Related Experiment Video
Updated: Aug 30, 2026

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq
Published on: March 19, 2021
Systematic review of nutrient profile models for front-of-pack nutrition labelling
Margarida Bica1, Jessica Renzella2, Asha Kaur3
1Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Abstract:
Front-of-pack nutrition labelling (FOPNL) systems, based on underlying nutrient profile models (NPMs) that classify foods according to their nutritional composition, are key policies for tackling diet-related non-communicable diseases. Yet, the growing number of NPMs poses a challenge for policymakers to select appropriate models for FOPNL policies. This systematic review identifies and characterizes the NPMs developed and/or used for FOPNL systems, from both peer-reviewed and grey literature. We identified 42 NPMs, of which 15 were developed for warning labels, 11 for nutrient-specific systems (including traffic-light labelling), 11 for health endorsements, 4 for summary scores and 1 for other systems. All NPMs limited the content of sugar, and most limited sodium and saturated fat. Convergent and criterion validity were demonstrated for nine and three NPMs, respectively. Considerable heterogeneity across NPMs suggests limited consensus on what constitutes the most appropriate NPM for FOPNL, reinforcing the need for greater regional guidance and alignment.
Related Concept Videos
Key Elements for Plant Nutrition
Pharmacokinetic Models: Overview
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.