Evidence map›Paper›PMID 40810819›Full record

ArticleEuropean journal of nutrition2025

Beyond "validated": the need for more rigorous reporting of food frequency questionnaire validation metrics in nutritional epidemiology.

Jimmy Chun Yu Louie

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Article in European journal of nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jimmy Chun Yu LouieDiscipline of Dietetics, Department of Allied Health, School of Health Sciences, Swinburne University of Technology, Room 203, SPW Building, 1 John St, Hawthorn, VIC, 3122, Australia. jimmylouie@swin.edu.au.ORCID http://orcid.org/0000-0001-7736-605X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis paper examines current practices in reporting food frequency questionnaire (FFQ) validation and energy adjustment in nutritional epidemiology, highlighting how oversimplified reporting can mask important limitations and potentially lead to misleading conclusions in diet-health research.

methodsA critical analysis of common FFQ validation reporting practices was presented, using hypothetical scenarios and real-world examples to demonstrate how different patterns of measurement error can yield similar overall correlation coefficients. This article examines the interplay between FFQ validation and energy adjustment methods, illustrating how measurement errors can persist even after energy adjustment.

resultsThe analysis reveals that current reporting practices often fail to capture the context-dependent nature of FFQ validation, particularly when examining specific food groups or dietary patterns. It demonstrates how high correlation coefficients for total nutrient intake can mask poor measurement of specific dietary components, and how energy adjustment methods, while valuable, operate under specific assumptions that require validation themselves.

conclusionsThis article proposes a structured framework for comprehensive validation reporting that includes exposure-specific validation metrics, detailed energy adjustment methodology, and measurement error assessment. This framework aims to enhance transparency in nutritional epidemiology research and improve the interpretation of diet-health relationships. Implementing these recommendations will enable more accurate assessment of FFQ-based research and ultimately contribute to more reliable dietary recommendations. 210 words.

Indexed as

DietDiet SurveysValidation Studies as TopicEnergy IntakeHumansReproducibility of ResultsSurveys and QuestionnairesDietary assessmentFood frequency questionnaireMeasurement errorNutritional epidemiologyReportingValidation methodsValidity

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.