Abstract

BackgroundExisting nutrition knowledge measures tend to be lengthy or tailored for specific contexts, making them unsuitable for population-based surveys. Given the growing emphasis within country-specific dietary guidelines on reducing consumption of highly processed foods, consumers’ ability to understand and apply principles related to level of food processing could serve as a proxy measure of general nutrition knowledge. ObjectiveTo examine the content validity of the Food Processing Knowledge (FoodProK) score based on subject matter expert consultation with Registered dietitian nutritionists (RDNs). MethodsRDNs in Canada (n = 64) completed an online survey, including the FoodProK, in January 2020. Participants rated the “healthiness” of 12 food products from four categories (fruit, meat, dairy, and grains) on a scale from 1 to 10. FoodProK scores were assigned based on concordance of ratings within each food category, with rankings according to the NOVA classification system, with less processed foods representing higher healthiness. For each category, one-way repeated-measures analysis of variance models tested whether the three product ratings were significantly different from one another. Descriptive statistics compared ratings and FoodProK scores across categories. Open-ended feedback was solicited to assess face validity of the score. ResultsRDNs’ FoodProK scores were strongly associated with level of food processing. Almost one in three RDNs received perfect FoodProK scores, and the mean score was 7.0 of 8.0 possible points. Within each category, the three foods received significantly different healthiness ratings, in the same order as the NOVA system (P < 0.001 for all contrasts). Open-ended responses showed that RDNs did not perceive meaningful differences between the processed meat products, suggesting the need to change one of the products in the meat category. Overall, 80% of RDNs reported level of processing as an important indicator of the healthiness of foods. ConclusionsLevel of food processing represents a promising framework for assessing general nutrition knowledge in population-based surveys.

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