alternative methods to predict IR on clinical practice, and the anthropometric indices are a good alternative to it. Given that, this study's purpose is to evaluate these indices behavior in relation to HOMA- IR (Homeostasis Model Assessment of Insulin Resistance). Materials and methods: We collected weight, height and waist circumference from 148 adolescents. Through these indices, we calculated the body mass index (BMI), inverted body mass index (iBMI), waist-to-height ratio (WHtR) and conicity index (C index). We also collected data from body composition (body fat percentage - % BF), through electric impedance, and biochemical data (fasting glucose and insulin levels) employed on the HOMA- IR calculation. The HOMA- IR cutoff adopted was of 2.39 +/- 1.93. The statistical analysis involved the Spearman correlation analysis, multiple linear regression models and ROC (Receiver Operating Characteristic) curves construction, using 95% CI. We used the statistic pack SPSS v. 18, considering p < 0.05 as the significance level. Results: All anthropometric indices were statistically and positively correlated to HOMA- IR. The ROC curve showed that WC, WHtR and C index, in this order, were the most efficient to predict IR. Conclusion: Among the indicators studied, those related to central fat accumulation seem the most suitable for predicting IR.