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Am J Clin Nutr. 2009 Apr;89(4):1227-36. doi: 10.3945/ajcn.2008.26465. Epub 2009 Feb 11.

Nutrient profiles discriminate between foods according to their contribution to nutritionally adequate diets: a validation study using linear programming and the SAIN,LIM system.

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1
INRA, UMR1260, Nutriments Lipidiques et Prévention des Maladies Métaboliques, Marseille, France. nicole.darmon@univmed.fr

Abstract

BACKGROUND:

The nutrient profile concept implies that it is possible to discriminate between foods according to their contribution to a healthy diet on the basis of their nutrient contents only.

OBJECTIVE:

The objective was to test the compatibility between nutrient profiling and nutrient-based recommendations by using diet modeling with linear programming.

DESIGN:

Food consumption data from the French "Individuelle et Nationale sur les Consommations Alimentaires" dietary survey and its associated food-composition database were used as input data. Each food was allocated to 1 of 4 classes, according to the SAIN,LIM system -- a nutrient profiling system based on 2 independent scores, including a total of 8 basic plus 4 optional nutrients. The possibility to model diets fulfilling a set of 40 nutrient recommendations (healthy models) was tested by using foods from a given nutrient profile class only or from a combination of classes. The possibility to fulfill a set of nutrient constraints in contradiction with the recommendations (unhealthy models) was also tested. For each model, the feasible energy range was assessed by minimizing and maximizing total energy content.

RESULTS:

With foods from the most favorable nutrient profile class, healthy diets could be modeled, but it was impossible to design unhealthy diets within a realistic range of energy intake with these foods. With foods from the least favorable class, unhealthy, but not healthy, diets could be designed. Both healthy and unhealthy diets could be designed with foods from intermediate classes.

CONCLUSION:

On the basis of a few key nutrients, it is possible to predict the ability of a given food to facilitate -- or to impair -- the fulfillment of a large number of nutrient recommendations.

PMID:
19211815
DOI:
10.3945/ajcn.2008.26465
[Indexed for MEDLINE]
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