Chrome Extension
WeChat Mini Program
Use on ChatGLM

Prioritizing Food Group Messages: Topics with Most Potential for Improved Consumer Behavior

Journal of Nutrition Education and Behavior(2013)

Cited 0|Views1
No score
Abstract
To identify educational messages that may have the most potential for improved consumer behavior, based on current consumption practices in relation to dietary recommendations. Nutrition educators and their clientele. This analysis builds on prior studies that identified food group intakes in comparison to recommendations and intakes of nutrient-dense versus typically consumed foods. The 2010 Dietary Guidelines encourages increasing consumption of underconsumed food groups and choosing foods in nutrient-dense forms. These recommendations can lead to numerous educational messages for consumers, which may be overwhelming. For each food group, this analysis compared intakes to recommendations and nutrient-dense to typical food choices, to determine where consumer choices differ most from the ideal and which messages provide the most opportunity for improving behavior. For fruits, dark green vegetables, beans and peas, whole grains, and seafood, the difference between intake and recommendations is greater than the difference between nutrient-dense and typical choices. Therefore, priority messages should focus on how to increase intake. For starchy vegetables, meat, and poultry, priority messages should focus on how to select these foods in more nutrient-dense forms. For dairy products and red and orange vegetables, both increased intake and making nutrient-dense choices are important messages. Prioritizing messages on which to focus may help consumers feel less overwhelmed with all of the nutrition messages they hear. This analysis provided an objective method for selecting a message for each food group that may have the most likelihood of making a difference, by allowing consumers to focus on fewer behaviors for improvement.
More
Translated text
Key words
prioritizing food group messages,improved consumer behavior,topics
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined