Indicadores dietéticos e bioquímicos do controle glicêmico e índice de massa corporal de adolescentes brasileiros

• Ano de defesa: 2020
• Autor(a) principal: Rocha, Camilla Medeiros Macedo da
• Outros Autores: [e-mail]
• Orientador(a): Sichieri, Rosely
• Banca de defesa: Souza, Amanda de Moura, Yooko, Edna Massae, Verly Júnior, Eliseu, Bloch, Katia Vergetti
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade do Estado do Rio de Janeiro
• Programa de Pós-Graduação: Programa de Pós-Graduação em Saúde Coletiva
• Departamento: Centro Biomédico::Instituto de Medicina Social Hesio Cordeiro
• País: Brasil
• Palavras-chave em Português: Índice glicêmico; Carga glicêmica; Consumo de alimentos; Obesidade; Adolescentes; Consumo alimentar; Controle glicêmico; Obesity; Adolescent
• Palavras-chave em Inglês: Glycemic index; Glycemic load; Glycemic control; Intake
• Área do conhecimento CNPq: CIENCIAS DA SAUDE::SAUDE COLETIVA
• Link de acesso: http://www.bdtd.uerj.br/handle/1/20340

To evaluate dietary indicators of carbohydrate consumption in Brazilian adolescents and their association with body mass index (BMI) and glycemic control in adolescents. Methodology: The Study of Cardiovascular Risks in Adolescents (Erica) had a cross-sectional design, school-based and stratified sampling. In the 273 schools visited, between 2013 and 2014, 102,237 adolescents were eligible. Of these, 71,553 had complete information on anthropometry, food consumption and socio-demographic characteristics. As they were diagnosed with diabetes 2,476 adolescents were excluded. Blood samples were available for 40,732 adolescents and 35,737 contributed to glycemic control analyzes with data on fasting insulin, glycated hemoglobin and HOMA-IR. Food consumption was estimated by the 24-hour recall and the dietary glycemic index (DIG) and the dietary glycemic load (DCG) were calculated according to the recommendations of the Food and Agriculture Organization of the United Nations / World Health Organization. Results: There is a wide variation in DGI and DCG during the day, with minimum values observed at lunchtime and higher values at night. The mean insulin was 8.08 (7.98-8.19) mU / L among adolescents with normal weight and 12.71 (12.49-12.94) among overweight / obesity. The HOMA-IR value was 1.72 and 2.75, respectively. DGI and AvGI (average glycemic index) was around 59, with no differences in weight status. DGL and AvGL (average glycemic load) were not associated with glycemic control markers (p values> 0.16), except AvCG in adolescents with normal weight, with the highest values of regression coefficient for insulin (β = 0.12, p value <0.001). Measures of the glycemic index seem to be the best predictors of glycemic control, with greater value for AvGI and insulin (β = 0.23) among overweight / obese adolescents. DIG was positively associated with female BMI z-score when carbohydrate intake was moderate (β = 0.010; p-value = 0.018). The glycemic index of the first meal was also associated with the z-score of BMI in girls, but this relationship was negative (β = -0.003; p-value = 0.053) and only for the highest level of carbohydrate intake. Conclusion: Among overweight / obese adolescents, carbohydrate quality counts more for glycemic control than portion size or peak carbohydrate intake. Even though the glycemic index is a good predictor of the quality of the carbohydrate consumed, our findings do not show that its increase affects the BMI z-score. The glycemic load proved to be only a proxy for the total consumption of energy and carbohydrates, which did not allow investigating the relationship between the quality of the carbohydrate consumed, the glycemic control and the z-score of the adolescents' BMI.