Evidence map›Paper›PMID 42756998›Full record

ArticleBMJ public health2026

Does the Nutri-Score 2023 algorithm provide consistent classification across European food supplies? A cross-sectional study using branded food composition data from 14 countries.

Chantal Julia, Théo Vasseur, Hélène Alexiou, Joline W J Beulens, Anette E Buyken, Torsten Bohn, Pauline Ducrot, Ann Katrin Engelbert, Marie-Noëlle Falquet, Esther Infanger and 3 more

Abstract read
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Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Chantal JuliaNutritional Epidemiology Research Team, Sorbonne Paris Nord University, INSERM U1153, INRAE U1125, CNAM, Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France.ORCID https://orcid.org/0000-0003-2006-5269
Théo VasseurNutritional Epidemiology Research Team, Sorbonne Paris Nord University, INSERM U1153, INRAE U1125, CNAM, Epidemiology and Statistics Research Center - University of Paris (CRESS), Bobigny, France.
Hélène AlexiouDietetics department, Haute Ecole Leonard de Vinci, Health Sector, Brussels, Belgium.
Joline W J BeulensDepartment of Epidemiology and Data Science, Amsterdam UMC, locatie Vrije Universiteit, Amsterdam, The Netherlands.
Anette E BuykenInstitute of Nutrition, Consumption and Health, Faculty of Natural Science, Paderborn University, Paderborn, Germany.
Torsten BohnNutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
Pauline DucrotSanté publique France, Saint-Maurice, Île-de-France, France.
Ann Katrin EngelbertDepartment of Physiology and Biochemistry of Nutrition, Max Rubner-Institute, Federal Research Institute of Nutrition and Food, Karlsruhe, Germany.
Marie-Noëlle FalquetDepartment of Agricultural, Forest and Food Sciences, Food Science and Management, Bern University of Applied Sciences, Bern, Switzerland.ORCID https://orcid.org/0000-0001-6741-6041
Esther InfangerExternas GmbH, Liebefeld, Switzerland.
Benedikt MerzDepartment of Nutritional Epidemiology and Physiology, Max Rubner-Institut Federal Research Institute of Nutrition and Food, Karlsruhe, Germany.
Elisabeth H M TemmeDepartment for Healthy and Sustainable Nutrition, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
Stefanie VandevijvereDepartment of Epidemiology and Public Health, Sciensano, Brussel, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The Nutri-Score is a summary graded and colour-coded front of pack nutritional label providing an overall assessment of the nutritional value of prepacked products. While its 2023 update has been shown to be consistent with food-based dietary guidelines in the countries in which it has been adopted, its application has not been investigated in a wider geographical area. The objective of this study was to describe the classification of products according to the Nutri-Score in a large number of European Union (EU) countries. Methods: Branded food composition from 14 European countries was obtained from Euromonitor. Food products were classified according to the Nutri-Score algorithm, based on their content in energy (kJ/100 g), saturated fats (g/100 g), sugars (g/100 g), salt (g/100 g), proteins (g/100 g), dietary fibres (g/100 g) and fruit, vegetables and legumes (%/100 g). The distribution of the 2023 and 2015 Nutri-Score classifications was described across countries and food categories. Results: Overall, classification according to the 2023 Nutri-Score was consistent across 408 399 products from 14 countries and consistent with food-based dietary guidelines: >90% of frozen fruit and vegetables or >95% pulses were classified in the more favourable classes of the Nutri-Score (A/B), while >90% of discretionary foods such as chocolate confectionery and sweet biscuits were classified in the less favourable classes (D/E). Cross-country differences in classification reflected underlying variability in nutrient composition of products (eg, salt content in refined breads ranged from 1.05 to 1.23 g/100 g across countries). Conclusion: The Nutri-Score classification appeared consistent across a large geographical area, confirming its potential as an EU-wide front-of-package label. While some residual challenges remain for a limited number of specific product groups (eg, whole-grain pasta or rice), our findings indicate that the 2023 update represents a substantial improvement over the 2015 algorithm.

Indexed as

Nutritive ValuePrimary PreventionPublic Health

Identifiers

PMID42756998
PMCPMC13583817

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