| Literature DB >> 26273127 |
Shu Wen Ng1, Gregory Bricker1, Kuo-Ping Li1, Emily Ford Yoon1, Jiyoung Kang2, Brian Westrich3.
Abstract
This study developed a method to estimate added sugar content in consumer packaged goods (CPG) that can keep pace with the dynamic food system. A team including registered dietitians, a food scientist and programmers developed a batch-mode ingredient matching and linear programming (LP) approach to estimate the amount of each ingredient needed in a given product to produce a nutrient profile similar to that reported on its nutrition facts label (NFL). Added sugar content was estimated for 7021 products available in 2007-08 that contain sugar from ten beverage categories. Of these, flavored waters had the lowest added sugar amounts (4.3g/100g), while sweetened dairy and dairy alternative beverages had the smallest percentage of added sugars (65.6% of Total Sugars; 33.8% of Calories). Estimation validity was determined by comparing LP estimated values to NFL values, as well as in a small validation study. LP estimates appeared reasonable compared to NFL values for calories, carbohydrates and total sugars, and performed well in the validation test; however, further work is needed to obtain more definitive conclusions on the accuracy of added sugar estimates in CPGs. As nutrition labeling regulations evolve, this approach can be adapted to test for potential product-specific, category-level, and population-level implications.Entities:
Keywords: Added sugars; Beverages; Food analysis; Food composition; Ingredients; Linear programming; Nutrition label
Year: 2015 PMID: 26273127 PMCID: PMC4528366 DOI: 10.1016/j.jfca.2015.04.004
Source DB: PubMed Journal: J Food Compost Anal ISSN: 0889-1575 Impact factor: 4.556