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[Aggregation of cardiovascular risk factors: alcohol, smoking, excess weight, and short sleep duration in adolescents in the ERICA study].

Gabriela OliveiraThiago Luiz Nogueira da SilvaIsabel Batista da Silva RibeiroEvandro da Silva Freire CoutinhoKatia Vergetti BlochElizabete Regina Araújo de Oliveira
Published in: Cadernos de saude publica (2019)
This study aimed to analyze the aggregation of alcohol consumption, smoking, excess weight, and short sleep in Brazilian adolescents. This was a cross-sectional multicenter study conducted with teens participating in the Study of Cardiovascular Risk Factors in Adolescents (ERICA in Portuguese). The sample consisted of adolescents that answered the complete questionnaires on sleep, tobacco, and alcoholic beverages, in addition to having their weight and height measured. Aggregation was analyzed by comparing the observed and expected prevalence of risk factors in all possible groupings, with the respective 95% confidence intervals. Analyses were performed in Stata 14 using the svy (survey) command for complex sample data. The sample included 73,624 adolescents, of whom 25.5% had excess weight and 24.2% consumed alcoholic beverages. Aggregation of the four risk factors was O/E = 5.6. Aggregation of three factors was more prevalent in those 15 to 17 years of age (P = 4.8). In the POR (prevalence odds ratio) analysis of the combination of two risk factors, those that smoked showed 11.80 higher odds of also consuming alcohol, compared to those that did not smoke, and vice versa, in private schools. In relation to age, adolescents 12 to 14 years of age that smoked showed 15.46 times higher odds of also drinking, and vice and versa. Adolescents in the sample presented the aggregate presence of four risk factors, and there was a significant relationship between tobacco and alcohol consumption.
Keyphrases
  • risk factors
  • physical activity
  • alcohol consumption
  • young adults
  • cardiovascular risk factors
  • body mass index
  • weight loss
  • healthcare
  • weight gain
  • sleep quality
  • machine learning
  • health insurance