A Drewnowski1, M Maillot, N Darmon. 1. Center for Public Health Nutrition and the Nutritional Sciences Program, School of Public Health and Community Medicine, University of Washington, Seattle, WA 98195-3410, USA. adamdrew@u.washington.edu
Abstract
BACKGROUND: Nutrient profiling of foods is defined as the science of classifying foods based on their nutrient content. Food rankings generated by nutrient profile models need to be tested against objective reality as opposed to public opinion. OBJECTIVE: To test the performance of selected nutrient profile models in relation to the foods' energy density (kcal g(-1)) and energy cost (Dollar per 1000 kcal). SUBJECTS/ METHODS: Analyses were based on 378 component foods of a food frequency instrument. The models tested were the French nutrient adequacy models NAS23 and NAS16 and nutrient density models NDS23 and NDS16; and a family of nutrient-rich models (NR(n), where n=5-7; 10-12, and 15). Also tested were LIM scores and a modified British Food Standards Agency model WXYfm. Profiles were calculated based on 100 g, 100 kcal and on Reference Amounts Customarily Consumed. Food rankings generated by different models were correlated with each other and with the foods' energy density and energy cost. RESULTS: Nutrient profile models based on protein, fiber, vitamins and minerals showed an inverse correlation with energy density that diminished as more micronutrients were introduced into the model. Models based on fat, sugar and sodium were highly correlated with energy density. Foods classified as healthier were generally associated with higher energy costs. CONCLUSIONS: Not all models accurately reflected the foods' content of nutrients known to be beneficial to health. High correlations with energy density meant that some models classified foods based on their energy density as opposed to nutrient content.
BACKGROUND: Nutrient profiling of foods is defined as the science of classifying foods based on their nutrient content. Food rankings generated by nutrient profile models need to be tested against objective reality as opposed to public opinion. OBJECTIVE: To test the performance of selected nutrient profile models in relation to the foods' energy density (kcal g(-1)) and energy cost (Dollar per 1000 kcal). SUBJECTS/ METHODS: Analyses were based on 378 component foods of a food frequency instrument. The models tested were the French nutrient adequacy models NAS23 and NAS16 and nutrient density models NDS23 and NDS16; and a family of nutrient-rich models (NR(n), where n=5-7; 10-12, and 15). Also tested were LIM scores and a modified British Food Standards Agency model WXYfm. Profiles were calculated based on 100 g, 100 kcal and on Reference Amounts Customarily Consumed. Food rankings generated by different models were correlated with each other and with the foods' energy density and energy cost. RESULTS: Nutrient profile models based on protein, fiber, vitamins and minerals showed an inverse correlation with energy density that diminished as more micronutrients were introduced into the model. Models based on fat, sugar and sodium were highly correlated with energy density. Foods classified as healthier were generally associated with higher energy costs. CONCLUSIONS: Not all models accurately reflected the foods' content of nutrients known to be beneficial to health. High correlations with energy density meant that some models classified foods based on their energy density as opposed to nutrient content.
Authors: P Scarborough; C Payne; C G Agu; A Kaur; A Mizdrak; M Rayner; J C G Halford; E Boyland Journal: Eur J Clin Nutr Date: 2013-06-26 Impact factor: 4.016
Authors: May A Beydoun; Marie T Fanelli-Kuczmarski; Allyssa Allen; Hind A Beydoun; Barry M Popkin; Michele K Evans; Alan B Zonderman Journal: PLoS One Date: 2015-11-04 Impact factor: 3.240