Estimating added sugars in US consumer packaged goods: An application to beverages in 2007-08.
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.
University of North Carolina at Chapel Hill CB #8120, Chapel Hill, NC 27599.
Shu Wen
SW
Ng
University of North Carolina at Chapel Hill CB #8120, Chapel Hill, NC 27599.
Gregory
G
Bricker
University of North Carolina at Chapel Hill CB #8120, Chapel Hill, NC 27599.
Kuo-Ping
KP
Li
University of North Carolina at Chapel Hill CB #8120, Chapel Hill, NC 27599.
Emily Ford
EF
Yoon
University of North Carolina at Chapel Hill CB #8120, Chapel Hill, NC 27599 ; JK conducted this work while with UNC-Chapel Hill.
Jiyoung
J
Kang
McWest Corporation 2321 30th Ave S, Minneapolis, MN 55406.
Brian
B
Westrich
Added sugars; Beverages; Food analysis; Food composition; Ingredients; Linear programming; Nutrition label