Background/Objectives <p>Food Frequency Questionnaires (FFQs) are widely used in nutritional epidemiology, particularly in substitution modelling to estimate health effects of dietary changes. This review examines validation practices in substitution modelling studies using FFQ-derived data published between 2018 and 2024.</p> Subjects/Methods <p>A total of 100 studies from 21 countries were included. We assessed the presence and quality of validation data for FFQ variables used in substitution models, focusing on reported validation metrics and correspondence with reference methods.</p> Results <p>Fifty-three percent of studies used unvalidated FFQ-derived variables in modelling. Among those providing validation data, correlation coefficients with reference methods ranged from 0.12 to 0.77 (median, Q1–Q3: 0.43, 0.30 to 0.50). Minimal or no documentation was found in 62% of studies. In some cases, deviations from reference values exceeded 450%. Studies using unvalidated inputs were frequently published in high-impact journals.</p> Conclusions <p>The widespread use of unvalidated FFQ variables and the broad variability in validation quality raise concerns about the reliability of substitution modelling outcomes. Given the role of these studies in informing dietary guidelines, consistent validation protocols and improved reporting standards are urgently needed.</p> <p></p>

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The (ab)use of food frequency questionnaire data in substitution modelling in nutritional epidemiology: a critique

  • Jimmy Chun Yu Louie,
  • Jahar Bhowmik

摘要

Background/Objectives

Food Frequency Questionnaires (FFQs) are widely used in nutritional epidemiology, particularly in substitution modelling to estimate health effects of dietary changes. This review examines validation practices in substitution modelling studies using FFQ-derived data published between 2018 and 2024.

Subjects/Methods

A total of 100 studies from 21 countries were included. We assessed the presence and quality of validation data for FFQ variables used in substitution models, focusing on reported validation metrics and correspondence with reference methods.

Results

Fifty-three percent of studies used unvalidated FFQ-derived variables in modelling. Among those providing validation data, correlation coefficients with reference methods ranged from 0.12 to 0.77 (median, Q1–Q3: 0.43, 0.30 to 0.50). Minimal or no documentation was found in 62% of studies. In some cases, deviations from reference values exceeded 450%. Studies using unvalidated inputs were frequently published in high-impact journals.

Conclusions

The widespread use of unvalidated FFQ variables and the broad variability in validation quality raise concerns about the reliability of substitution modelling outcomes. Given the role of these studies in informing dietary guidelines, consistent validation protocols and improved reporting standards are urgently needed.