Using the Multi-Attribute Utility Model to Better Understand Fruit and Vegetable Intake among College Students
This study examined the association between parameters of the decision-making processes that are described in the Multi-Attribute Utility (MAU) model and actual food choices (fruit and vegetable consumption) among undergraduate students. Four hundred and six undergraduates from a large, public university in Southern California completed a pencil-and-paper questionnaire for the parameters of MAU, which consist of the perceived value, perceived likelihood, and momentary salience for each anticipated consequence of eating a healthy diet. Fruit and vegetable intake was collected daily using an online food intake log. Linear regression analysis revealed that MAU total scores were a significant predictor of fruit plus vegetable consumption (p = .000). T-test results indicated that high fruit plus vegetable eaters and low fruit plus vegetable eaters were significantly different from each other on individual parameter scores of the MAU model (range, p = .032 to p = .000). Conclusions: This study suggest that the MAU model may predict eating behaviors and provides support for further investigation; the MAU framework may help identify the factors that have greatest influence college students’ nutrition decision making processes, and can aid in the development of interventions that address target consequences that have high utility scores in the target population.