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Iodine Intake and its Interindividual Variability in Brazilian Pregnant Women: EMDI Brazil Study.

Débora Letícia Frizzi SilvaSandra Patrícia CrispimGabriele Beraldi SilvaFrancilene Maria AzevedoJuliana Farias de NovaesCarolina Abreu de CarvalhoDanielle Góes da SilvaEdimar Aparecida Filomeno FontesMariana de Souza MacedoSylvia do Carmo Castro Franceschini
Published in: Biological trace element research (2023)
Data on pregnant women's iodine intake are limited in Brazil. The aim of the study was to evaluate the contribution of foods, food groups, and food subgroups to the Brazilian pregnant women's iodine intake, and identify which food items explain the interindividual variability of their intake. A cross-sectional study with food consumption data of 2247 pregnant women from 24-h recalls was developed. Food items were classified according to the FAO/WHO GIFT classification, and their contribution to iodine intake and interindividual variability was assessed by the proportion of means method and linear regression, respectively. The mean usual iodine intake was 163.1 mcg (95% CI: 162.9-163.2). The food groups "spices and condiments," "cereals and their products," and "milk and milk products"; and the food subgroups "herbs and spices," "wheat and wheat-based products," "milk: fresh and processed," "dough-based sweets," and "eggs: fresh and processed" contributed to at least 80% of the iodine intake. Of these, only the food subgroups "milk," "dough-based sweets," and "eggs" did not explain the higher proportion (> 80%) of the interindividual variability. The contribution of "salt," "white French bread," "fluid whole milk," and "rice" to the iodine intake and its interindividual variability is highlighted. This study confirms the importance of "salt" as a dietary source of iodine and that few food groups and subgroups explained the difference in the iodine intake among pregnant women. Despite that, Brazilian staple foods, such as "rice," "beans," "eggs," "milk," and "bread" were identified as important for iodine intake and could be included in nutritional guidelines targeted to Brazilian pregnant women.
Keyphrases
  • pregnant women
  • dual energy
  • weight gain
  • human health
  • machine learning
  • computed tomography
  • pregnancy outcomes
  • physical activity
  • magnetic resonance imaging
  • body mass index
  • big data
  • risk factors