Abstract:In response to the inclusion in the French Act on the modernization of the health system of a principle of a simplified nutrition labelling system, two nutrient profiling systems have been developed to classify foods according to their nutritional composition: the 5-colour labelling system (5-C), recently adopted by the French Ministry of Health and the French Simplified Nutritional Labelling System (SENS), adapted from the SAIN,LIM, developed by the ANSES. The aim of this study was to compare rankings yielded… Show more
“…Furthermore, total Nutri-Score was highly correlated with LIM (r s = 0.69, p < 0.001) and less correlated with SAIN (r s = −0.58, p < 0.001). These figures corroborate the results (κ = 0.45, r s = 0.78 for LIM and r s = −0.42 for SAIN) obtained in a previous study comparing SAIN,LIM and 5-C (former name of the Nutri-Score, of which the algorithm has since been slightly modified) nutrient profiling systems [ 51 ]. The SAIN,LIM system can be represented graphically (LIM on the x -axis and SAIN on the y -axis), thus allowing the display of the nutritional positions of the products: Figure A1 Projection of non-vegetarian and vegetarian main dishes ( n = 984) on the SAIN,LIM plane, represented with the colours of their class according to the Nutri-Score.…”
Section: Table A1supporting
confidence: 89%
“…Furthermore, total Nutri-Score was highly correlated with LIM (r s = 0.69, p < 0.001) and less correlated with SAIN (r s = −0.58, p < 0.001). These figures corroborate the results (κ = 0.45, r s = 0.78 for LIM and r s = −0.42 for SAIN) obtained in a previous study comparing SAIN,LIM and 5-C (former name of the Nutri-Score, of which the algorithm has since been slightly modified) nutrient profiling systems [ 51 ].…”
In France, school canteens must offer a vegetarian meal at least once per week. The objective was to evaluate the nutritional quality of school main dishes. A database of main dishes served in primary schools was first split into non-vegetarian (n = 669) and vegetarian (n = 315) categories. The latter has been divided into three sub-categories: vegetarian dishes containing cheese, vegetarian dishes containing eggs and/or dairy products but no cheese and vegetarian dishes without any eggs, cheese or other dairy products (vegan). Categories and sub-categories were compared based on nutrient adequacy ratios for “protective” nutrients (proteins, fibres, vitamins, minerals, essential fatty acids), the contents of nutrients to be limited (saturated fatty acids (SFA), sodium, free sugars) and on two nutrient profiling systems (SAIN,LIM and Nutri-Score). The vegetarian category and the non-vegetarian category displayed “adequate” levels (≥5% adequacy for 100 kcal) on average for almost all “protective” nutrients. The three sub-categories of vegetarian dishes displayed good SAIN,LIM and Nutri-Score profiles on average, although key nutrients were lacking (vitamin B12, vitamin D and DHA) or were present in insufficient amounts (vitamin B2 and calcium) in the vegan sub-category. The sub-category containing eggs and/or dairy products other than cheese was a good compromise, as it provided protective nutrients associated with eggs and fresh dairy products, while the sub-category containing cheese provided higher levels of SFA. Nutrient profile algorithms are insufficiently informative to assess the nutritional quality of school dishes.
“…Furthermore, total Nutri-Score was highly correlated with LIM (r s = 0.69, p < 0.001) and less correlated with SAIN (r s = −0.58, p < 0.001). These figures corroborate the results (κ = 0.45, r s = 0.78 for LIM and r s = −0.42 for SAIN) obtained in a previous study comparing SAIN,LIM and 5-C (former name of the Nutri-Score, of which the algorithm has since been slightly modified) nutrient profiling systems [ 51 ]. The SAIN,LIM system can be represented graphically (LIM on the x -axis and SAIN on the y -axis), thus allowing the display of the nutritional positions of the products: Figure A1 Projection of non-vegetarian and vegetarian main dishes ( n = 984) on the SAIN,LIM plane, represented with the colours of their class according to the Nutri-Score.…”
Section: Table A1supporting
confidence: 89%
“…Furthermore, total Nutri-Score was highly correlated with LIM (r s = 0.69, p < 0.001) and less correlated with SAIN (r s = −0.58, p < 0.001). These figures corroborate the results (κ = 0.45, r s = 0.78 for LIM and r s = −0.42 for SAIN) obtained in a previous study comparing SAIN,LIM and 5-C (former name of the Nutri-Score, of which the algorithm has since been slightly modified) nutrient profiling systems [ 51 ].…”
In France, school canteens must offer a vegetarian meal at least once per week. The objective was to evaluate the nutritional quality of school main dishes. A database of main dishes served in primary schools was first split into non-vegetarian (n = 669) and vegetarian (n = 315) categories. The latter has been divided into three sub-categories: vegetarian dishes containing cheese, vegetarian dishes containing eggs and/or dairy products but no cheese and vegetarian dishes without any eggs, cheese or other dairy products (vegan). Categories and sub-categories were compared based on nutrient adequacy ratios for “protective” nutrients (proteins, fibres, vitamins, minerals, essential fatty acids), the contents of nutrients to be limited (saturated fatty acids (SFA), sodium, free sugars) and on two nutrient profiling systems (SAIN,LIM and Nutri-Score). The vegetarian category and the non-vegetarian category displayed “adequate” levels (≥5% adequacy for 100 kcal) on average for almost all “protective” nutrients. The three sub-categories of vegetarian dishes displayed good SAIN,LIM and Nutri-Score profiles on average, although key nutrients were lacking (vitamin B12, vitamin D and DHA) or were present in insufficient amounts (vitamin B2 and calcium) in the vegan sub-category. The sub-category containing eggs and/or dairy products other than cheese was a good compromise, as it provided protective nutrients associated with eggs and fresh dairy products, while the sub-category containing cheese provided higher levels of SFA. Nutrient profile algorithms are insufficiently informative to assess the nutritional quality of school dishes.
“…One challenge of nutrient profiling is to adequately weight the respective contributions of positive and negative components. Some existing systems appear to be mainly driven by energy density and nutrients ( 33 , 34 ). In this study, we tested four alternative weighting models for the BQS.…”
BackgroundNutrient profiling methods can be applied to individual foods or to composite meals. This article introduces a new method to assess the nutrient density of breakfast meals.ObjectiveThis study aimed to develop a new breakfast quality score (BQS), based on the nutrient standards previously published by the International Breakfast Research Initiative (IBRI) consortium.MethodsBQS was composed of three sub-scores derived from the weighted arithmetic mean of corresponding nutrient adequacy: an eLIMf sub-score (energy, saturated fat, free sugars, and sodium), a PF (protein and fiber) sub-score, and a VMn1 − 14 micronutrient sub-score, where n varied from 0 to 14. The effects of assigning different weights to the eLIMf, PF, and VMn were explored in four alternative models. The micronutrients were calcium, iron, potassium, magnesium, zinc, vitamin A, thiamin, riboflavin, niacin, vitamin B5, vitamin B6, vitamin B12, vitamin C, and vitamin D. Micronutrient permutations were used to develop alternate VMn1 − 14 sub-scores. The breakfast database used in this study came from all breakfasts declared as consumed by adults (>18 years old) in the French dietary survey INCA3. All models were tested with respect to the Nutrient Rich Food Index (NRF9.3). BQS sensitivity was tested using three prototype French breakfasts, for which improvements were made.ResultsThe correlations of the models with NRF9.3 improved when the VMn>3 sub-score (n > 3) was included alongside the PF and eLIMf sub-scores. The model with (PF+VMn) and eLIMf each accounting for 50% of the total score showed the highest correlations with NRF9.3 and was the preferred final score (i.e., BQS). BQS was sensitive to the changing quality of three prototype breakfasts defined as tartine, sandwich, and cereal.ConclusionThe proposed BQS was shown to valuably rank the nutritional density of breakfast meals against a set of nutrient recommendations. It includes nutrients to limit along with protein, fiber, and a variable number of micronutrients to encourage. The flexible VMn sub-score allows for the evaluation of breakfast quality even when nutrient composition data are limited.
ÖZGıdaların içerdiği besin öğelerinin beslenme açısından önemi ve sağlık üzerine olumlu/olumsuz etkileri çeşitli yöntemlerle değerlendirilmektedir. Literatürde gıdaların ve diyetin genel olarak besleyici özelliğinin değerlendirildiği indeksler oldukça yaygın olarak kullanılmaktadır. Gıdaların besin öğesi içeriklerine göre sıralanması ve/veya sınıflandırılması ile besin öğesi profilinin oluşturulması ve gıdaların besleyicilik özelliklerinin ölçülmesinde kullanılması gün geçtikçe önem kazanmaktadır. Gıdaların besleyicilik özelliğinin içerdikleri yağ asitleri, protein veya karbonhidrat vb. besin öğelerinden herhangi biri açısından değerlendirilmesi bütünsel bir yaklaşım sağlamamaktadır. Bu derlemede, bu bütünsel yaklaşımı sağlayacak nitelikte, gıdaların makro ve mikro besin öğeleri ile besleyicilik özelliklerinin değerlendirildiği, literatürde indeks veya puan olarak tanımlanmış ve kullanılmakta olan geçerli yöntemler incelenmiştir. Anahtar kelimeler: Besleyicilik kalite indeksi, besin öğesi profili, besleyici gıda
INDEXES EVALUATE THE NUTRITIONAL PROPERTIES OF FOODS ABSTRACTThe nutritional importance of the nutrients contained in foods and their positive/negative effects on health are evaluated by various methods. In the literature, indexes that evaluate the nutritional properties of foods and diet in general are widely used. Sorting and/or classifying foods according to their nutrient content, forming a nutrient profile and measuring the nutritional properties of foods are gaining importance day by day. Evaluating the nutritional properties of foods in terms of either fatty acids, protein or carbohydrates does not provide a holistic approach. In this review, in order to provide this holistic approach, methods that evaluate the nutritional properties of foods by macro and micro nutrients, defined as index or score in the literature, are examined.
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