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

Abstract

Background/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.

Fig. 1

The third step for classifying a food with SENS: allocating foods to one of the four SENS classes according to the thresholds applied to the scores (two exceptions to the general ranking were introduced. First, non-water beverages that the algorithm had allocated to Class 1 were systematically downgraded to Class 2. Second, in the ‘Other solid foods’ category, foods exceeding 400 kcal/100 g allocated to Class 1 were systematically downgraded to Class 2, or from Class 2 to Class 3, and foods with an ED > 500 kcal/100 g and a sodium (Na) content > 200 mg/100 g allocated to Class 3 were downgraded to Class 4)

Fig. 2

Distribution (Boxplot represents first quartile; median, and third quartile; Diamonds represent the averages) of energy density (kcal/100 g, a (median values are 71, 123, 250 and 355  kcal/100 g for Class 1, Class 2, Class 3 and Class 4, respectively)) and of nutrient density score (the nutrient density score was calculated as previously described [27]) (%/100 kcal, b (median values are 12.4, 5.9, 4.4 and 2.7 %/100 kcal for Class 1, Class 2, Class 3 and Class 4, respectively)) of CIQUAL foods (water excluded) by SENS class