The development and evaluation of a novel measure of discretionary food intake
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Background
While dietary guidelines recommend limiting foods high in added sugars, saturated fat, refined grains, and sodium, and all alcoholic beverages, there are no available methods for classifying discretionary foods or quantifying discretionary food intake using dietary intake data.
Objective
To develop and evaluate a nutrient-based method to classify discretionary foods and compare with two established methods for classifying foods to limit.
Design
Foods in the 2017-2018 USDA Food and Nutrient Database for Dietary Studies (FNDDS, n=6909) were classified as discretionary, hyperpalatable, and ultra-processed, and their nutrient values were compared. Correlations of discretionary, hyperpalatable, and ultra-processed food intakes with overall diet quality were evaluated using 2017-2018 National Health and Nutrition Examination Survey (NHANES) data.
Participants
All non-pregnant NHANES participants age 2+ years with two valid 24-hour recalls (n=6136) were included.
Main outcome measures
Outcomes included food-level nutrient density (Nutrient Rich Foods 9.3 index) and person-level Healthy Eating Index-2020 scores (HEI total, HEI-adequacy, and HEI-moderation).
Statistical Analyses
Differences in nutrient density of FNDDS foods classified as discretionary, hyperpalatable, and ultra-processed vs. not were compared using t-tests and ANOVA. Fisher’s z-transformation compared associations of HEI scores with intake (percent kcal) from discretionary, hyperpalatable, and ultra-processed foods.
Results
The difference in nutrient density (p<0.001) of discretionary vs. non-discretionary foods (mean diff=74.8, 95%CI:70.6-78.9) was larger than that of ultra-processed vs. non-ultra-processed (mean diff=29.7, 95%CI:25.1-34.2) and hyperpalatable vs. non-hyperpalatable (mean diff=53.2, 95%CI:49.3-57.1). Discretionary foods contributed 77% of energy intake in U.S. children and adults, while hyperpalatable foods and ultra-processed foods contributed 71% and 58%, respectively. Inverse associations of HEI-2020 total (r=-0.72) and HEI-adequacy scores (r=-0.67) with discretionary food intake were stronger than those with hyperpalatable (r=-0.40; - 0.23) and ultra-processed food intake (r=-0.49;-0.43); associations with HEI-moderation scores were similar across all classifications.
Conclusions
The discretionary food classification method effectively distinguishes between low-and high-nutrient dense foods and is strongly associated with adherence to dietary guidelines. The method may improve diet quality assessment and inform public health interventions.
