| Autor: |
Cacau LT; Faculdade de Saúde Pública, Universidade de São Paulo., Sampaio HAC; Centro de Ciências da Saúde. Universidade Estadual do Ceará., Carioca AAF; Centro de Ciências da Saúde. Universidade de Fortaleza., Bezerra IN; Centro de Ciências da Saúde. Universidade Estadual do Ceará., Pinheiro LGP; Faculdade de Medicina. Universidade Federal de Ceará., Vasques PHD; Faculdade de Medicina. Universidade Federal de Ceará., Rocha DC; Centro de Ciências da Saúde. Universidade Estadual do Ceará., Meneses AF; Centro de Ciências da Saúde. Universidade Estadual do Ceará., Mendes ALRF; Centro de Ciências da Saúde. Universidade Estadual do Ceará. |
| Abstrakt: |
Introduction: Introduction: inadequate consumption of micronutrients is an emerging public health problem that can compromise health. Objectives: to assess whether the quality of dietary carbohydrates is associated with the consumption of 13 micronutrients in a sample of women monitored by the Brazilian Unified Health System. Methods: this cross-sectional study included 648 women monitored by the Brazilian Unified Health System. The association between quality of dietary carbohydrates and adequacy of consumption of 13 micronutrients was investigated using logistic regression models adjusted for potential confounding variables. Results: the consumption of micronutrients increased as the quality of carbohydrates improved. The micronutrients with the highest prevalence of inadequate intake were vitamin A, magnesium, manganese, and thiamine. After adjustments using logistic regression models, women in the third tertile of the carbohydrate quality index were less likely to have an inadequate consumption of magnesium (odds ratio (OR), 0.29; 95 % confidence interval (CI), 0.14-0.59), manganese (OR, 0.32; 95% CI, 0.21-0.49), and copper (OR, 0.22; 95% CI, 0.12-0.37). Conclusions: intake of a higher quality of dietary carbohydrates is associated with improved adequacy in consumption of most micronutrients in women monitored by the Brazilian Unified Health System, especially magnesium, manganese, and copper, after adjustment using regression models. |
