The SENS algorithm—a new nutrient profiling system for food labelling in Europe

International audienceBackground/objectives In response to the European regulation on nutrition and health claims, France proposed in 2008 the SAIN,LIM profiling system that classifies foods into four classes based on a nutrient density score called ‘SAIN’, a score of nutrients to limit called ‘LIM’, and one primary threshold on each score. We present here the SENS algorithm, a new nutrient profiling system adapted from the SAIN,LIM to be operational for simplified nutrition labelling in line with the European regulation on food information to consumers. Subjects/methods The main changes made to SAIN,LIM to get SENS were to introduce food categories and sub-categories (‘Beverages’, ‘Added Fats’ and ‘Other Solid Foods’ sub-categorised into ‘cereals’, ‘cheese’, ‘other dairy products’, ‘eggs’, ‘fish’ and ‘others’), reduce the number of nutrients, introduce category-specific nutrients and category-specific weighting for some nutrients, replace French recommendations with European reference intakes, and add secondary thresholds. Each food and non-alcoholic beverage from the 2013-CIQUAL French composition database (n = 1065) was assigned one SENS class. Distribution of foods according to the four SENS classes was described by food groups (n = 26). Results The SENS classification was consistent with the recommendations to consume large amounts of whole grains, vegetables and fruits, and moderate intake of fats, sugars, meats, caloric beverages and salt. For most groups (19/26), foods were distributed across at least three SENS classes. Conclusions The SENS is a nutrition-sensitive system that discriminates foods between and within food categories. It preserves the strengths of the initial SAIN,LIM while making it operational for simplified nutrition labelling in Europe

Testing the nutritional relevance of food- based dietary guidelines with mathematical optimisation of individual diets

Mathematical optimisation of diets is generally used to translate nutrient-based recommendations into healthy food choices but can also be used to assess the possible impact of food-based dietary guidelines (FBDG) on nutrient intakes. Optimisation of individual diets, which allows individual variability of food consumption to be taken into account, generates more robust results and more realistic diets than population diet optimisation. It was used to simulate the impact on nutrient intakes of complying with the new French FBDGs. For each observed diet of adults in the French INCA2 survey, a new isoenergetic diet was designed to meet all food consumption frequencies recommended by the new French FBDGs, as interpreted by the constraints included in a model called DP2. Because the dairy food group is the only one whose guideline has been reduced (from 3 to 2 portions/day) compared to the previous FBDGs, an alternative model, called DP3, imposing 3 daily portions of dairy products instead of 2 was also tested. Diets optimised with the DP2 model had lower energy density and higher nutrient density than the observed diets, and inadequate intakes decreased for most vitamins and minerals. With the alternative DP3 model, the decrease in saturates was less pronounced than with 2 portions/day of dairy products (13.8%, 11.9% and 12.8% energy in observed diets and in DP2 and DP3, respectively), but calcium adequacy was improved instead of being worsened (51%, 58% and 16% of inadequacy in observed diets and in diets modelled with 2 portions/day and 3 portions/day of dairy products, respectively). Individual diet optimisation is a powerful tool for assessing the nutritional relevance of existing FBDGs and to test possible alternatives