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Robustness of Food Processing Classification Systems

Author:
Bleiweiss-Sande, Rachel, Chui, Kenneth, Evans, E. Whitney, Goldberg, Jeanne, Amin, Sarah, Sacheck, Jennifer
Source:
Nutrients 2019 v.11 no.6
ISSN:
2072-6643
Subject:
National Health and Nutrition Examination Survey, added sugars, children, discriminant analysis, food intake, food processing, minimally processed foods, nutrient content, nutritional adequacy, potassium, regression analysis, sodium, vitamin D
Abstract:
Discrepancies exist among food processing classification systems and in the relationship between processed food intake and dietary quality of children. This study compared inter-rater reliability, food processing category, and the relationship between processing category and nutrient concentration among three systems (Nova, International Food Information Council (IFIC), and University of North Carolina at Chapel Hill (UNC)). Processing categories for the top 100 most commonly consumed foods children consume (NHANES 2013&ndash;2014) were independently coded and compared using Spearman&rsquo;s rank correlation coefficient. Relative ability of nutrient concentration to predict processing category was investigated using linear discriminant analysis and multinomial logistic regression and compared between systems using Cohen&rsquo;s kappa coefficient. UNC had the highest inter-rater reliability (&rho; = 0.97), followed by IFIC (&rho; = 0.78) and Nova (&rho; = 0.76). UNC and Nova had the highest agreement (80%). Lower potassium was predictive of IFIC&rsquo;s classification of foods as moderately compared to minimally processed (p = 0.01); lower vitamin D was predictive of UNC&rsquo;s classification of foods as highly compared to minimally processed (p = 0.04). Sodium and added sugars were predictive of all systems&rsquo; classification of highly compared to minimally processed foods (p < 0.05). Current classification systems may not sufficiently identify foods with high nutrient quality commonly consumed by children in the U.S.
Agid:
6508043