Dataset Information

Effect of a new graphically modified Nutri-Score on the objective understanding of foods' nutrient profile and ultraprocessing: a randomised controlled trial.

ABSTRACT:

Introduction

When considering health-related impacts of foods, nutrient profile and (ultra)processing are two complementary dimensions. The Nutri-Score informs on the nutrient profile dimension. Recently, mounting evidence linked ultraprocessed food consumption to various adverse health outcomes, independently of their nutrient profile. To inform consumers about each of these health-related dimensions of food, we tested, in a randomised controlled trial, if a graphically modified version 'Nutri-Score V.2.0', including a black 'ultraprocessed' banner, would improve the capacity of consumers to rank products according to their nutrient profile and to detect those ultra-processed, compared with a no-label situation.

Methods

21 159 participants included in the NutriNet-Santé web-cohort were randomly assigned to a control arm (no front-of-pack label) or an experimental arm (Nutri-Score 2.0) and were presented an online questionnaire with three sets of food products (cookies, breakfast cereals and ready-to-eat meals) to rank according to nutrient profile and to identify ultraprocessed foods. The primary outcome was objective understanding of nutrient profile and ultraprocessing, represented by a score of correct answers. Secondary outcomes were purchasing intentions and the healthiest-perceived product. Multinomial logistic regressions were performed.

Results

The Nutri-Score V.2.0 increased the objective understanding of both the nutrient profile dimension (OR _{highest vs lowest score category}=29.0 (23.4-35.9), p<0.001) and the ultraprocessing dimension (OR=174.3 (151.4-200.5), p<0.001). Trends were similar for cookies, breakfast cereals and ready-to-eat meals. The Nutri-Score V.2.0 had a positive effect on purchasing intentions and on the products perceived as the healthiest.

Conclusion

This randomised controlled trial demonstrates the interest of a front-of-pack label combining the Nutri-Score (informing on the nutrient profile dimension) with an additional graphic mention, indicating when the food is ultraprocessed, compared with a no-label situation. Our results show that a combined label enabled participants to independently understand these two complementary dimensions of foods.

Trial registration number

NCT05610930.

SUBMITTER: Srour B

PROVIDER: S-EPMC10359533 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effect of a new graphically modified Nutri-Score on the objective understanding of foods' nutrient profile and ultraprocessing: a randomised controlled trial.

Srour Bernard B Hercberg Serge S Galan Pilar P Monteiro Carlos Augusto CA Szabo de Edelenyi Fabien F Bourhis Laurent L Fialon Morgane M Sarda Barthélémy B Druesne-Pecollo Nathalie N Esseddik Younes Y Deschasaux-Tanguy Mélanie M Julia Chantal C Touvier Mathilde M

BMJ nutrition, prevention & health 20230608 1

<h4>Introduction</h4>When considering health-related impacts of foods, nutrient profile and (ultra)processing are two complementary dimensions. The Nutri-Score informs on the nutrient profile dimension. Recently, mounting evidence linked ultraprocessed food consumption to various adverse health outcomes, independently of their nutrient profile. To inform consumers about each of these health-related dimensions of food, we tested, in a randomised controlled trial, if a graphically modified version ...[more]

PMID: 37484539

Similar Datasets

Project description:Front-of-package nutrition labelling (FOPNL) is known as an effective tool that can encourage healthier food choices and food reformulation. A very interesting type of FOPNL is grading schemes. Our objective was to compare two market-implemented grading schemes-European Nutri-Score (NS) and Australian Health Star Rating (HSR), using large Slovenian branded foods database. NS and HSR were used for profiling 17,226 pre-packed foods and drinks, available in Slovenian food supply dataset (2020). Alignment between models was evaluated with agreement (% of agreement and Cohen's Kappa) and correlation (Spearman rho). The 12-month nationwide sales-data were used for sale-weighing, to address market-share differences. Study results indicated that both models have good discriminatory ability between products based on their nutritional composition. NS and HSR ranked 22% and 33% of Slovenian food supply as healthy, respectively. Agreement between NS and HSR was strong (70%, κ = 0.62) with a very strong correlation (rho = 0.87). Observed profiling models were most aligned within food categories Beverages and Bread and bakery products, while less aligned for Dairy and imitates and Edible oils and emulsions. Notable disagreements were particularly observed in subcategories of Cheese and processed cheeses (8%, κ = 0.01, rho = 0.38) and Cooking oils (27%, κ = 0.11, rho = 0.40). Further analysis showed that the main differences in Cooking oils were due to olive oil and walnut oil, which are favoured by NS and grapeseed, flaxseed and sunflower oil that are favoured by HSR. For Cheeses and cheese products, we observed that HSR graded products across the whole scale, with majority (63%) being classified as healthy (≥3.5 *), while NS mostly graded lower scores. Sale-weighting analyses showed that offer in the food supply does not always reflect the sales. Sale-weighting increased overall agreement between profiles from 70% to 81%, with notable differences between food categories. In conclusion, NS and HSR were shown as highly compliant FOPNLs with few divergences in some subcategories. Even these models do not always grade products equally high, very similar ranking trends were observed. However, the observed differences highlight the challenges of FOPNL ranking schemes, which are tailored to address somewhat different public health priorities in different countries. International harmonization can support further development of grading type nutrient profiling models for the use in FOPNL, and make those acceptable for more stake-holders, which will be crucial for their successful regulatory implementation.

Project description:BACKGROUND:To improve nutritional status and prevent chronic nutrition-related diseases, international organizations have recommended the use of multiple strategies, including front-of-package nutrition labelling (FOPL). In France, the Nutri-Score has been selected by health authorities in March 2017. However, to be effective in purchasing situations, the label needs to be well understood, which may be influenced by label format and sociodemographic characteristics. This study aimed at investigating the objective understanding of the Nutri-Score compared to other label formats, and more particularly among specific at-risk populations. METHODS:The objective understanding of four FOPLs-namely Nutri-Score, Multiple Traffic Lights (MTL), the simplified nutrition labelling system (SENS), and modified Reference Intakes (mRIs)-was investigated in a sample from the NutriNet-Santé French cohort (n = 3,751). Logistic regression mixed models were computed to assess the association of the four FOPLs, compared to a "no label" situation, on the consumers' ability to rank products according to their overall nutritional quality. Objective understanding was also investigated according to sociodemographic and lifestyle characteristics. RESULTS:Compared to a "no label" situation, all FOPLs were significantly associated to an increase in consumers' ability to classify the products correctly, with wide disparities in results according to formats. The best performance was observed for the Nutri-Score (OR = 20.33(17.68-23.37)), followed by SENS (OR = 9.57(8.50-10.77)), MTL (OR = 3.55(3.20-3.93)) and mRIs (OR = 1.53(1.39-1.69)). This ranking was similar among all sub-populations and the ORs associated to the Nutri-Score were over 10, whichever the sub-group considered. Women, younger people, non-smokers, individuals with higher educational level and those with children had a higher capacity to identify healthier products (all P≤0.05). CONCLUSION:Nutri-Score, with a summarized graded and color-coded format, using semantic colours, is associated to a higher objective understanding than monochrome and nutrient-specific labels. Furthermore, though objective understanding may differ according to individual characteristics of subjects, the magnitude of effect of the Nutri-Score largely outweighed this effect, even in the at-risk populations.

Project description:BackgroundThe Nutri-Score is a candidate for the harmonized mandatory front-of-pack nutrition label enabling consumers in the European Union to make healthier food choices. Nutri-Score classifies foods (including beverages) from A (high nutritional quality) to E (low nutritional quality) based on the foods' qualifying and disqualifying components. We aimed to evaluate the updated Nutri-Score for foods (2022) and beverages (2023) in a Norwegian setting by exploring its ability to discriminate the nutritional quality of foods within categories. Additionally, we assessed Nutri-Scores' ability to classify foods in accordance with the Norwegian food-based dietary guidelines (FBDGs).MethodsThe updated Nutri-Score was calculated for 1,782 foods in a Norwegian food database. The discriminatory ability of the updated Nutri-Score was considered by exploring the distribution of Nutri-Score within categories of foods using boxplots and frequency tables, and by examining which qualifying and disqualifying components that contributed most to the Nutri-Score class. Accordance with the Norwegian FBDGs was assessed by exploring Nutri-Score for foods specifically mentioned in the guidelines.ResultsOverall, the updated Nutri-Score seemed to discriminate the nutritional quality of foods within categories, in a Norwegian setting. The foods' content of salt and the beverages' content of sugar were components contributing the most to Nutri-Scores' discriminatory ability. Furthermore, in most cases the updated Nutri-Score classified foods in accordance with the Norwegian FBDGs. However, there were minor inconsistencies in how Nutri-Score classified certain foods, such as the inabilities to discriminate between full-fat and low-fat/leaner cheeses, cremes and processed meats (sausages), and between whole grain and refined pasta/rice.ConclusionsWe observed an overall acceptable discriminatory performance of the updated Nutri-Score in a Norwegian setting and in most cases the updated Nutri-Score classified foods in accordance with the Norwegian FBDGs. However, minor inconsistencies were observed. Together with the FBDGs, the updated Nutri-Score could be a useful tool in guiding consumers towards healthier food choices in Norway, but consumer evaluations are warranted to fully assess the performance of the updated Nutri-Score in a Norwegian context.

Dataset Information

Effect of a new graphically modified Nutri-Score on the objective understanding of foods' nutrient profile and ultraprocessing: a randomised controlled trial.

Introduction

Methods

Results

Conclusion

Trial registration number

Publications

Effect of a new graphically modified Nutri-Score on the objective understanding of foods' nutrient profile and ultraprocessing: a randomised controlled trial.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets