Adam Drewnowski1. 1. Center for Public Health Nutrition, School of Public Health, University of Washington, Seattle, WA 98195-3410, USA. adamdrew@u.washington.edu
Abstract
BACKGROUND: The Nutrient Rich Foods (NRF) Index is a formal scoring system that ranks foods on the basis of their nutrient content. When used in conjunction with a food prices database, it can help identify foods that are both nutritious and affordable. OBJECTIVE: Our aim was to identify healthy, affordable foods and food groups by using the NRF index and US Department of Agriculture (USDA) nutrient composition and food prices data sets. DESIGN: Foods in the USDA Food and Nutrition Database for Dietary Studies 1.0 were scored by using the NRF index. This NRF algorithm was represented by the sum of the percentage of the daily values of 9 nutrients to encourage (protein, fiber, vitamin A, vitamin C, vitamin E, calcium, iron, magnesium, and potassium) minus the sum of the percentage of the maximum recommended values for 3 nutrients to limit (saturated fat, added sugar, and sodium). NRF scores and mean national food prices were calculated per calorie and per US Food and Drug Administration-defined serving. RESULTS: Each of the 9 USDA food groups offered foods of diverse nutritive value and cost. Eggs, dry beans and legumes, and meat and milk products were the lowest-cost sources of protein. Milk and milk products were the lowest-cost sources of calcium, whereas vegetables and fruit were the lowest-cost sources of vitamin C. Milk, potatoes, citrus juices, cereals, and beans had more favorable overall nutrient-to-price ratios than did many vegetables and fruit. Energy-dense grains, sweets, and fats provided most of the calories but fewer nutrients per dollar. CONCLUSION: One important application of nutrient profile models is to help consumers identify foods that provide optimal nutrition at an affordable cost.
BACKGROUND: The Nutrient Rich Foods (NRF) Index is a formal scoring system that ranks foods on the basis of their nutrient content. When used in conjunction with a food prices database, it can help identify foods that are both nutritious and affordable. OBJECTIVE: Our aim was to identify healthy, affordable foods and food groups by using the NRF index and US Department of Agriculture (USDA) nutrient composition and food prices data sets. DESIGN: Foods in the USDA Food and Nutrition Database for Dietary Studies 1.0 were scored by using the NRF index. This NRF algorithm was represented by the sum of the percentage of the daily values of 9 nutrients to encourage (protein, fiber, vitamin A, vitamin C, vitamin E, calcium, iron, magnesium, and potassium) minus the sum of the percentage of the maximum recommended values for 3 nutrients to limit (saturated fat, added sugar, and sodium). NRF scores and mean national food prices were calculated per calorie and per US Food and Drug Administration-defined serving. RESULTS: Each of the 9 USDA food groups offered foods of diverse nutritive value and cost. Eggs, dry beans and legumes, and meat and milk products were the lowest-cost sources of protein. Milk and milk products were the lowest-cost sources of calcium, whereas vegetables and fruit were the lowest-cost sources of vitamin C. Milk, potatoes, citrus juices, cereals, and beans had more favorable overall nutrient-to-price ratios than did many vegetables and fruit. Energy-dense grains, sweets, and fats provided most of the calories but fewer nutrients per dollar. CONCLUSION: One important application of nutrient profile models is to help consumers identify foods that provide optimal nutrition at an affordable cost.
Authors: Sathish Subramanian; Laura V Blanton; Steven A Frese; Mark Charbonneau; David A Mills; Jeffrey I Gordon Journal: Cell Date: 2015-03-26 Impact factor: 41.582