The influence of the Nutri-Score on the perceived healthiness of foods labelled with a nutrition claim of sugar.
Jürkenbeck K, Mehlhose C, Zühlsdorf A.
PLoS ONE 17(8): e0272220.
https://doi.org/10.1371/journal.pone.0272220
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0272220
Abstract
High sugar intake in humans is associated with the development of overweight and other diet-related diseases. The World Health Organization and other health organizations recommend limiting the sugar intake to 10% of the total energy intake. There have been different approaches of front-of-pack labelling to reduce the amount of sugar in food products. Companies use nutrition claims to advertise the sugar content (e.g., without added sugar, 30% less sugar). Such nutrition claims can lead to false assumptions about the healthiness of foods and can lead to health-halo effects. Nutrition claims make products appear healthier than they really are, the aspect advertised in the nutrition claim is transferred to the entire food product. As a result, food products can be perceived as healthy even though they are not. Recently, the Nutri-Score was introduced in an increasing number of countries throughout Europe to provide consumers with an overview of the overall nutritional quality of a product. This study analyzes if the Nutri-Score can help to prevent health-halo effects caused by nutrition claims on sugar. Therefore, an online survey consisting of a split-sample design with more than 1,000 respondents was assessed. The results show that, depending on the initial perceived healthiness of a product, the Nutri-Score is able to prevent health-halo effects caused by claims on sugar. Making the Nutri-Score mandatory when using nutrition claims would be one possible way to reduce misperceptions about unhealthy food and reduce health-halo effects caused by claims on sugar.
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An 18-country analysis of the effectiveness of five front-of-pack nutrition labels
Pettigrew S, Jongenelis M, Jones A, Hercberg S, Julia C
Food Quality and Preference,
2022, 104691, ISSN 0950-3293,
https://doi.org/10.1016/j.foodqual.2022.104691.
https://www.sciencedirect.com/science/article/abs/pii/S0950329322001665?via%3Dihub
Abstract
Various front-of-pack food labels (FoPLs) are being introduced across the world, and discussion continues about the most effective label formats to improve consumers’ (i) understanding of the relative healthiness of alternative products and (ii) product choices. Of increasing interest is the relative ability of different types of labels to steer consumers away from unhealthy options (aversion) versus steer them towards healthier options (attraction). The aim of this study was to assess aversion and attraction outcomes for five FoPLs (Health Star Rating, Multiple Traffic Lights, Nutri-Score, Reference Intakes, and Warning Label) across 18 countries (n=18393). Descriptive analyses assessed improvements in consumer understanding and choice outcomes for each label across three different types of food products. Binary logistic regressions were used to compare the relative ability of the labels to improve respondents’ understanding of product healthiness and their product choices, using the industry-developed Reference Intakes as the comparator. Aversion and attraction effects were assessed for each label/food type combination. Across the total sample, the Nutri-Score performed best in terms of both attraction and aversion results for understanding and simulated choice outcomes, followed by the Multiple Traffic Lights. The Reference Intakes exhibited the weakest performance overall, with the Warning Label and Health Star Rating falling in between. The most effective FoPLs featured a colour-coded spectrum design. The results indicate that front-of-pack labels that are effective in guiding consumers towards healthier food products can also be effective in steering them away from unhealthy options.
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Toward a differentiated understanding of the effect of Nutri-Score nutrition labeling on healthier food choices
Gassler B, Faesel CK, Moeser A
Agribusiness, July 29th, 2022
https://onlinelibrary.wiley.com/doi/10.1002/agr.21762
Abstract
By 2022, the European Commission seeks to introduce harmonized, mandatory front-of-pack (FOP) nutrition labeling. The color-graded Nutri-Score is at the heart of the European debate. Yet, little is known about how the information provided in back-of-pack (BOP) nutrition tables interacts with evaluative FOP labels, such as Nutri-Score, and if different consumer groups use both information cues differently when making food choices. Our objective is thus to identify segments of nutrition label users and contrast their choice behavior and use of FOP and BOP nutritional information. Therefore, this study builds on an attitude-based segmentation analysis and a survey-based discrete choice experiment among German consumers. We identify five segments of nutritional information users and significant interaction effects between FOP and BOP nutritional cues. Consumers use supplementary nutritional information differently: relying on BOP nutrition facts only (label-resisters) or combining both information cues (majority). For most, Nutri-Score reinforces the positive effect of a healthier nutrient profile on purchase likelihood, while its use stigmatizes products of low nutritional quality. Overall, supplementary Nutri-Score labeling enables better alignment of food choices and health preferences, especially for consumers overwhelmed by technical BOP nutrition tables, and helps differentiate products with relatively unhealthy nutritional profiles. We discuss implications for food policy and business. [EconLit citations: D12, Q13, Q18].
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Respective contribution of ultra-processing and nutritional quality of foods to the overall diet quality: results from the NutriNet-Santé study.
Julia C, Baudry J, Fialon M, Hercberg S, Galan P, Srour B, Andreeva VA, Touvier M, Kesse-Guyot E.
Eur J Nutr. 2022 Aug 4. doi: 10.1007/s00394-022-02970-4. Epub ahead of print. PMID: 35925444.
https://link.springer.com/article/10.1007/s00394-022-02970-4#citeas
Abstract
Background
Both the nutritional quality of the foods consumed (as nutrient composition) and their ultra-processed nature have been linked to health risks. However, the respective contribution of each of these correlated dimensions or their synergy to the overall diet quality has been rarely explored.
Objective
To identify the respective effects of the nutritional quality of the foods consumed, the ultra-processed nature of foods and their cross-effect contributing to the overall quality of the diet.
Design
Cross-sectional observational study.
Setting
Web-based French NutriNet-Santé cohort study.
Participants
Participants in the NutriNet-Santé cohort study with at least three available 24 h records as baseline dietary data (N = 98 454 participants).
Main outcome measures
The overall quality of the diet (qualified using the adherence to the 2017 French national nutrition and health dietary recommendations dietary score PNNS-GS2) was broken down into: (1) an effect of the nutritional quality of the foods consumed (qualified using the modified Foods Standards Agency nutrient profile model (underlying the Nutri-Score) dietary index FSAm-NPS DI); (2) an effect of the ultra-processed nature of the foods consumed (qualified using the proportion of ultra-processed foods consumed UPFp using the NOVA classification), and (3) a cross-effect of both dimensions.
Results
The overall effect from the ‘nutritional quality of the foods consumed’ (FSAm-NPS DI) was 1.10, corresponding to 26% of the total effect; the overall effect from ultra-processed foods consumption was 1.29, corresponding to 30% of the total effect; and cross-effect between nutritional quality of the foods consumed and ultra-processing was at 1.91, corresponding to 44% of total effects.
Conclusions
Our study provides support to the postulate that nutritional quality and ultra-processing should be considered as two correlated but distinct and complementary dimensions of the diet.
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Cross-sectional comparisons of dietary indexes underlying nutrition labels: nutri-score, Canadian ‘high in’ labels and Diabetes Canada Clinical Practices (DCCP).
Paper, L., Ahmed, M., Lee, J.J, Kesse-Guyot E, Touvier M, Hercberg S, Galan P, Salanave B, Verdot C, L’Abbé MR, Deschamps V, Julia C
Eur J Nutr (2022).
https://doi.org/10.1007/s00394-022-02978-w
Abstract
Purpose
To assess the cross-sectional association between dietary indexes (DI) that underlie, respectively, the Nutri-score (NS), the proposed Canadian ‘High In’ Symbol (CHIL) and the Diabetes Canada Clinical Practice Guidelines (DCCP) with food consumption, nutrient intakes and metabolic markers.
Methods
1836 adults (18–74 years) participating in the representative ESTEBAN study, conducted in mainland France in 2014–2016, were included in the analysis. Food consumption was assessed with three repeated 24 h dietary recalls. Anthropometric measurements and biomarkers of metabolic risk (cholesterol—total, LDL (Low Density Lipoprotein), HDL (High Density Lipoprotein)—triglycerides, glucose) were obtained through a clinical examination and fasting blood draw. The DI were assessed for their association with food consumption, dietary intakes and metabolic biomarkers as quintiles and continuous variables using multi-adjusted linear regression. Heathier diets were assigned to lower scores.
Results
Correlations between scores ranged from + 0.62 between CHIL-DI and NS-DI to + 0.75 between NS-DI and DCCP-DI. All DIs discriminated individuals according to the nutritional quality of their diets through food consumption and nutrient intakes (healthier diets were associated with lower intakes of energy, added sugars and saturated fat; and with higher intakes of fiber, vitamins and minerals). NS-DI was associated with blood glucose (adjusted mean in Q1 = 5 vs. Q5 = 5.46 mmol/dl, ptrend = 0.001) and DCCP-DI was associated with BMI (Q1 = 24.8 kg/m2 vs. Q5 = 25.8 kg/m2, ptrend = 0.025), while CHIL showed no significant association with any anthropometric measures or biomarkers.
Conclusions
This study provides elements supporting the validity of the nutrient profiling systems underlying front-of-package nutrition labellings (FOPLs) to characterize the healthiness of diets.
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Estimating the environmental impacts of 57,000 food products
Clark M, Springmann M, Rayner M, Scarborough P, Hill J, Tilman D, Macdiarmid JI, Fanzo J, Bandy L, Harrington RA
PNAS, August 8, 2022, 119 (33) e2120584119
https://doi.org/10.1073/pnas.2120584119
Abstract
Understanding and communicating the environmental impacts of food products is key to enabling transitions to environmentally sustainable food systems [El Bilali and Allahyari, Inf. Process. Agric. 5, 456–464 (2018)]. While previous analyses compared the impacts of food commodities such as fruits, wheat, and beef [Poore and Nemecek, Science 360, 987–992 (2018)], most food products contain numerous ingredients. However, because the amount of each ingredient in a product is often known only by the manufacturer, it has been difficult to assess their environmental impacts. Here, we develop an approach to overcome this limitation. It uses prior knowledge from ingredient lists to infer the composition of each ingredient, and then pairs this with environmental databases [Poore and Nemecek Science 360, 987–992 (2018); Gephart et al., Nature 597, 360–365 (2021)] to derive estimates of a food product’s environmental impact across four indicators: greenhouse gas emissions, land use, water stress, and eutrophication potential. Using the approach on 57,000 products in the United Kingdom and Ireland shows food types have low (e.g., sugary beverages, fruits, breads), to intermediate (e.g., many desserts, pastries), to high environmental impacts (e.g., meat, fish, cheese). Incorporating NutriScore reveals more nutritious products are often more environmentally sustainable but there are exceptions to this trend, and foods consumers may view as substitutable can have markedly different impacts. Sensitivity analyses indicate the approach is robust to uncertainty in ingredient composition and in most cases sourcing. This approach provides a step toward enabling consumers, retailers, and policy makers to make informed decisions on the environmental impacts of food products.
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Nutri-Score and NutrInform Battery: Effects on Performance and Preference in Italian Consumers
Fialon, M.; Serafini, M.; Galan, P.; Kesse-Guyot, E.; Touvier, M.; Deschasaux-Tanguy, M.; Sarda, B.; Hercberg, S.; Nabec, L.; Julia, C.
Nutrients 2022, 14, 3511.
https://doi.org/10.3390/nu14173511
https://www.mdpi.com/2072-6643/14/17/3511
Abstract
In May 2020, the European Commission announced a proposal for a mandatory front-of-pack label (FoPL) for all European Union (EU) countries. Indeed, FoPLs have been recognized by several public institutions as a cost-effective measure to guide consumers toward nutritionally favorable food products. The aim of this study was to compare the performance and consumer preference of two FoPLs currently proposed or implemented in EU countries, the interpretive format Nutri-Score and the non-interpretive format NutrInform Battery, among Italian consumers. The experimental study was conducted in 2021 on a representative sample of 1064 Italian adults (mean age = 46.5 ± 14.1 years; 48% men). Participants were randomized to either Nutri-Score or NutrInform and had to fill out an online questionnaire testing their objective understanding of the FoPL on three food categories (breakfast products, breakfast cereals and added fats) as well as purchase intention, subjective understanding and perception. Multivariable logistic regressions and t-tests were used to analyze the answers. In terms of the capacity of participants to identify the most nutritionally favorable products, Nutri-Score outperformed NutrInform in all food categories, with the highest odds ratio being observed for added fats (OR = 21.7 [15.3–31.1], p < 0.0001). Overall, with Nutri-Score, Italian participants were more likely to intend to purchase nutritionally favorable products than with NutrInform (OR = 5.29 [4.02–6.97], p < 0.0001). Focusing on olive oil, participants of the Nutri-Score group had higher purchase intention of olive oil compared to those in the NutrInform group (OR = 1.92 [1.42–2.60], p < 0.0001) after manipulating the label. The interpretive format Nutri-Score appears to be a more efficient tool than NutrInform for orienting Italian consumers towards more nutritionally favorable food choices.
NUTRI-SCORE 