[{"publication_status":"published","date_updated":"2026-10-15T10:09:18Z","intvolume":"         4","year":"2026","title":"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","status":"public","author":[{"first_name":"Chantal","last_name":"Julia","full_name":"Julia, Chantal"},{"full_name":"Vasseur, Théo","first_name":"Théo","last_name":"Vasseur"},{"first_name":"Hélène","last_name":"Alexiou","full_name":"Alexiou, Hélène"},{"last_name":"Beulens","first_name":"Joline WJ","full_name":"Beulens, Joline WJ"},{"id":"65985","full_name":"Buyken, Anette","last_name":"Buyken","first_name":"Anette"},{"full_name":"Bohn, Torsten","last_name":"Bohn","first_name":"Torsten"},{"first_name":"Pauline","last_name":"Ducrot","full_name":"Ducrot, Pauline"},{"last_name":"Engelbert","first_name":"Ann Katin","full_name":"Engelbert, Ann Katin"},{"full_name":"Falquet, Marie-Noelle","last_name":"Falquet","first_name":"Marie-Noelle"},{"full_name":"Infanger, Esther","last_name":"Infanger","first_name":"Esther"},{"full_name":"Merz, Benedikt","first_name":"Benedikt","last_name":"Merz"},{"last_name":"Temme","first_name":"Elisabeth H M","full_name":"Temme, Elisabeth H M"},{"full_name":"Vandevijere, Stefanie","last_name":"Vandevijere","first_name":"Stefanie"}],"user_id":"92491","doi":"10.1136/ bmjph-2026-005015","volume":4,"main_file_link":[{"url":"https://bmjpublichealth.bmj.com/content/4/3/e005015"}],"_id":"67538","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"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.\r\n\r\nMethods: 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.\r\n\r\nResults: 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).\r\n\r\nConclusion: 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."}],"issue":"3","publication":"BMJ Public Health","citation":{"chicago":"Julia, Chantal, Théo Vasseur, Hélène Alexiou, Joline WJ Beulens, Anette Buyken, Torsten Bohn, Pauline Ducrot, et al. “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.” <i>BMJ Public Health</i> 4, no. 3 (2026). <a href=\"https://doi.org/10.1136/ bmjph-2026-005015\">https://doi.org/10.1136/ bmjph-2026-005015</a>.","short":"C. Julia, T. Vasseur, H. Alexiou, J.W. Beulens, A. Buyken, T. Bohn, P. Ducrot, A.K. Engelbert, M.-N. Falquet, E. Infanger, B. Merz, E.H.M. Temme, S. Vandevijere, BMJ Public Health 4 (2026).","apa":"Julia, C., Vasseur, T., Alexiou, H., Beulens, J. W., Buyken, A., Bohn, T., Ducrot, P., Engelbert, A. K., Falquet, M.-N., Infanger, E., Merz, B., Temme, E. H. M., &#38; Vandevijere, S. (2026). 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. <i>BMJ Public Health</i>, <i>4</i>(3). <a href=\"https://doi.org/10.1136/ bmjph-2026-005015\">https://doi.org/10.1136/ bmjph-2026-005015</a>","ieee":"C. Julia <i>et al.</i>, “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,” <i>BMJ Public Health</i>, vol. 4, no. 3, 2026, doi: <a href=\"https://doi.org/10.1136/ bmjph-2026-005015\">10.1136/ bmjph-2026-005015</a>.","ama":"Julia C, Vasseur T, Alexiou H, et al. 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. <i>BMJ Public Health</i>. 2026;4(3). doi:<a href=\"https://doi.org/10.1136/ bmjph-2026-005015\">10.1136/ bmjph-2026-005015</a>","bibtex":"@article{Julia_Vasseur_Alexiou_Beulens_Buyken_Bohn_Ducrot_Engelbert_Falquet_Infanger_et al._2026, title={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}, volume={4}, DOI={<a href=\"https://doi.org/10.1136/ bmjph-2026-005015\">10.1136/ bmjph-2026-005015</a>}, number={3}, journal={BMJ Public Health}, author={Julia, Chantal and Vasseur, Théo and Alexiou, Hélène and Beulens, Joline WJ and Buyken, Anette and Bohn, Torsten and Ducrot, Pauline and Engelbert, Ann Katin and Falquet, Marie-Noelle and Infanger, Esther and et al.}, year={2026} }","mla":"Julia, Chantal, et al. “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.” <i>BMJ Public Health</i>, vol. 4, no. 3, 2026, doi:<a href=\"https://doi.org/10.1136/ bmjph-2026-005015\">10.1136/ bmjph-2026-005015</a>."},"type":"journal_article","department":[{"_id":"22"}],"date_created":"2026-10-15T10:08:58Z"}]