AUTHOR=Westenbrink Susanne , Tenhagen Cyrelle J. , Toxopeus Ido , Verkaik-Kloosterman Janneke , Feskens Edith J. M. , Ocké Marga 

TITLE=Procedure to identify fortified foods in the Dutch branded food database

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2024.1366083

DOI=10.3389/fnut.2024.1366083

ISSN=2296-861X

ABSTRACT=Introduction: Information on fortified foods is needed for multiple purposes, including food consumption research and dietary advice. Branded food databases are a valuable source of food label data. European labelling legislation prescribes that food fortification should be indicated in the ingredient list and nutrient values should be declared under certain conditions. This creates the potential to identify fortified foods in branded food databases, though it is not straightforward and labor intense. The aim of our study was to develop an automated approach to identify fortified foods in the Dutch branded food database called LEDA.Methods: An automated procedure, based on a stepwise approach conforming with European labelling legislation, using a list of rules and search terms was developed to identify fortified foods. Fortification with calcium, folic acid, vitamin B12, and zinc was studied as an example. Results of a random stratified sample with fortified and not-fortified foods were validated by two experts.Results: The automated approach resulted in the identification of 1,817 foods fortified with one or more of the selected nutrients in the LEDA dataset (0.94%). The proportions of fortified foods per nutrient were below 0.7%. Classification of fortified/non-fortified foods matched manual validation by experts for the majority of the foods in the sample; i.e. sensitivity and specificity indicating the probability to correctly indicate fortified and non-fortified foods was high (>94.0%).The automated approach is capable of easily and quickly identifying fortified foods in the Dutch branded food database with high accuracy, although some improvements to the automated procedure could be made. Also, completeness, correctness and consistency of the LEDA database can be improved. To fully benefit from this automated approach, it needs to be expanded to cover all micronutrients that may be added to foods.