Prospective associations of the original Food Standards Agency nutrient profiling system and three variants with weight gain, overweight and obesity risk: results from the French NutriNet-Santé cohort

Complementarity between the updated version of the front-of-pack nutrition label Nutri-Score and the food-processing NOVA classification

OBJECTIVE

To compare the initial and the updated versions of the front-of-pack label Nutri-Score (related to the nutritional content) with the NOVA classification (related to the degree of food processing) at the food level.

DESIGN

Using the OpenFoodFacts database - 129,950 food products - we assessed the complementarity between the Nutri-Score (initial and updated) with the NOVA classification through a correspondence analysis. Contingency tables between the two classification systems were used.

SETTINGS

The food offer in France.

PARTICIPANTS

Not applicable.

RESULTS

With both versions (i.e. initial and updated) of the Nutri-Score, the majority of ultra-processed products received medium to poor Nutri-Score ratings (between 77·9 % and 87·5 % of ultra-processed products depending on the version of the algorithm). Overall, the update of the Nutri-Score algorithm led to a reduction in the number of products rated A and B and an increase in the number of products rated D or E for all NOVA categories, with unprocessed foods being the least impacted (-3·8 percentage points (-5·2 %) rated A or B and +1·3 percentage points (+12·9 %) rated D or E) and ultra-processed foods the most impacted (-9·8 percentage points (-43·4 %) rated A or B and +7·8 percentage points (+14·1 %) rated D or E). Among ultra-processed foods rated favourably with the initial Nutri-Score, artificially sweetened beverages, sweetened plant-based drinks and bread products were the most penalised categories by the revision of Nutri-Score while low-sugar flavoured waters, fruit and legume preparations were the least affected.

CONCLUSION

These results indicate that the update of the Nutri-Score reinforces its coherence with the NOVA classification, even though both systems measure two distinct health dimensions at the food level.

Criterion validation of nutrient profiling systems: a systematic review and meta-analysis

BACKGROUND

Nutrient profiling systems (NPSs) use algorithms to evaluate the nutritional quality of foods and beverages. Criterion validation, which assesses the relationship between consuming foods rated as healthier by the NPS and objective measures of health, is essential to ensure the accuracy of NPSs.

OBJECTIVE

We examined and compared NPSs that have undergone criterion validity testing in relation to diet-related disease risk and risk markers.

METHODS

Academic databases were searched for prospective cohort and cross-sectional studies published before November, 2022. NPSs were eligible if they incorporated multiple nutrients or food components using an algorithm to determine an overall summary indicator (e.g., a score or rank) for individual foods. Studies were included if they assessed the criterion validity of an eligible NPS. Validation evidence was first summarized in narrative form by NPS, with random effects meta-analysis where ≥2 prospective cohort studies assessed the same NPS and outcomes.

RESULTS

Of 4519 publications identified, 29 describing 9 NPSs were included in the review. The Nutri-Score NPS was assessed as having substantial criterion validation evidence. Highest compared with lowest diet quality as defined by the Nutri-Score was associated with significantly lower risk of cardiovascular disease (hazard ratio [HR]: 0.74; 95% confidence interval [CI]: 0.59, 0.93; n = 6), cancer (HR: 0.75; 95% CI: 0.59, 0.94; n = 5), all-cause mortality (HR: 0.74; 95% CI; 0.59, 0.91; n = 4) and change in body mass index (HR: 0.68; 95% CI: 0.50, 0.92; n = 3). The Food Standards Agency NPS, Health Star Rating, Nutrient Profiling Scoring Criterion, Food Compass, Overall Nutrition Quality Index, and the Nutrient-Rich Food Index were determined as having intermediate criterion validation evidence. Two other NPSs were determined as having limited criterion validation evidence.

CONCLUSIONS

We found limited criterion validation studies compared with the number of NPSs estimated to exist. Greater emphasis on conducting and reporting on criterion validation studies across varied contexts may improve the confidence in existing NPSs.

Comparing product healthiness according to the Health Star Rating and the NOVA classification system and implications for food labelling systems: An analysis of 25 486 products in Australia

We investigated the extent of alignment between 'healthiness' defined by a food classification system that classifies foods and beverages primarily by their nutrient composition, the Health Star Rating (HSR) and a system that considers only the degree of processing of the product, the NOVA classification system. We used data for 25 486 products contained within the George Institute for Global Health's Australian 2022 FoodSwitch Dataset. Agreement between the two systems in the proportion of products classified as 'healthier' (HSR ≥3.5 or NOVA group 1-3) or 'less healthy' (HSR <3.5 or NOVA group 4) was assessed using the κ statistic. There was 'fair' agreement (κ = 0.30, 95%CI: 0.29-0.31) between both systems in the proportion of all products classified as healthier or less healthy. Approximately one-third (n = 8729) of all products were defined as 'discordant', including 34.3% (n = 5620) of NOVA group 4 products with HSR ≥3.5 (commonly convenience foods, sports/diet foods, meat alternatives, as well as products containing non-sugar sweeteners) and 34.1% (n = 3109) of NOVA group 1-3 products with HSR <3.5 (commonly single-ingredient foods such as sugars/syrups, full-fat dairy and products specially produced to contain no ultra-processed ingredients). Our analysis strengthens the evidence for the similarities and differences in product healthiness according to a nutrient-based classification system and a processing-based classification system. Although the systems' classifications align for the majority of food and beverage products, the discordance found for some product categories indicates potential for confusion if systems are deployed alongside each other within food policies.

Living with obesity in Ireland: determinants, policy and future perspectives

Globally, the prevalence of those living with obesity (≥30 kg/m2) is rising, with this trend expected to continue if firm and decisive policy interventions are not introduced. Across Europe, despite many consecutive policies aiming to reverse rising trends in weight status over recent decades, no country is currently on track to halt and reverse current trends in the coming years. This is evident in Ireland too, whereby the reporting of nationally representative weight status data show that targets have not been achieved since reporting began. The aim of this review is to critically appraise recent evidence relating to the key determinants of obesity including weight status, diet quality and physical activity with an emphasis on socioeconomic inequalities. And to consider these in the context of respective policy measures and propose future-focused recommendations. Furthermore, as with the complex nature of obesity, multifaceted approaches that shift the focus from the individual and place responsibility at a societal level will be reviewed.

Food Compass Score and its association with inflammatory markers and homocysteine in cardiovascular disease-free adults: a cross-sectional analysis of the ATTICA epidemiological study

BACKGROUND/OBJECTIVES

Several nutrient profiling systems have been developed to assist in food choices and policy. Food Compass Score (FCS) is a novel holistic food score assessing 54 parameters. The aim was to assess the relation of FCS with inflammatory and lipid markers in cardiovascular disease-free volunteers.

SUBJECTS/METHODS

Information from the ATTICA epidemiological study participants, with complete data on lipid, inflammatory markers and dietary intake were studied (n = 1018). C-reactive protein (CRP) and amyloid A were determined by immunonephelometry, fibrinogen by nephelometry, homocysteine by fluorometry, while tumor necrosis factor-a (TNF-a), interleukin-6 (IL-6), adiponectin and leptin were determined by ELISA in fasting blood samples. Dietary intake was assessed through a semi-quantitative validated food frequency questionnaire. Each food was assigned a FCS value from the published values and then individual's FCS values were calculated.

RESULTS

Mean FCS was 56 (standard deviation: 5.7) and it was similar in men and women. FCS was inversely correlated with age (r = -0.06, p = 0.03). In multiple linear regression models, FCS was inversely associated with CRP (-0.03, 0.01), TNF-a (-0.04, 0.01), amyloid A (-0.10, 0.04) and homocysteine (-0.09, 0.04) (b coefficients, standard errors, all p < 0.05) and was not associated with IL-6, fibrinogen, adiponectin, leptin, or lipids levels (all p > 0.05).

CONCLUSIONS

The inverse correlations of the FCS with inflammatory markers suggest that a diet containing foods with high FCS might be protective against inflammation process. Our results support the usefulness of the FCS, but future studies should evaluate its relation to cardiovascular and other inflammation-related chronic diseases.

Nutri-Score: Its Benefits and Limitations in Children's Feeding

Reducing the burden of noncommunicable diseases (NCDs) is one of the top priorities of public health policies worldwide. One of the recognized means of achieving this objective is to improve the diet quality. The Nutri-Score (N-S) is a [five-color-A, B, C, D, E letters] front-of-pack labeling logo intended to help consumers quickly identify the healthier prepackaged foods within a food category. Available studies have shown that the N-S is an efficient tool to achieve this aim in terms of consumers' awareness, perception, understanding, and purchasing and that its use may help to reduce the prevalence of NCDs. The N-S is currently implemented on a voluntary basis in 7 European countries and a discussion is underway within the European Commission to achieve a harmonized mandatory label. However, no study on the putative impact of the N-S on children's dietary patterns and health is available. The N-S is not applicable to infants' and young children's formulas and to specific baby foods, the compositions of which are already laid down in European Union regulations. The N-S does not replace age-appropriate dietary guidelines. As children consume an increasing number of adult type and processed foods, the relevance of the N-S for children should be evaluated considering the children's high specific requirements, especially in younger children. This is especially necessary for fitting fat and iron requirements, whereas protein-rich foods should be better framed. Moreover, efforts should be made to inform on how to use the N-S and in education on healthy diets.

Cross-sectional comparisons of dietary indexes underlying nutrition labels: nutri-score, Canadian 'high in' labels and Diabetes Canada Clinical Practices (DCCP)

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, p_trend = 0.001) and DCCP-DI was associated with BMI (Q1 = 24.8 kg/m² vs. Q5 = 25.8 kg/m², p_trend = 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.

Consumer Reactions to Positive and Negative Front-of-Package Food Labels

INTRODUCTION

The National Academy of Medicine recommends that the U.S. adopt an interpretative front-of-package food labeling system, but uncertainty remains about how this system should be designed. This study examined reactions to front-of-package food labeling systems that use positive labels to identify healthier foods, negative labels to identify unhealthier foods, or both.

METHODS

In August 2021, U.S. adults (N=3,051) completed an online randomized experiment. Participants were randomly assigned to 1 of 4 labeling conditions: control (calorie), positive, negative, or both positive and negative labels. Labels were adapted from designs for a 'healthy' label drafted by the Food and Drug Administration and displayed on the front of product packaging. Participants selected products to purchase, identified healthier products, and reported reactions to the labels. Analyses, conducted in 2022, examined the healthfulness of participants' selections using the Ofcom Nutrient Profiling Model score (0-100, higher scores indicate being healthier).

RESULTS

Participants exposed to only positive labels, only negative labels, or both positive and negative labels had healthier selections than participants in the control arm (differences vs control=1.13 [2%], 2.34 [4%] vs 3.19 [5%], respectively; all p<0.01). The both-positive-and-negative-labels arm outperformed the only-negative-labels (p=0.03) and only-positive-labels (p<0.001) arms. The only-negative-labels arm outperformed the only-positive-labels arm (p=0.005). All the 3 interpretative labeling systems also led to improvements in the identification of healthier products and beneficial psychological reactions (e.g., attention, thinking about health effects; all p<0.05).

CONCLUSIONS

Front-of-package food labeling systems that use both positive and negative labels could encourage healthier purchases and improve understanding more than systems using only positive or only negative labels.

Are Front-of-Pack Nutrition Labels Influencing Food Choices and Purchases, Diet Quality, and Modeled Health Outcomes? A Narrative Review of Four Systems

Front-of-Pack Nutrition labels (FOPNLs) aim to improve consumers' food purchases and prompt product reformulation by the food and beverage industry. Despite their widespread use, the effectiveness of FOPNL in achieving these goals is still a matter of debate. This review has gathered 65 original studies exploring the performances of four widely used FOPNLs (Multiple Traffic Light, Warning signs, Nutri-Score and Health Star Rating). Although FOPNLs have been associated with healthier food purchases, the magnitude of improvements was small and dependent on study settings. Any associated health effects were modeled rather than observed. None of the four FOPNLs clearly outperformed the other ones on any outcome. Few studies dealt with the impact of FOPNL on product reformulation. Some of those studies, but not all, found small reductions in energy, sodium, sugar and saturated fat content of foods in some food categories. Although global trends point to a small favorable effect of FOPNL, this conclusion is subject to caution since the evidence is inconsistent and comes from a wide variety of contexts and study designs. There remain numerous research gaps, notably with regard to the optimal characteristics of FOPNLs, the durability of FOPNL effects on consumer behaviors, and any possible unexpected consequences.

The Nutri-Score algorithm: Evaluation of its validation process

The Nutri-Score front-of-pack label, which classifies the nutritional quality of products in one of 5 classes (A to E), is one of the main candidates for standardized front-of-pack labeling in the EU. The algorithm underpinning the Nutri-Score label is derived from the Food Standard Agency (FSA) nutrient profile model, originally a binary model developed to regulate the marketing of foods to children in the UK. This review describes the development and validation process of the Nutri-Score algorithm. While the Nutri-Score label is one of the most studied front-of-pack labels in the EU, its validity and applicability in the European context is still undetermined. For several European countries, content validity (i.e., ability to rank foods according to healthfulness) has been evaluated. Studies showed Nutri-Score's ability to classify foods across the board of the total food supply, but did not show the actual healthfulness of products within different classes. Convergent validity (i.e., ability to categorize products in a similar way as other systems such as dietary guidelines) was assessed with the French dietary guidelines; further adaptations of the Nutri-Score algorithm seem needed to ensure alignment with food-based dietary guidelines across the EU. Predictive validity (i.e., ability to predict disease risk when applied to population dietary data) could be re-assessed after adaptations are made to the algorithm. Currently, seven countries have implemented or aim to implement Nutri-Score. These countries appointed an international scientific committee to evaluate Nutri-Score, its underlying algorithm and its applicability in a European context. With this review, we hope to contribute to the scientific and political discussions with respect to nutrition labeling in the EU.

A review of front-of-pack nutrition labelling in Southeast Asia: Industry interference, lessons learned, and future directions

Front-of-pack nutrition labelling is an evidence-based nutrition intervention that is recommended by the World Health Organization and other health agencies as an effective non-communicable disease prevention strategy. To date, the types of front-of-pack labels that have been identified as being most effective have yet to be implemented in Southeast Asia. This has been partly attributed to extensive industry interference in nutrition policy development and implementation. This paper outlines the current state of food labelling policy in the region, describes observed industry interference tactics, and provides recommendations for how governments in Southeast Asia can address this interference to deliver best-practice nutrition labelling to improve diets at the population level. The experiences of four focal countries - Malaysia, Thailand, the Philippines, and Viet Nam - are highlighted to provide insights into the range of industry tactics that are serving to prevent optimal food labelling policies from being developed and implemented.

Funding

This research was supported by the United Kingdom Global Better Health Programme, which is managed by the United Kingdom Foreign, Commonwealth and Development Office and supported by PricewaterhouseCoopers in Southeast Asia.

Associations Between the Modified Food Standard Agency Nutrient Profiling System Dietary Index and Cardiovascular Risk Factors in an Elderly Population

Background

Helping consumers to improve the nutritional quality of their diet is a key public health action to prevent cardiovascular diseases (CVDs). The modified version of the Food Standard Agency Nutrient Profiling System Dietary Index (FSAm-NPS DI) underpinning the Nutri-Score front-of-pack label has been used in public health strategies to address the deleterious consequences of poor diets. This study aimed to assess the association between the FSAm-NPS DI and some CVD risk factors including body mass index (BMI), waist circumference, plasma glucose levels, triglyceride levels, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, and diastolic and systolic blood pressure.

Materials and Methods

Dietary intake was assessed at baseline and after 1 year of follow-up using a 143-item validated semi-quantitative food-frequency questionnaire. Dietary indices based on FSAm-NPS applied at an individual level were computed to characterize the diet quality of 5,921 participants aged 55–75 years with overweight/obesity and metabolic syndrome from the PREDIMED-plus cohort. Associations between the FSAm-NPS DI and CVD risk factors were assessed using linear regression models.

Results

Compared to participants with a higher nutritional quality of diet (measured by a lower FSAm-NPS DI at baseline or a decrease in FSAm-NPS DI after 1 year), those participants with a lower nutritional quality of diet (higher FSAm-NPS DI or an increase in score) showed a significant increase in the levels of plasma glucose, triglycerides, diastolic blood pressure, BMI, and waist circumference (β coefficient [95% confidence interval]; P for trend) (1.67 [0.43, 2.90]; <0.001; 6.27 [2.46, 10.09]; <0.001; 0.56 [0.08, 1.05]; 0.001; 0.51 [0.41, 0.60]; <0.001; 1.19 [0.89, 1.50]; <0.001, respectively). No significant associations in relation to changes in HDL and LDL-cholesterol nor with systolic blood pressure were shown.

Conclusion

This prospective cohort study suggests that the consumption of food items with a higher FSAm-NPS DI is associated with increased levels of several major risk factors for CVD including adiposity, fasting plasma glucose, triglycerides, and diastolic blood pressure. However, results must be cautiously interpreted because no significant prospective associations were identified for critical CVD risk factors, such as HDL and LDL-cholesterol, and systolic blood pressure.

Clinical Application of the Food Compass Score: Positive Association to Mediterranean Diet Score, Health Star Rating System and an Early Eating Pattern in University Students

Nutrient profiling systems (NPS) assist consumers in food choices. Several scores based on NPS have been proposed, but data on their clinical application are lacking. The food compass score (FCS) is a newly developed NPS per 100 kcal (from 1 “least healthy” to 100 “most healthy”). We examined the correlations of FCS with other indices, food groups, and meal patterns. A total of 346 students of the University of the Peloponnese (269 women and 77 men) participated. Dietary habits were evaluated with a food frequency questionnaire, and FCS, health star rating score (HSR), and MedDietScore were computed. Meal and snack frequency consumption was reported. Principal component analysis revealed three meal patterns: “early eater” (breakfast, morning snack and afternoon snack), “medium eater” (lunch and dinner), and “late eater” (bedtime snack). Pearson partial correlations between ranked variables were used to test the correlation coefficients between FCS, other scores, and meal patterns, after adjustment for age, sex, BMI, and underreporting. FCS was positively correlated to HSR (rho = 0.761, p ≤ 0.001) in a multi-adjusted analysis. In the highest tertile of MedDietScore FCS was also positively correlated to MedDietScore (rho = 0.379, p < 0.001). The FCS was positively correlated with juices, high-fat dairy, vegetables, legumes, fruits, and olive oil and negatively correlated with sodas, alcoholic drinks, red meat, refined grains, sweets, fats other than olive oil, fast foods, and coffee. In addition, it related positively to the “early eater” pattern (rho = 0.207, p < 0.001). The FCS was associated with other quality indices and better nutritional habits, such as being an early eater.

Front-of-pack (FOP) labelling systems to improve the quality of nutrition information to prevent obesity: NutrInform Battery vs Nutri-Score

Many systems for classifying food products to adequately predict lower all-cause morbidity and mortality have been proposed as front-of-pack (FOP) nutritional labels. Although the efforts and advances that these systems represent for public health must be appreciated, as scientists involved in nutrition research and belonging to diverse Italian nutrition scientific societies, we would like to draw stakeholders' attention to the fact that some FOP labels risk being not correctly informative to consumers' awareness of nutritional food quality. The European Commission has explicitly called for such a nutrition information system to be part of the European "strategy on nutrition, overweight and obesity-related issues" to "facilitate consumer understanding of the contribution or importance of the food to the energy and nutrient content of a diet". Some European countries have adopted the popular French proposal Nutri-Score. However, many critical limits and inadequacies have been identified in this system. As an alternative, we endorse a new enriched informative label-the NutrInform Battery-promoted by the Italian Ministry of Health and deeply studied by the Center for Study and Research on Obesity, Milan University. Therefore, the present position paper limits comparing these two FOP nutritional labels, focusing on the evidence suggesting that the NutrInform Battery can help consumers better than the Nutri-Score system to understand nutritional information, potentially improving dietary choices. LEVEL OF EVIDENCE: II. Evidence was obtained from well-designed controlled trials without randomization.

Evaluating intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model

PURPOSE

To investigate intake levels of nutrients linked to non-communicable diseases in Australia using the novel combination of food processing and nutrient profiling metrics of the PAHO Nutrient Profile Model.

METHODS

Dietary intakes of 12,153 participants from the Australian Health Survey (2011-12) aged 2 + years were evaluated. Food items reported during a 24 h recall were classified using the NOVA system. The Pan-American Health Organization Nutrient Profile Model (PAHO NPM) was applied to identify processed and ultra-processed products with excessive content of critical nutrients. Differences in mean intakes and prevalence of excessive intakes of critical nutrients for groups of the population whose diets were made up of products with and without excessive content in critical nutrients were examined.

RESULTS

The majority of Australians consumed daily at least three processed and ultra-processed products identified as excessive in critical nutrients according to the PAHO NPM. Individuals consuming these products had higher intakes of free sugars (β = 8.9), total fats (β = 11.0), saturated fats (β = 4.6), trans fats (β = 0.2), and sodium (β = 1788 for adolescents and adults; β = 1769 for children 5-10 years; β = 1319 for children aged < 5 years) (p ≤ 0.001 for all nutrients) than individuals not consuming these foods. The prevalence of excessive intake of all critical nutrients also followed the same trend.

CONCLUSION

The PAHO NPM has shown to be a relevant tool to predict intake levels of nutrients linked to non-communicable diseases in Australia and, therefore, could be used to inform policy actions aimed at increasing the healthiness of food environments.

Do Overweight People Have Worse Cognitive Flexibility? Cues-Triggered Food Craving May Have a Greater Impact

Background: Overweight people have been revealed to have poor cognitive flexibility. Cognitive flexibility reflects proactive and reactive control abilities. However, the impairment had not been explicitly positioned at the cognitive stage. Therefore, this study provides increased support for impairment of cognitive flexibility due to overweight. Method: The study included 34 overweight and 35 normal-weight participants. They were required to complete the food and flower target AX-continuous performance test (AX–CPT), including the resting-state fMRI and cue-triggered food craving subscales. We compared the performance difference between the two tasks. Furthermore, we investigated whether the cue-triggered food cravings and the corresponding brain regions mediated the effect of overweight on the two control mechanisms. Result: Significant differences were found only in the food target AX-CPT task, where overweight participants performed worse. Cue-triggered food cravings mediated this relationship. Additionally, we found that the brain regions associated with cue-triggered food cravings (bilateral SFG) can completely mediate the relationship between BMI and the z-value of the fat mass index and sensitivity to proactive control. Conclusion: In the food target task, overweight participants performed worse in both control mechanisms. Moreover, we also revealed the potential mechanism by which being overweight might affect the two control mechanisms through cue-triggered food cravings.

Impact of the Front-of-Pack Label Nutri-Score on the Nutritional Quality of Food Choices in a Quasi-Experimental Trial in Catering

The front-of-pack labelling Nutri-Score has recently been implemented as a policy measure to improve the healthiness of food choices. The aim of this study was to investigate the impact of the Nutri-Score label in catering. A quasi-experimental trial was conducted in France between 16 December 2019 and 13 March 2020 in two staff restaurants (one intervention and one control site) from the same company. After a control period of seven weeks, the Nutri-Score label was affixed on all proposed products in the intervention site. Overall effects of the intervention were investigated using a difference in difference approach with generalised linear models. Over the 13 weeks of the study, 2063 participants who frequented the restaurant cafeteria at least once were included (1268 and 795 in the intervention and control site, respectively), representing 36,114 meals. Overall, the intervention led to a significant improvement in the nutritional quality of meals (p = 0.008) and a significant reduction in the intake of calories, sugars and saturated fat (p < 0.0001). Mixed effects models showed a qualitative improvement of food choices initially, and an adaptation of the quantities consumed over time, suggesting for the first time longer-term effects of the label on dietary behaviour.

The Nutri-Score nutrition label

Nutri-Score is a front-of-pack nutrition label with summary graded colour-coding, which aims to inform consumers, in a simple and understandable way, of the overall nutritional value of foods, in order to help them to make healthier choices at the point of purchase and to encourage manufacturers to improve the nutritional quality of their products. It is based on a five-colour scale (from dark green to dark orange) associated with letters, from A to E, to optimize logo accessibility and understanding by the consumer. Nutri-Score does not merely characterize foods as "healthy" or "unhealthy". Rather, the graded logo provides semi-quantitative information, depending on the colour/ letter, of the relative overall nutritional composition of a food product compared to other similar products as to whether it is more or less favourable to health. Nutri-Score is the only proposed labelling scheme that adheres entirely to the concepts and processes that were published by the World Health Organisation (WHO) Europe concerning the validation studies that are required to select and evaluate a front-of-pack nutrition label. The aim of the present paper is to present the scientific basis for the design of the Nutri-Score and to summarize the various studies to validate its calculation method and its graphic format. We explore its effectiveness and superiority compared to other labelling schemes that have been implemented in other countries or supported by pressure groups. The necessity for objective, impartial consideration of how best to use Nutri-Score and avoid misunderstandings is highlighted.