Evaluation of Nutri-Score in Relation to Dietary Guidelines and Food Reformulation in The Netherlands

Borg, Sovianne ter; Steenbergen, Elly; Milder, Ivon E J; Temme, Elisabeth H. M.

doi:10.3390/nu13124536

Cited by 27 publications

(41 citation statements)

References 12 publications

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“…The national FBDGs provide food-based guidance on the basis of "foods to avoid, " "foods to consume in moderation" and "foods to promote." For the purpose of this analysis it was assumed that Nutri-Score grades (A) or (B) represented "foods to promote, " grade (C) represented "foods to consume in moderation, " and grades (D) and (E) represented "foods to avoid, " following previously published methodology (22).…”

Section: Evaluation Of Alignment With the National Food-based Dietary...mentioning

confidence: 99%

Performance and discriminatory capacity of Nutri-Score in branded foods in Greece

2022

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BackgroundThe harmonization of front-of-pack nutritional declaration is in the heart of food and nutrition policy discussions in Europe. The Nutri-Score system has been proposed by many countries as a potential candidate but its suitability for use across Europe is still under consideration. The current study aimed to evaluate the performance and discriminatory capacity of Nutri-Score in Greece and to test its alignment with the national food-based dietary guidelines.Materials and methodsData on the energy, saturated fat, total sugars, sodium, protein, and fiber content per 100°g or ml were extracted for all foods available (n = 4,002) in the Greek branded food composition database HelTH. Each food content in fruits, vegetables, pulses, nuts and oils was manually estimated from the ingredients list. The Nutri-Score algorithm was used both as a continuous (FSAm-NPS Score) and a categorical variable [Grades (A)–(E)].ResultsThe average FSAm-NPS Score in Greece was 8.52 ± 9.4. More than half of the solid foods (53.8%) were graded from (A) to (C), while most beverages (59.2%) were graded (E). More than 50% of food categories were populated with foods in all Nutri-Score grades, indicative of a good discriminatory capacity. The system scores favorably vegetables, pulses, and low-fat dairy products and unfavourablly sweets and processed meats showing in this way good alignment with the national guidelines. Eggs and seafood scored preferably compared to meat products. Animal fats received less favorable scores and so did cereal products that were highly processed.DiscussionNutri-Score showed good capacity to inform consumers toward better food choices in line with the national guidelines. It showed a potential to guide consumers and manufacturers toward less energy dense and more nutrient dense options and highlighted areas of improvement in the food supply.

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Section: Evaluation Of Alignment With the National Food-based Dietary...mentioning

confidence: 99%

Performance and discriminatory capacity of Nutri-Score in branded foods in Greece

2022

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“…Such foods have been variously described as healthful, wholesome, nutrient-dense, or nutrient-rich ( 3 , 4 , 7 , 9 ). Foods that are awarded A or B grades (Nutri-Score) or 4 or 5 stars (HSR) are generally viewed as conforming with dietary guidelines ( 29 ).…”

Section: Discussionmentioning

confidence: 99%

Balanced Hybrid Nutrient Density Score Compared to Nutri-Score and Health Star Rating Using Receiver Operating Characteristic Curve Analyses

2022

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BackgroundNutrient profiling (NP) models that are used to assess the nutrient density of foods can be based on a combination of key nutrients and desirable food groups.ObjectiveTo compare the diagnostic accuracy of a new balanced hybrid nutrient density score (bHNDS) to Nutri-Score and Health Star Rating (HSR) front-of-pack systems using receiver operating characteristic (ROC) curve analyses. The diet-level bHNDS was first validated against Healthy Eating Index (HEI-2015) using data from the 2017–18 National Health and Nutrition Examination Survey (2017–18 NHANES). Food-level bHNDS values were then compared to both the Nutri-Score and HSR using ROC curve analyses.ResultsThe bHNDS was based on 6 nutrients to encourage (protein, fiber, calcium, iron, potassium, and vitamin D); 5 food groups to encourage (whole grains, nuts and seeds, dairy, vegetables, and fruit), and 3 nutrients (saturated fat, added sugar, and sodium) to limit. The algorithm balanced components to encourage against those to limit. Diet-level bHNDS values correlated well with HEI-2015 (r = 0.67; p < 0.001). Food-level correlations with both Nutri-Score (r = 0.60) and with HSR (r = 0.58) were significant (both p < 0.001). ROC estimates of the Area Under the Curve (AUC) showed high agreement between bHNDS values and optimal Nutri-Score and HSR ratings (>0.90 in most cases). ROC analysis identified those bHNDS cut-off points that were predictive of A-grade Nutri-Score or 5-star HSR. Those cut-off points were highly category-specific.ConclusionThe new bHNDS model showed high agreement with two front-of-pack labeling systems. Cross-model comparisons based on ROC curve analyses are the first step toward harmonization of proliferating NP methods that aim to “diagnose” high nutrient-density foods.

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“…While the WHO recommends adapting FOP labeling to national dietary guidelines (12) such adaptation was done only for France and not for the other countries so far. For instance, research from the Netherlands showed that the Nutri-Score is in line with the Dutch dietary guidelines recommending increased consumption of fruit and vegetable, pulses, and unsalted nuts (70), but there are also discrepancies (45,46). Outside Europe, discrepancies with dietary guidelines were also reported on a FOP label based on the same algorithm (58-61).…”

Section: Implications For European Implementation Of Nutri-scorementioning

confidence: 97%

“…To date, it is unknown whether adapting the across-the-board criteria of Nutri-Score will support product reformulation for different food groups or whether food group-specific criteria are required. A Dutch analysis investigated to what extent different product improvement scenarios can initiate a shift in Nutri-Score and hence can be an incentive for reformulation ( 70 ). It was found that a reduction in sodium, saturated fat or sugars result in a more favorable Nutri-Score in a large variety of food groups.…”

Section: Implications For European Implementation Of Nutri-scorementioning

confidence: 99%

“…However, as noted previously, the Nutri-Score's algorithm is based on a balance between “positive” and “negative” nutrients that may compensate for each other. For example, dairy drinks with added sugar that are low in saturated fat and salt may benefit from their naturally high protein content as this compensates for the sugar content, leading to a more favorable Nutri-Score ( 70 ). Also, adding extra protein to these beverages may make it seem they are reformulated, while their sugar content has not changed.…”

Section: Implications For European Implementation Of Nutri-scorementioning

confidence: 99%

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The Nutri-Score algorithm: Evaluation of its validation process

Bend

Eijsden²,

Roost³

et al. 2022

Front. Nutr.

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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.

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Evaluation of Nutri-Score in Relation to Dietary Guidelines and Food Reformulation in The Netherlands

Cited by 27 publications

References 12 publications

Performance and discriminatory capacity of Nutri-Score in branded foods in Greece

Performance and discriminatory capacity of Nutri-Score in branded foods in Greece

Balanced Hybrid Nutrient Density Score Compared to Nutri-Score and Health Star Rating Using Receiver Operating Characteristic Curve Analyses

The Nutri-Score algorithm: Evaluation of its validation process

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