Food Labelling & Reformulation

Branded food databases, food labelling, and reformulation

Branded foods databases are becoming very valuable not only in nutrition research but also for clinical practice, policymakers, businesses, and the general population. This because the percentage of branded foods that consumers purchase compared to generic foods is steadily increasing. In contrast to generic foods, branded foods are marked by rapid changes because of reformulations, the introduction of new foods, and the removal of existing ones from the market. Reliable data about the composition of branded foods is essential to provide insights into those changes.

Explore different methods to generate branded food datasets, examples of available tools and services for who wants to use such datasets, and a series of case studies developed in the FNS-Cloud project for the different types of users of branded food datasets.

How are branded food datasets generated?

Food label information can be sourced from food manufacturers and retailers, from physical food labels, or from web pages with labelling data of branded foods (i.e. online food stores, manufacturer’s web pages, etc.). In the FNS-Cloud project, we used and compared various approaches to generate a harmonised branded food dataset, which was used for a series of demonstration case studies.

Learn more about Food Monitoring Studies in this video.

Services and tools for branded food datasets

This section details examples of available resources for users of branded food datasets that were used or generated in the FNS-Cloud project.

Users of branded food datasets

The aim of the “food labelling & reformulation” demonstrator is to showcase how food label data and branded food databases can be useful to a wide range of users, from researchers to policy makers, consumers, food businesses, app developers and clinical practitionners. The cases studies below illustrate differents aspects of the use of food labelling data.

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