Independent predictors of insulin resistance in Brazilian adolescents: Results of the study of cardiovascular risk in adolescents–Brazil

Considering the current changes in dietary patterns and the increasing prevalence of excess weight throughout the world, several studies have reported insulin resistance, which is a key driver of many chronic diseases, to be an important public health problem in all age groups. Therefore, the aim of the present study was to identify the prevalence and independent predictors of insulin resistance in Brazilian adolescents. A cross-sectional study was conducted with a probabilistic, representative sample of Brazilian adolescents (n = 37,023) who participated in the Study of Cardiovascular Risk in Adolescents. Data were collected on demographic, socioeconomic, lifestyle, anthropometric, and biochemical characteristics as well as antioxidant micronutrient intake (vitamins A, C, E, zinc, and selenium). Insulin resistance was determined using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and classified based on the 75th percentile of the sample distribution. Insulin resistance was detected in 27% of the adolescents and was more prevalent among those aged 12 to 14 years (PR: 1.26 [95%CI: 1.13;1.41]), those residing in the southern and south-eastern regions of the country (PR: 1.47 [95%CI: 1.27;1.70]), those who were physically inactive (PR: 1.12 [95%CI: 1.02;1.23]), and those did not consume alcohol (PR: 1.50 [95%CI: 1.13;1.99]). The prevalence of insulin resistance was 2.5-fold higher among individuals with severe obesity (PR: 2.49 [95%CI: 2.07;3.00]). Waist circumference indicative of cardiovascular risk and high serum triglyceride levels increased the likelihood of insulin resistance (PR: 1.37 [95%CI: 1.19;1.59] and 1.60 [95%CI: 1.45;1.78], respectively). The prevalence of the outcome was higher among adolescents in the lower quartiles of vitamin E intake (p<0.05). In the present study, the prevalence of insulin resistance was high among Brazilian adolescents and we identified sociodemographic, lifestyle, anthropometric, biochemical, and dietary predictors of this outcome.