4.7 Article

Methodology for the Determination of Fruit, Vegetable, Nut and Legume Points for Food Supplies without Quantitative Ingredient Declarations and Its Application to a Large Canadian Packaged Food and Beverage Database

Journal

FOODS
Volume 9, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/foods9081127

Keywords

nutrient profiling; FVNL points; ingredients; nutrition policy

Funding

  1. Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award
  2. Ontario Graduate Scholarship
  3. University of Toronto Department of Nutritional Sciences Graduate Student Fellowship
  4. CIHR Frederick Banting and Charles Best Canada Graduate Scholarships Master's Award
  5. Mitacs Elevate Postdoctoral Fellowship
  6. Endeavor Research Fellowship
  7. Foundation for High Blood Pressure Research Early Career Research Transition Grant
  8. CIHR Strategic Training Grant in Population Intervention for Chronic Disease Prevention
  9. CIHR Collaborative Training Program in Public Health Policy
  10. Fonds de recherche du Quebec-Sante (FRQS) Chercheurs-boursiers-Junior 1 Young Investigator Salary Award
  11. CIHR Strategic Operating Grant [2016PJT-152979]
  12. Earle W. McHenry Research Chair from the University of Toronto

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Nutrient profiling (NP) models are useful tools for objectively and transparently quantifying the nutritional quality of packaged foods and beverages. Many NP models incorporate ingredients beneficial for health (e.g., fruits, vegetables, nuts, legumes (FVNL)) in addition to less healthful nutrients or components, assigning points based on the proportion of the product that contains FVNL ingredients. However, with food labelling in most countries lacking mandatory quantitative ingredient declarations (QUIDs), there is potential for the estimation of FVNL points to be ambiguous and inconsistent. The purpose of this article was to describe the development and application of methodology for estimating FVNL points for products without QUIDs, based on the position of FVNL components within the ingredients list. Using this method, FVNL points were calculated for packaged foods and beverages in the University of Toronto Food Label Information Program 2017 database (n= 17,337). Distributions of FVNL points were examined overall and by food category. This study provides evidence of the feasibility of this method in distinguishing between products with differing amounts of FVNL ingredients. This method will be valuable for researchers and policymakers in ensuring consistent, objective and reproducible estimations of FVNL points-and consequently, assessments of product healthfulness-for food supplies without QUIDs.

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