Towards a data-driven approach to intervention design: A predictive path model of healthy eating determinants

Abstract

Dietary behavior and attitude play major roles in the worldwide prevalence of obesity, as weight is gained when energy intake exceeds energy expenditure. Although research has focused on designing technological interventions for healthy eating behavior, recent reviews have identified a gap in the knowledge base regarding the variables/determinants of healthy eating and the interactions between them. We developed a model of some determinants and their impact on healthy eating as a basis for designing technological interventions to promote healthy eating behavior within a target community. The main goal of this work is to understand how people adopt a healthy eating attitude, the variables influencing such attitudes, the interactions between these variables, and the degree of influence each variable exerts on healthy eating attitudes. We use fast food-related eating behavior as our case study. Our model shows that weight concern, nutrition knowledge, concern for diseases, social influence, and food choice motives predicts 65% of the variance in healthy eating attitudes, showing the suitability of the model for use in predicting healthy eating attitude. This result will inform decisions on the most effective persuasive strategy for designing interventions to promote healthy eating behavior. © 2012 Springer-Verlag.