Adolescence is a stage in life characterized by important social, cognitive, and physical changes. Adolescents are vulnerable to various psychosocial disorders, including eating disorders. We aimed to investigate the association between unhealthy habits, sociodemographic characteristics, and the practice of self-induced vomiting or laxative misuse in a representative sample of Brazilian adolescent girls and boys. Data from 102,072 students who participated in the National Adolescent School-based Health Survey were analyzed using the dependent variable: presence or absence of self-induced vomiting and/or laxative misuse; independent variables: consumption of unhealthy and high-calorie food items, age during first sexual intercourse, and the use of tobacco, alcohol, and/or illicit drugs. Associations between exposure and outcome were estimated using Poisson’s regression models stratified by sex, and including region, school, age group, and mother's educational history as adjustment variables. Eating ultra-processed foods and age during first sexual intercourse were associated with self-induced vomiting and laxative misuse only for girls; all other variables (consuming unhealthy foods and using legal or illicit substances) were associated with these behaviors for both sexes after applying adjustment variables. Early interventions focusing on changing unhealthy behaviors may prevent development of eating disorders in adolescents. Our findings demonstrate a strong association of many unhealthy habits with laxative misuse and self-induced vomiting practices in Brazilian adolescents.
The Research Group on Children and Adolescents' Health (GPSaCA) contributes to the construction and socialization of public knowledge by developing scientific research on child and adolescent health. This is an important topic because of the serious lack of attention to the healthcare of these individuals in many parts of the world. The group researches and implements activities to improve healthcare education at its institution. Rigorous studies and activities contribute to the educational process and foster healthy habits.
Objetivou-se a análise de algoritmos de mineração de dados que melhor se adequem às condições e dados dos cursos técnicos integrados ao Ensino Médio do Campus Ceres do IF Goiano. A partir da metodologia KDD, foi possível trabalhar com uma amostra de 1.478 matrículas. Com a ferramenta Weka, pôde ser feita a comparação dos algoritmos: J48, Naive Bayes, Logistic, Multilayer Perceptron, IBk e LibSVM. Dentre eles, o LibSVM se mostrou o melhor preditor, alcançando o melhor resultado de três das cinco métricas consideradas no estudo.
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