A Nutrient Density Standard for Vegetables and Fruits: Nutrients per Calorie and Nutrients per Unit Cost

University of Washington Seattle, Seattle, Washington, United States
Journal of the American Dietetic Association (Impact Factor: 3.92). 01/2006; 105(12):1881-7. DOI: 10.1016/j.jada.2005.09.005
Source: PubMed


The Dietary Guidelines for Americans 2005 recommended that consumers give priority to nutrient-dense foods, those that contain substantial amounts of key nutrients in relation to the dietary energy they provide. This study developed a scoring system to estimate the nutritional adequacy of vegetables and fruits, on a per weight, per calorie, and per unit cost basis.
We used a French national food composition database for 637 foods, including 129 vegetables and fruits. Mean national retail prices were obtained for each food.
The nutrient adequacy score was defined as the mean of percent daily values for 16 nutrients, based on 100 g of food. The nutrient density score and the nutrient-to-price ratio were the mean of percent daily values for 16 nutrients, expressed per 100 kcal and per 1 euro of food, respectively. Relationships between energy density of vegetables and fruits, nutrient adequacy score, nutrient density score, and nutrient-to-price ratio were tested using linear regression.
Energy density and nutrient density score were negatively correlated, confirming the widely accepted notion that energy-dense foods tend to be nutrient-poor. As expected, fruits and vegetables had the highest nutrient density score because they were nutrient-rich in relation to their low energy content. They also had a relatively high nutrient-to-price ratio, showing that they provided nutrients at a reasonable cost when compared with other foods.
Foods ranked differently when nutritional adequacy was calculated per weight (nutrient adequacy score), per calorie (nutrient density score), or per unit cost (nutrient-to-price ratio). The present results showed that although fruits and vegetables are an expensive source of dietary energy, they provide key nutrients at a reasonable cost.

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    • "While the number of nutrients involved in calculating the SAIN score is often questioned regarding whether it is fully representative of the nutritional quality of a food group (i.e. fruits and vegetables ), the number of disqualifying nutrients is never questioned (Darmon et al., 2005, 2009). There are, potential disqualifying nutrients that are not systematically included on nutritional labels (trans fatty acids) or that have not clear maximal recommended daily values (acrylamide). "
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    ABSTRACT: This paper analyzes the impact of deep-fat frying options on the nutritional profile of fried plantain-based products by using the SAIN, LIM system. 23 nutrients and 4 disqualifying compound including acrylamide were used to calculate SAIN and LIM scores. Experimental data for heat, mass transfers and reactions modeling were from previous studies. The options of the frying were oil type, micronutrient-enrichment or not, thickness of final product, frying temperature and number of baths. Frying turned plantain from neutral food to positive or negative categories as a function of process variables. The most impacting parameters were the oil type (SAIN and LIM scores of crisps varied by 6.5 and 7.5-fold respectively) and product thickness assimilated with the final oil content (LIM scores increased by 5-fold from 6% to 33% final fat content). Acrylamide increased LIM scores by 2 to 11-fold in crisps while the use of oils enriched with beta-carotene impacted the SAIN scores by 10-20%. The best trade off process time/nutritional score was obtained for thick products (fat content <25%) fried in sunflower oil in non-isothermal conditions. The use of geometrical mean to calculate SAIN scores enabled a more sensitive evaluation of the effect of number of bath.
    Journal of Food Engineering 03/2015; 149. DOI:10.1016/j.jfoodeng.2014.10.017 · 2.77 Impact Factor
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    • "Second, a nutrient density score was calculated for each food using the method of Darmon et al (10). The numerator is a nutrient adequacy score calculated as the mean of percent daily values (DVs) for the qualifying nutrients (based on a 2,000 kcal/d diet [11]) per 100 g of food. "
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    ABSTRACT: National nutrition guidelines emphasize consumption of powerhouse fruits and vegetables (PFV), foods most strongly associated with reduced chronic disease risk; yet efforts to define PFV are lacking. This study developed and validated a classification scheme defining PFV as foods providing, on average, 10% or more daily value per 100 kcal of 17 qualifying nutrients. Of 47 foods studied, 41 satisfied the powerhouse criterion and were more nutrient-dense than were non-PFV, providing preliminary evidence of the validity of the classification scheme. The proposed classification scheme is offered as a tool for nutrition education and dietary guidance.
    Preventing chronic disease 06/2014; 11(6). DOI:10.5888/pcd11.130390 · 2.12 Impact Factor
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    • "By construction, the highest theoretically achievable value for the MAR is 100% adequacy/day. A total of 16 positive nutrients were included in the MAR, including fibre, proteins, vitamins, minerals, and essential fatty acids [41]. All selected foods (including milk, juice, and soft drinks) were used to calculate the MAR for each basket. "
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    ABSTRACT: Background Prices are an important determinant of food choices. Consequently, food price policies (subsidies and/or taxes) are proposed to improve the nutritional quality of diets. The aim of the present study was to explore the impact of food price policies on the expenditures and nutritional quality of the food baskets chosen by low- and medium-income households. Methods Experimental economics was used to examine two price manipulations: i) a fruit and vegetable price subsidy named “fruit and vegetables condition”; ii) a healthy-product subsidy coupled with an unhealthy-product tax named “nutrient profile condition”. The nutrient profiling system called SAIN,LIM was used. This system classifies each individual food according to its overall nutritional quality which then allows for a food item to be taxed or subsidized. Women from low- (n = 95) and medium-incomes (n = 33) selected a daily food basket, first, at current prices and then at manipulated prices. The redistributive effects of experimental conditions were assessed by comparing the extent of savings induced by subsidies and of costs generated by the tax on the two income groups. Energy density (kcal/100 g), free sugars (% energy) and the mean adequacy ratio (MAR) were used as nutritional quality indicators. Results At baseline (before price manipulations), low-income women selected less expensive and less healthy baskets than medium-income ones. After price manipulations expenditures for both income group decreased significantly, whereas, the nutritional quality improved (energy density decreased, the MAR increased). Additionally, the redistributive effects were less favourable for low-income women and their nutritional quality improvements from baseline were significantly lower. Conclusion Low-income women derived fewer financial and nutritional benefits from implemented food subsidies and taxes than medium-income women. This outcome suggests that food price policies may improve diet quality while increasing socio-economic inequalities in nutrition.
    International Journal of Behavioral Nutrition and Physical Activity 05/2014; 11(1):66. DOI:10.1186/1479-5868-11-66 · 4.11 Impact Factor
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