The relationship of nutrition knowledge structures to accuracy of food label interpretation in adults

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Virginia Tech

A new, standardized food label developed by the Food and Drug Administration is appearing on products this year. Extensive research on consumer use suggests that approximately 20 % of the U.S. population, composed mainly of elderly and minorities, cannot correctly interpret the nutrition information on the label. This research explored the specific knowledge required for correct interpretation based on a model in which nutrition knowledge was organized in hierarchical levels: food groups, macronutrients and micronutrients in foods, with each level including dimensions of nutrition terminology, health relationships and related mathematics skills.

An instrument was developed and pilot tested to measure knowledge at each level, as well as to measure accuracy in food label interpretation. Test items were revised based on peer input, correlational data, item analysis, and reliability. The revised instrument was then administered to purposive samples of adults (250 subjects) representing the range of nutrition knowledge measured by the test. Scores were re-analyzed to establish the validity and reliability of the new instrument. Factor analysis was used to explore the value of the original hierarchical model and to posit an additional model based on conceptual complexity. Hierarchical multiple regression was used to predict accuracy of food label interpretation based on factors depicted by both models.

Findings indicated that the structures outlined in each model are useful predictors of food label interpretation, accounting for over 52 percent of the variance. Suggestions are made for further development of the test instrument and on how to incorporate learner pre-assessment in designing nutrition education interventions.