Body mass index, waist circumference, and chronic disease risk factors in Australian adolescents

Objective: To determine the association between measures of adiposity (body mass index and waist circumference) and risk factors for heart disease, type 2 diabetes, fatty liver disease, and the clustering of risk factors in middle adolescence. Design: Cross-sectional study. Setting: Secondary schools in Sydney. Participants: Grade 10 students (N = 496; 58.4% boys; mean [SD] age, 15.4 [0.4] years). Main Exposures: Height, weight, waist circumference, blood pressure, and fasting blood samples. Outcome Measures: Participants were categorized as overweight or obese using the International Obesity Task Force cut points and the UK waist circumference cut points. Blood was analyzed for high- and low-density lipoprotein cholesterol, triglycerides, insulin, glucose, alanine aminotransferase, gamma-glutamyltransferase, and high-sensitivity C-reactive protein levels, and the results were categorized as normal or abnormal according to published guidelines where possible. Associations between overweight and obesity and risk factors were explored using logistic regression. Clustering of risk factors within individuals was also explored. Results: Insulin (P <.001), alanine aminotransferase (P <.001), gamma-glutamyltransferase (P=.005), high-density lipoprotein cholesterol (P <.001), high-sensitivity C-reactiveprotein (P <.001), and blood pressure (P <.001) were significantly associated with overweight and obesity in adolescent boys. In adolescent girls, insulin, high-density lipoprotein cholesterol (P <.001), and high-sensitivity C-reactive protein (P <.001) were significantly associated with overweight and obesity. Obese adolescent boys and girls were significantly more likely to have 2 or more risk factors (boys: 73.5% vs 7.6%; girls: 44.4% vs 5.4%; P <.001 for both) than nonoverweight adolescents. Conclusions: Overweight and obese adolescents, especially boys, are at substantial risk for chronic conditions. Waist circumference is not a better predictor of metabolic risk factors than is body mass index.