This study aimed to examine the association between drinking water intake and diet quality, and to analyse the adherence of French men and women to the European Food Safety Authority 2010 Adequate Intake (EFSA AI). A representative sample of French adults (≥18) from the Individual and National Survey on Food Consumption (INCA2) was classified, by sex, into small, medium, and large drinking water consumers. Diet quality was assessed with several nutritional indices (mean adequacy ratio (MAR), mean excess ratio (MER), probability of adequate intakes (PANDiet), and solid energy density (SED)). Of the total sample, 72% of men and 46% of women were below the EFSA AI. This percentage of non-adherence decreased from the small to the large drinking water consumers (from 95% to 34% in men and from 81% to 9% in women). For both sexes, drinking water intake was associated with higher diet quality (greater MAR and PANDiet). This association remained significant independently of socio-economic status for women only. Low drinking water consumers did not compensate with other sources (beverages and food moisture) and a high drinking water intake was not a guarantee for reaching the EFSA AI, meaning that increasing consumption of water should be encouraged in France.

Background/objectivesIn 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/methodsThe 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).ResultsThe 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.ConclusionsThe 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.

Background/objectivesWe aimed to validate the simplified nutrient profiling system (SENS) algorithm based on its ability to rank foods across the four SENS classes in relation to overall nutritional quality of both observed diets and nutritionally optimized diets.Subjects/methodsFoods and beverages from the French nutritional composition database were classified according to SENS. Diets consumed by French adults in the latest national dietary survey (>19 years, n = 1719) were divided into four nutritional quality levels, and average daily frequencies (number of portions per day) of foods from the four SENS classes were compared between the four levels. Then, for each individual observed diet, one iso-caloric and nutritionally adequate diet was optimized, and variations in daily frequencies of foods from each SENS class between observed and optimized diets were estimated.ResultsIn observed diets, as overall nutritional quality level of diet increased, daily frequency increased for Class-1 foods (3.5 to 8.7 portions/d) and decreased for Class-4 foods (6.8 to 3.0 portions/day). From observed to optimized diets, daily frequency increased for Class-1 foods for 98.4% of individuals and decreased for Class-4 foods for 94.2% of individuals. Class-2 and Class-3 foods also followed patterns that fit the expected ranking.ConclusionsResults from two WHO-recommended validation approaches showed that the SENS algorithm adequately ranks foods according to their contribution to overall nutritional quality of diets, which is a pre-requisite to use for simplified nutritional labeling in Europe.