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Objective: To estimate the prevalence of excessive weight and to identify associations with socioeconomic, demographic, biological, and lifestyle factors in adolescents. Methods: It is a cross-sectional school-based study, with a stratified and complex sample. The evaluated individuals were adolescents (2404), aged 12–17 years old, participating in the Study of Cardiovascular Risk Factors in Adolescents (ERICA). Demographic, socioeconomic, biological, anthropometric, and lifestyle variables were assessed. Poisson regression was used to verify the association between excess weight and independent variables. Results: The prevalence of excessive weight was 26.3% in the study population, being 16.3% for overweight and 10% for obesity. In the multivariate analysis (hierarchical model), were associated with excessive weight: private education network, a higher number of televisions in the residence, eating habits related to the breakfast consumption, snacks purchase in the canteen, snacks in front to screens consumption and consumption of carbohydrates and lipids, in addition to age group (12–14 years) and sexual maturation (post-pubertal). Conclusions: The prevalence of excessive weight among the school adolescents studied is high, with a value higher than the national average and the results of previous studies with adolescents. Its distribution is associated with different factors, which are socioeconomic, demographic, biological, and related to lifestyle, reinforcing the complexity of this condition, which deserves a broad coping approach, involving not only individual efforts but social and public ones as well.

ABSTRACT Objective: To identify the prevalence of insulin resistance in adolescents and its associations with metabolic factors and food intake. Methods: Cross-sectional study conducted with a stratified, complex, school-based sample. The subjects were adolescents (n=1,081) who participated in the Study of Cardiovascular Risk in Adolescents in the city of Recife (Pernambuco, Brazil). We analyzed demographic, socioeconomic, behavioral, anthropometric, biochemical, and dietary variables. Insulin resistance was defined as HOMA-IR>75th percentile. A Poisson multivariate regression model with robust variance adjustment was used, and variables with p≤0.05 in the final model were considered statistically associated with insulin resistance. Results: Median age was 14 years (interquartile range: 13-16 years), and 25.3% of the sample showed insulin resistance. The variables associated with insulin resistance in the final model were age, body mass index-for-age (BMI/A), biochemical markers (triglycerides and high-density lipoprotein cholesterol) and saturated fat intake, with insulin resistance being more prevalent in individuals whose consumption of this type of fat was below the median of the sample distribution. Conclusions: Insulin resistance was prevalent in the adolescents analyzed and was significantly associated with metabolic variables and saturated fat intake.