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The Reproducibility and Relative Validity of a Food Frequency Questionnaire for Identifying Iron-Related Dietary Patterns in Pregnant Women.

Mayra Lizeth Navarro-PadillaMaría Fernanda Bernal-OrozcoJoan Fernández-BallartBarbara Vizmanos-LamotteNorma Patricia Rodriguez RochaGabriela Macedo-Ojeda
Published in: Nutrients (2022)
Analyzing pregnant women's iron intake using dietary patterns would provide information that considers dietary relationships with other nutrients and their sources. The objective of this study was to evaluate the reproducibility and relative validity of a Qualitative Food Frequency Questionnaire to identify iron-related dietary patterns (FeP-FFQ) among Mexican pregnant women. A convenience sample of pregnant women ( n = 110) completed two FeP-FFQ (FeP-FFQ1 and FeP-FFQ2) and a 3-day diet record (3DDR). Foods appearing in the 3DDR were classified into the same food groupings as the FeP-FFQ, and most consumed foods were identified. Exploratory factor analysis was used to determine dietary patterns. Scores were compared (FeP-FFQ for reproducibility and FeP-FFQ1 vs. 3DDR for validity) through intraclass correlation coefficients (ICC), cross-classification, Bland-Altman analysis, and weighed Cohen kappa (κw), using dietary patterns scores tertiles. Two dietary patterns were identified: "healthy" and "processed foods and dairy". ICCs ( p < 0.01) for "healthy" pattern and "processed foods and dairy" pattern were 0.76 for and 0.71 for reproducibility, and 0.36 and 0.37 for validity, respectively. Cross-classification and Bland-Altman analysis showed good agreement for reproducibility and validity; κw values showed moderate agreement for reproducibility and low agreement for validity. In conclusion, the FeP-FFQ showed good indicators of reproducibility and validity to identify dietary patterns related to iron intake among pregnant women.
Keyphrases
  • pregnant women
  • machine learning
  • healthcare
  • iron deficiency
  • human health
  • climate change
  • high intensity
  • toll like receptor
  • risk assessment