Obesity has reached epidemic proportions around the developed world, and the prevalence still seems to be steadily increasing. Great attention in recent years has focused on the prevalence of obesity in adolescents, relative to the potential risks of developing chronic diseases in adulthood. Recent focus on anthropometric measurements of obesity (e.g. waist circumference, body composition estimated via bioelectrical impedance analysis, estimations of body fat and skeletal muscle mass) has shifted attention to a homeostatic model assessment of insulin resistance (HOMA-IR).
A recent study conducted in New York aimed to determine the most accurate measurements to predict insulin resistance in both obese and non-obese subjects. Nearly 1300 predominantly Hispanic and African American subjects between 14 and 20 years of age (714 females and 584 males) were recruited and measured for body mass index; serum triglycerides, glucose and insulin, and HOMA-IR.
This study found that waist circumference combined with body fat percentage was the best predictor of HOMA-IR. While body mass index was found to be poor in predicting insulin resistance, the prospect of measuring body fat composition versus lean muscle mass in adolescents holds promise in detecting insulin resistance during this age range.
Most relevant to men's health, this model of prediction for males predicted a higher percentage of variance compared to females. The secondary conclusion of this study suggests that body fat composition has a higher likelihood of predicting HOMA-IR in leaner subjects. The authors admit that the lack of significant ethnic diversity may present a limitation in interpretation of results. In conclusion, body mass index is not sufficient for assessing insulin resistance, as waist circumference and body fat composition lend more accurate prediction of insulin resistance.
Reference: Wedin W, Diaz-Gimenez L, Convit AJ. Prediction of insulin resistance with anthropometric measure: lessons from a large adolescent population. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2012;5:219-225.