Nutri-Score of Meat, Fish, and Dairy Alternatives: A Comparison between the Old and New Algorithm
Abstract
:1. Introduction
2. Materials and Methods
2.1. Product Selection and Data Collection
2.2. Nutri-Score Calculation
2.3. Data Analysis
3. Results
3.1. Nutri-Score for Meat, Fish, and Cold Cuts Alternatives
3.2. Nutri-Score for Milk, Dessert, and Cheese Alternatives
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- World Health Organization. World Health Statistics 2023: Monitoring Health for the SDGs, Sustainable Development Goals; World Health Organization: Geneva, Switzerland, 2023; Available online: https://www.who.int/publications/i/item/9789240074323 (accessed on 11 October 2023).
- Willett, W.; Rockström, J.; Loken, B.; Springmann, M.; Lang, T.; Vermeulen, S.; Garnett, T.; Tilman, D.; DeClerck, F.; Wood, A.; et al. Food in the Anthropocene: The EAT-Lancet Commission on Healthy Diets from Sustainable Food Systems. Lancet 2019, 393, 447–492. [Google Scholar] [CrossRef]
- Our World in Data. Daily Protein Supply from Animal and Plant-Based Foods, 1962 to 2020. Available online: https://ourworldindata.org/grapher/daily-protein-supply-from-animal-and-plant-based-foods?tab=table (accessed on 7 March 2024).
- National Institute for Public Health and the Environment (RIVM). Voedselconsumptiepeiling (VCP) 2019–2021. Available online: https://www.wateetnederland.nl/resultaten/energie-en-macronutrienten/eiwitten (accessed on 7 March 2024).
- Ministry of Agriculture, Nature and Food Quality. National Protein Strategy; Ministry of Agriculture, Nature and Food Quality: The Hague, The Netherlands, 2020. Available online: https://zoek.officielebekendmakingen.nl/blg-969245.pdf (accessed on 7 March 2024).
- Ferrari, L.; Panaite, S.-A.; Bertazzo, A.; Visioli, F. Animal- and Plant-Based Protein Sources: A Scoping Review of Human Health Outcomes and Environmental Impact. Nutrients 2022, 14, 5115. [Google Scholar] [CrossRef]
- Crowe, F.L.; Appleby, P.N.; Travis, R.C.; Key, T.J. Risk of Hospitalization or Death from Ischemic Heart Disease among British Vegetarians and Nonvegetarians: Results from the EPIC-Oxford Cohort Study. Am. J. Clin. Nutr. 2013, 97, 597–603. [Google Scholar] [CrossRef]
- Huang, T.; Yang, B.; Zheng, J.; Li, G.; Wahlqvist, M.L.; Li, D. Cardiovascular Disease Mortality and Cancer Incidence in Vegetarians: A Meta-Analysis and Systematic Review. Ann. Nutr. Metab. 2012, 60, 233–240. [Google Scholar] [CrossRef] [PubMed]
- Simonson, M.; Boirie, Y.; Guillet, C. Protein, Amino Acids and Obesity Treatment. Rev. Endocr. Metab. Disord. 2020, 21, 341–353. [Google Scholar] [CrossRef]
- Najjar, R.S.; Feresin, R.G. Plant-Based Diets in the Reduction of Body Fat: Physiological Effects and Biochemical Insights. Nutrients 2019, 11, 2712. [Google Scholar] [CrossRef] [PubMed]
- Turner-Mcgrievy, G.M.; Davidson, C.R.; Wingard, E.E.; Billings, D.L. Low Glycemic Index Vegan or Low-Calorie Weight Loss Diets for Women with Polycystic Ovary Syndrome: A Randomized Controlled Feasibility Study. Nutr. Res. 2014, 34, 552–558. [Google Scholar] [CrossRef] [PubMed]
- Klementova, M.; Thieme, L.; Haluzik, M.; Pavlovicova, R.; Hill, M.; Pelikanova, T.; Kahleova, H. A Plant-Based Meal Increases Gastrointestinal Hormones and Satiety More Than an Energy- and Macronutrient-Matched Processed-Meat Meal in T2D, Obese, and Healthy Men: A Three-Group Randomized Crossover Study. Nutrients 2019, 11, 157. [Google Scholar] [CrossRef]
- Ivanova, S.; Delattre, C.; Karcheva-Bahchevanska, D.; Benbasat, N.; Nalbantova, V.; Ivanov, K. Plant-Based Diet as a Strategy for Weight Control. Foods 2021, 10, 3052. [Google Scholar] [CrossRef] [PubMed]
- Brink, E.; Postma-Smeets, A.; Stafleu, A.; Wolvers, D. Richtlijnen Schijf van Vijf, 6th ed.; Voedingscentrum: The Hague, The Netherlands, 2020. [Google Scholar]
- Smart Protein Project. Plant-Based Foods in Europe: How Big Is the Market? Available online: https://smartproteinproject.eu/plant-based-food-sector-report/ (accessed on 17 January 2023).
- Smart Protein Project. Plant-Based Foods in Europe: What Do Consumers Want? Available online: https://smartproteinproject.eu/consumer-attitudes-plant-based-food-report/ (accessed on 19 December 2022).
- Cutroneo, S.; Angelino, D.; Tedeschi, T.; Pellegrini, N.; Martini, D.; SINU Young Working Group. Nutritional Quality of Meat Analogues: Results from the Food Labelling of Italian Products (FLIP) Project. Front. Nutr. 2022, 9, 852831. [Google Scholar] [CrossRef]
- Katidi, A.; Xypolitaki, K.; Vlassopoulos, A.; Kapsokefalou, M. Nutritional Quality of Plant-Based Meat and Dairy Imitation Products and Comparison with Animal-Based Counterparts. Nutrients 2023, 15, 401. [Google Scholar] [CrossRef]
- Pointke, M.; Pawelzik, E. Plant-Based Alternative Products: Are They Healthy Alternatives? Micro- and Macronutrients and Nutritional Scoring. Nutrients 2022, 14, 601. [Google Scholar] [CrossRef] [PubMed]
- Fructuoso, I.; Romão, B.; Han, H.; Raposo, A.; Ariza-Montes, A.; Araya-Castillo, L.; Zandonadi, R.P. An Overview on Nutritional Aspects of Plant-Based Beverages Used as Substitutes for Cow’s Milk. Nutrients 2021, 13, 2650. [Google Scholar] [CrossRef] [PubMed]
- Batista, M.F.; de Carvalho-Ferreira, J.P.; Thimoteo da Cunha, D.; De Rosso, V.V. Front-of-Package Nutrition Labeling as a Driver for Healthier Food Choices: Lessons Learned and Future Perspectives. Compr. Rev. Food Sci. Food Saf. 2023, 22, 535–586. [Google Scholar] [CrossRef] [PubMed]
- Santé Publique France. Available online: https://www.santepubliquefrance.fr/en/nutri-score (accessed on 14 October 2021).
- Egnell, M.; Crosetto, P.; D’almeida, T.; Kesse-Guyot, E.; Touvier, M.; Ruffieux, B.; Hercberg, S.; Muller, L.; Julia, C. Modelling the Impact of Different Front-of-Package Nutrition Labels on Mortality from Non-Communicable Chronic Disease. Int. J. Behav. Nutr. Phys. Act. 2019, 16, 56. [Google Scholar] [CrossRef] [PubMed]
- Egnell, M.; Talati, Z.; Galan, P.; Andreeva, V.A.; Vandevijvere, S.; Gombaud, M.; Dréano-Trécant, L.; Hercberg, S.; Pettigrew, S.; Julia, C. Objective Understanding of the Nutri-Score Front-of-Pack Label by European Consumers and Its Effect on Food Choices: An Online Experimental Study. Int. J. Behav. Nutr. Phys. Act. 2020, 17, 146. [Google Scholar] [CrossRef] [PubMed]
- Goiana-da-Silva, F.; Cruz-e-Silva, D.; Nobre-da-Costa, C.; Nunes, A.M.; Fialon, M.; Egnell, M.; Galan, P.; Julia, C.; Talati, Z.; Pettigrew, S.; et al. Nutri-Score: The Most Efficient Front-of-Pack Nutrition Label to Inform Portuguese Consumers on the Nutritional Quality of Foods and Help Them Identify Healthier Options in Purchasing Situations. Nutrients 2021, 13, 4335. [Google Scholar] [CrossRef]
- Shrestha, A.; Cullerton, K.; White, K.M.; Mays, J.; Sendall, M. Impact of Front-of-Pack Nutrition Labelling in Consumer Understanding and Use across Socio-Economic Status: A Systematic Review. Appetite 2023, 187, 106587. [Google Scholar] [CrossRef]
- Monteiro, C.A.; Cannon, G.; Lawrence, M.; Costa Louzada, M.L.; Pereira Machado, P. Ultra-Processed Foods, Diet Quality, and Health Using the NOVA Classification System; Food and Agriculture Organization of the United Nations: Rome, Italy, 2019; Available online: https://www.fao.org/3/ca5644en/ca5644en.pdf (accessed on 23 January 2024).
- Health Council of the Netherlands. Evaluation of the Nutri-Score Algorithm; Health Council of the Netherlands: The Hague, The Netherlands, 2022. Available online: https://www.healthcouncil.nl/binaries/healthcouncil/documenten/advisory-reports/2022/11/29/evaluation-of-the-nutri-score-algorithm/Advisory-report_Evaluation-of-the-Nutri-Score-algorithm.pdf (accessed on 23 January 2024).
- Huybers, S.; Roodenburg, A.J.C. Cross-Sectional Study to Map Nutritional Quality of Meat, Fish, and Dairy Alternatives in Dutch Supermarkets According to the Dutch Food-Based Dietary Guidelines and Nutri-Score. Foods 2023, 12, 1738. [Google Scholar] [CrossRef]
- Rodríguez-Martín, N.M.; Córdoba, P.; Sarriá, B.; Verardo, V.; Pedroche, J.; Alcalá-Santiago, Á.; García-Villanova, B.; Molina-Montes, E. Characterizing Meat- and Milk/Dairy-like Vegetarian Foods and Their Counterparts Based on Nutrient Profiling and Food Labels. Foods 2023, 12, 1151. [Google Scholar] [CrossRef]
- de las Heras-Delgado, S.; Shyam, S.; Cunillera, È.; Dragusan, N.; Salas-Salvadó, J.; Babio, N. Are Plant-Based Alternatives Healthier? A Two-Dimensional Evaluation from Nutritional and Processing Standpoints. Food Res. Int. 2023, 169, 112857. [Google Scholar] [CrossRef] [PubMed]
- Øvrebø, B.; Brantsæter, A.L.; Lund-Iversen, K.; Andersen, L.F.; Paulsen, M.M.; Abel, M.H. How Does the Updated Nutri-Score Discriminate and Classify the Nutritional Quality of Foods in a Norwegian Setting? Int. J. Behav. Nutr. Phys. Act. 2023, 20, 122. [Google Scholar] [CrossRef]
- Sarda, B.; Kesse-Guyot, E.; Deschamps, V.; Ducrot, P.; Galan, P.; Hercberg, S.; Deschasaux-Tanguy, M.; Srour, B.; Fezeu, L.K.; Touvier, M.; et al. Consistency of the Initial and Updated Version of the Nutri-Score with Food-Based Dietary Guidelines: A French Perspective. J. Nutr. 2024, 154, 1027–1038. [Google Scholar] [CrossRef]
- Sarda, B.; Kesse-Guyot, E.; Deschamps, V.; Ducrot, P.; Galan, P.; Hercberg, S.; Deschasaux-Tanguy, M.; Srour, B.; Fezeu, L.K.; Touvier, M.; et al. Complementarity between the Updated Version of the Front-of-Pack Nutrition Label Nutri-Score and the Food-Processing NOVA Classification. Public Health Nutr. 2024, 27, e63. [Google Scholar] [CrossRef]
- Galán, P.; Babio, N.; Salas Salvadó, J. Scientific Update of Nutri-Score: Improvements to Correct Some of Its Limitations and to Ensure Greater Consistency with Nutritional Recommendations. Nutr. Hosp. 2022, 39, 1417–1426. [Google Scholar] [CrossRef]
- Health Council of the Netherlands. Findings on and Description of the Revised Nutri-Score Algorithm; Health Council of the Netherlands: The Hague, The Netherlands, 2022. Available online: https://www.healthcouncil.nl/binaries/healthcouncil/documenten/advisory-reports/2022/11/29/evaluation-of-the-nutri-score-algorithm/Background-document_Findings-on-and-description-of-the-revised-Nutri-Score-algorithm.pdf (accessed on 6 February 2024).
- Merz, B.; Temme, E.; Alexiou, H.; Beulens, J.W.J.; Buyken, A.E.; Bohn, T.; Ducrot, P.; Falquet, M.-N.; Solano, M.G.; Haidar, H.; et al. Nutri-Score 2023 update. Nat. Food 2024, 5, 102–110. [Google Scholar] [CrossRef] [PubMed]
- National Institute for Public Health and the Environment (RIVM). Voedselconsumptiepeiling (VCP) 2012–2016. Available online: https://www.wateetnederland.nl/resultaten/mineralen/calcium (accessed on 22 November 2022).
- Collings, R.; Harvey, L.J.; Hooper, L.; Hurst, R.; Brown, T.J.; Ansett, J.; King, M.; Fairweather-Tait, S.J. The Absorption of Iron from Whole Diets: A Systematic Review. Am. J. Clin. Nutr. 2013, 98, 65–81. [Google Scholar] [CrossRef] [PubMed]
Nutri-Score General | ||||||||
---|---|---|---|---|---|---|---|---|
Nutritional quality | ||||||||
Nutri-Score Old | Nutri-Score New | |||||||
Product categories |
|
| ||||||
General Foods Old | General Foods New | Beverages Old | Beverages New | |||||
Specific profiling characteristics |
|
|
|
| ||||
Range (min–max) of allocated points with the related nutritional values per component: | Points | Values/100 g | Points | Values/100 g | Points | Values/100 mL | Points | Values/100 mL |
Energy (KJ) | 0–10 | ≤335–≥3350 | 0–10 | ≤335–≥3350 | 0–10 | 0–≥270 | 0–10 | ≤30–≥390 |
SFA (g) | 0–10 | ≤1–≥10 | 0–10 | ≤1–≥10 | 0–10 | ≤1–≥10 | 0–10 | ≤1–≥10 |
Sugar (g) | 0–10 | ≤4.5–≥45 | 0–15 | ≤3.4–≥51 | 0–10 | 0–≥13.5 | 0–10 | ≤0.5–≥11 |
Salt (g) | 0–10 | ≤0.225–≥2.25 | 0–20 | ≤0.2–≥4 | 0–10 | ≤0.225–≥2.25 | 0–20 | ≤0.2–≥4 |
Protein (g) | 0–5 | ≤1.6–≥8.0 | 0–7 | ≤2.4–≥17 | 0–5 | ≤1.6–≥8.0 | 0–7 | ≤1.2–≥3 |
Fiber (g) | 0–5 | ≤0.9–≥4.7 | 0–5 | ≤3.0–≥7.4 | 0–5 | ≤0.9–≥4.7 | 0–5 | ≤3.0–≥7.4 |
FVL (%) 1 | 0–5 | ≤40–≥80 | 0–5 | ≤40–≥80 | 0–5 | ≤40–≥80 | 0–6 | ≤40–≥80 |
NNS | 0–4 | absent–present | ||||||
FSAm-NPS score: | ||||||||
Nutri-Score A | Min to −1 | Min to 0 | Waters | Waters | ||||
Nutri-Score B | 0 to 2 | 1 to 2 | Min to 1 | Min to 2 | ||||
Nutri-Score C | 3 to 10 | 3 to 10 | 2 to 5 | 3 to 6 | ||||
Nutri-Score D | 11 to 18 | 11 to 18 | 6 to 9 | 7 to 9 | ||||
Nutri-Score E | 19 to max | 19 to max | 10 to max | 10 to max |
Unit | Nutri-Score A Old (n = 223) | Nutri-Score A New (n = 161) | Nutri-Score B Old (n = 76) | Nutri-Score B New (n = 73) | Criteria | |
---|---|---|---|---|---|---|
Protein | E% | 32.7 (20.7–46.0) | 41.3 (28.4–49.9) * | 23.3 (13.7–33.9) | 30.3 (20.4–41.2) * | ≥20 |
Meet criteria (%) | 75 | 88 | 59 | 75 | ||
Fiber | g/100 g | 5.10 (3.80–6.40) | 5.50 (3.25–6.55) | 3.40 (1.85–4.28) | 4.00 (1.80–5.68) | x |
Meet criteria (%) | x | x | x | x | ||
Energy | Kcal/100 g | 175 (135–205) | 165 (127–198) * | 202 (176–241) | 186 (168–219) * | x |
Meet criteria (%) | x | x | x | x | ||
Sugar | g/100 g | 1.30 (0.60–2.80) | 1.00 (0.50–2.25) | 1.80 (1.00–2.8) | 1.50 (0.70–2.45) | x |
Meet criteria (%) | x | x | x | x | ||
SFA | g/100 g | 0.90 (0.60–1.30) | 0.90 (0.60–1.20) | 1.25 (0.90–2.00) | 1.00 (0.75–1.55) * | ≤2.5 |
Meet criteria (%) | 94 | 94 | 83 | 93 | ||
Salt | g/100 g | 1.10 (0.84–1.30) | 1.00 (0.55–1.20) | 1.30 (1.10–1.49) | 1.30 (1.10–1.49) | ≤1.125 |
Meet criteria (%) | 60 | 65 | 34 | 27 | ||
Iron | mg/100 g | 0.00 (0.00–2.10) | 0.00 (0.00–2.10) | 0.00 (0.00–2.10) | 0.00 (0.00–2.10) | ≥0.8 |
Meet criteria (%) | 33 | 27 | 32 | 44 | ||
VitB12 | mcg/100 g | 0.00 (0.00–0.38) | 0.00 (0.00–0.30) | 0.00 (0.00–0.30) | 0.00 (0.00–0.38) | ≥0.24 |
Meet criteria (%) | 31 | 27 | 26 | 38 |
Unit | Nutri-Score A Old (n = 64) | Nutri-Score A New (n = 0) | Nutri-Score B Old (n = 137) | Nutri-Score B New (n = 84) | Criteria | |
---|---|---|---|---|---|---|
Protein | E% | 5.18 (27.60–36.04) | x | 4.94 (2.34–10.29) | 15.38 (5.00–31.58) * | ≥20 |
Meet criteria (%) | 59 | 3 | 45 | |||
Fiber | g/100 g | 1.05 (0.50–3.85) | x | 0.30 (0.10–0.60) | 0.50 (0.13–1.38) * | x |
Meet criteria (%) | x | x | x | |||
Energy | Kcal/100 g | 41.0 (35.3–52.0) | x | 45.0 (26.5–53.0) | 34.0 (24.0–46.5) * | x |
Meet criteria (%) | x | x | x | |||
Sugar | g/100 g | 0.60 (0.00–2.45) | x | 3.80 (0.30–5.50) | 0.00 (0.00–0.80) * | ≤6 |
Meet criteria (%) | 98 | 80 | 100 | |||
SFA | g/100 g | 0.30 (0.20–0.40) | x | 0.20 (0.10–0.40) | 0.30 (0.20–0.40) | ≤1.1 |
Meet criteria (%) | 100 | 91 | 96 | |||
Salt | g/100 g | 0.09 (0.00–0.11) | x | 0.10 (0.08–0.13) | 0.09 (0.03–0.11) * | ≤0.15 |
Meet criteria (%) | 92 | 96 | 98 | |||
Ca | mg/100 g | 0.00 (0.00–120) | x | 0.00 (0.00–120) | 0.00 (0.00–120) | ≥80 |
Meet criteria (%) | 41 | 34 | 39 | |||
VitB12 | mcg/100 g | 0.00 (0.00–0.38) | x | 0.00 (0.00–0.35) | 0.00 (0.00–0.38) | ≥0.24 |
Meet criteria (%) | 39 | 28 | 37 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Huybers, S.; Roodenburg, A.J.C. Nutri-Score of Meat, Fish, and Dairy Alternatives: A Comparison between the Old and New Algorithm. Nutrients 2024, 16, 892. https://doi.org/10.3390/nu16060892
Huybers S, Roodenburg AJC. Nutri-Score of Meat, Fish, and Dairy Alternatives: A Comparison between the Old and New Algorithm. Nutrients. 2024; 16(6):892. https://doi.org/10.3390/nu16060892
Chicago/Turabian StyleHuybers, Sylvie, and Annet J. C. Roodenburg. 2024. "Nutri-Score of Meat, Fish, and Dairy Alternatives: A Comparison between the Old and New Algorithm" Nutrients 16, no. 6: 892. https://doi.org/10.3390/nu16060892
APA StyleHuybers, S., & Roodenburg, A. J. C. (2024). Nutri-Score of Meat, Fish, and Dairy Alternatives: A Comparison between the Old and New Algorithm. Nutrients, 16(6), 892. https://doi.org/10.3390/nu16060892