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Advancing digital nutrition assessment: development and evaluation of the UK eNutriFFQv2.0

  • Michelle Weech
  • , Rosalind Fallaize
  • , Rodrigo Zenun Franco
  • , Rachel Sutton
  • , Maria Fotiou
  • , Nicole Robertson
  • , Faustina Hwang
  • , Julie A Lovegrove

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
3 Downloads (Pure)

Abstract

Background: Digital dietary assessment tools are highly beneficial for nutrition research and personalised interventions.
Objective: This paper describes the development and evaluation of eNutriFFQv2.0, an updated online food frequency questionnaire designed to reflect current diets in the United Kingdom (UK). Updates included modernised food lists based on recent UK population surveys, food composition tables, and food portion photos to improve accuracy and user experience.
Methods: To assess reproducibility, UK adults completed the FFQ twice, 14 days apart; validity was evaluated against a 3-day weighed food record in a sub sample. Multiple statistical methods were used. After excluding participants with unfeasible energy intakes, 87 participants completed the reproducibility and 53 the evaluation.
Results: The final eNutriFFQv2.0 captured 164 items and estimated intake for 56 nutrients and 6 food groups. Agreement with the WFR was acceptable to good for 25 out of the 29 nutrients analysed (weighted kappa 0.21- 0.77), with ≤10% misclassification into opposite quartiles for most nutrients. Bland-Altman plots showed good agreement for energy (176kcal/d higher in FFQ1) and macronutrient estimates. Reproducibility was good for 24 out of the 29 nutrients analysed (weighted kappa 0.58-0.85) with <5% misclassification. Mean bias for estimates of carbohydrate, fat and protein were small (0.0-0.7). Energy estimates were 209kcal/d (10.7%) higher in the first compared with second completion of the FFQ. Conclusions: These findings demonstrate that eNutriFFQv2.0 is a valid and reliable tool for assessing nutrient intake in UK adults, offering a practical, scalable solution for research and public health in the context of digital health and personalised dietary interventions.
Original languageEnglish
Article number113212
Number of pages14
JournalNutrition
Volume149
Early online date20 Mar 2026
DOIs
Publication statusE-pub ahead of print - 20 Mar 2026

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