Explaining Fruit and Vegetable Intake Using a Consumer Marketing Tool

• Published in: Health education & behavior Vol. 36; no. 5; pp. 895 - 914
• Main Authors: Della, Lindsay J., DeJoy, David M., Lance, Charles E.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.10.2009; Sage Publications; SAGE PUBLICATIONS, INC
• Subjects: Algorithms; Attitudes; Audiences; Behavior; Behavior Theories; Biological and medical sciences; Campaigns; Case Studies; Consumer advertising; Consumer Science; Consumption; Cross-Sectional Studies; Data Collection; Dietetics; Eating Habits; Feeding Behavior - psychology; Food; Fruit; Fruits; Health behavior; Healthy food; Humans; Intention; Marketing; Medical sciences; Miscellaneous; Models, Theoretical; Perceived control; Planned behaviour theory; Prediction; Prevention and actions; Psychological Theory; Public health. Hygiene; Public health. Hygiene-occupational medicine; Social Marketing; Statistical Analysis; Structural Equation Models; Surveys and Questionnaires; Vegetables; theory of planned behavior; fruit and vegetable; audience segmentation; Segmentation; Image processing; Theory; Fruit vegetable; Health education; Marketing; Consumer; Food intake; Public health; theory ofplanned behavior; Tool
• ISSN: 1090-1981; 1552-6127
• DOI: 10.1177/1090198108322820

In response to calls to reinvent the 5 A Day fruit and vegetable campaign, this study assesses the utility of VALS™, a consumer-based audience segmentation tool that divides the U.S. population into groups leading similar lifestyles. The study examines whether the impact of theory of planned behavior (TPB) constructs varies across VALS groups in a cross-sectional sample of 1,588 U.S. adults. In a multigroup structural equation model, the VALS audience group variable moderated latent TPB relationships. Attitudes, subjective norms, and perceived behavioral control explained 57% to 70% of the variation in intention to eat fruit and vegetables across 5 different VALS groups. Perceived behavioral control and intention also predicted self-reported consumption behavior (R² = 20% to 71% across VALS groups). Bivariate z tests were calculated to determine statistical differences in parameter estimates across groups. Nine of the bivariate z tests were statistically significant (p ≤ .04), with standardized coefficients ranging from .05 to .70. These findings confirm the efficacy of using the TPB to explain variation in fruit and vegetable consumption as well as the validity of using a consumer-based algorithm to segment audiences for fruit and vegetable consumption messaging.