Measurement and Correlates of Food Selection Motivations in a United States Sample

Bibliographic Data

ID15329372
AuthorsDanielle Dunn (0000-0001-7447-5365, Virginia Commonwealth University, corresponding author), Danielle Keenan-Miller (0000-0002-8923-0229, University of California, Los Angeles), Kathy K Isoldi (0000-0003-3465-4152, Kathy K. Isoldi, Associate Professor, Department of Health Sciences and Administration , Long Island University Post, Brookville, NY, United States;, Email: [email protected]), Alessandra Sarcona (0000-0003-4668-2732, Alessandra Sarcona, Associate Professor, Department of Nutrition, West Chester University of Pennsylvania, West Chester, PA, United States), Veronika Dolar (0000-0003-0842-3860, Veronika Dolar, Assistant Professor, Department of Politics, Economics and Law, State University of New York (SUNY) at Old Westbury, Old Westbury, NY, United States), Raquel P F Guiné (0000-0003-0595-6805, Polytechnic Institute of Viseu)
Year2022
Volume46
Issue2
Pages186-196
Publication date2022-04-20
Open AccessNo
TypeARTICLE
VenueAmerican Journal of Health Behavior (JOURNAL)
Journal identifiersISSN: 1087-3244 • E-ISSN: 1945-7359
PublisherPNG Publications (PUBLISHER • US)
DOI10.5993/ajhb.46.2.8
PMID35501960
OpenAlexW4225404415
LanguageEN
References cited19

Background: In this study, we explored the factors that motivate food choice, and evaluated the psychometric properties and demographic correlates of the Eating Motivation (EATMOT) questionnaire in adults in the United States (US). Methods: This cross-sectional survey involved 905 adults in 6 sites across the US. The EATMOT questionnaire measures participants' self-reported motivations for food selection, demographic, and anthropometric data. Analyses included exploratory and confirmatory factor analyses, correlations, Welch's t-tests, and logistic regressions. Results: We established a 3-factor model (health-related, emotional, and environmental/political motivations) as the best fit to the data (CFI = .983, RMSEA = .049, SRMR = .054). Gender differences were found within the 3 factors, as well as in the intercorrelations between factors. Higher levels of health-related motivations (B = .10, SE = .04, OR = 1.11 (95% CI: 1.03, 1.19), p = .006) were associated with increased reports of weight loss dieting, whereas higher levels of environmental/political motivations (B = -.09, SE = .04, OR = 0.91, p = .02) were associated with fewer reports of weight-loss dieting. Conclusion: An abbreviated version of the EATMOT scale is appropriate for use in a US sample and identifies 3 categories of factors that impact dietary choices. These factors may be important in building interventions to improve diets

Anthropometry · Confirmatory factor analysis · Dieting · Environmental health · Exploratory factor analysis · Food choice · Geography · Logistic regression · Obesity · Psychological intervention · Psychometrics · Scale (ratio · Statistics · Structural equation modeling · Weight loss · Behavioral Health and Interventions · Clinical Psychology · Demography · Environmental Education and Sustainability · Medicine · Obesity, Physical Activity, Diet · Psychology · Social Psychology · Gerontology

Tools

Open DOI