Association between dietary patterns and overweight/obesity: a Brazilian national school-based research (ERICA 2013–2014).

Autor: de Almeida Alves, Mariane, Retondario, Anabelle, Bricarello, Liliana Paula, Fernandes, Ricardo, de Moura Souza, Amanda, Zeni, Lucia Andréia Zanette Ramos, de Moraes Trindade, Erasmo Benicio Santos, de Assis Guedes de Vasconcelos, Francisco
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Zdroj: Journal of Public Health (09431853); Apr2020, Vol. 28 Issue 2, p163-171, 9p
Abstrakt: Aim: The aim of this study was to identify dietary patterns and verify their association with overweight/obesity. Subjects and methods: This was a cross-sectional study conducted with a probabilistic sample of 71,298 Brazilian adolescents aged between 12 and 17 years, who participated in the Study of Cardiovascular Risk in Adolescents (ERICA). ERICA is a multicenter school-based countrywide cross-sectional study, conducted in 2013–2014. Food consumption was estimated with a single 24-h dietary recall, and factor analysis was conducted to identify dietary patterns. To test the association between dietary patterns and overweight/obesity, we performed logistic regression analyses. Results: The prevalence of overweight/obesity was 25.4% (95% CI 24.3–26.6). Three dietary patterns were identified: "traditional Brazilian" (beans, rice and meat), "unhealthy" (sugar sweetened beverages, processed foods, desserts and cakes, and milk and cheese), and "coffee and bread" (bread, oils and fat, coffee, and processed meat). Adolescents in the highest tertile of the "traditional Brazilian" pattern had lower odds of overweight/obesity (OR 0.85; 95% CI 0.74–0.98; p = 0.033) compared with adolescents in the first tertile. "Coffee and bread" and "unhealthy" dietary patterns were not associated with overweight/obesity. Conclusion: Brazilian adolescents with higher scores on the "traditional Brazilian" pattern had lower odds of being overweight/obese. To promote and enhance the consumption of traditional Brazilian foods may help prevent overweight/obesity in this population. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index