Exploring a Combined Quantitative and Qualitative Research Approach in Developing a Culturally Competent Dietary Behavior Assessment Instrument
Cultural competence is widely recognized as an essential strategy for reducing health disparities. As the United States' population becomes increasingly ethnoculturally diverse, these disparities are becoming even more pronounced. One particular challenge in this regard concerns overweight/obesity prevalence among American adults, as a disproportionately high number of racial and ethnic minority adults are classified as overweight or obese. Dietary behavior assessments are often utilized by health and human services professionals to obtain the data necessary to promote goals such as the reduction and elimination of overweight/obesity across all ethno-cultural groups.
The primary objective of this research study was to develop, test, and evaluate a culturally-competent dietary behavior assessment instrument by effectively synthesizing qualitative methods from Cognitive Anthropology with appropriate survey research and quantitative statistical methods. Specifically, a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression, and Poisson regression in conjunction with the free listing qualitative research technique from Cognitive Anthropology was explored as a possible combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level.
Binary logistic regression and Poisson regression enabled the relationship between selected food categories and certain demographic/cultural indicators to be modeled, while hierarchical cluster analyses enabled modeling of the distinct patterns of food category groupings that comprise individuals' regular diet. Additionally, initial qualitative analyses of the raw data promoted an understanding of the influence that the local fast food and dine-in restaurant environment has on the dietary behaviors of the target population.
The results of this study suggest that a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression analysis, and Poisson regression analysis founded upon qualitative research principles has potential for use as a combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. By employing these techniques, researchers can analyze individual dietary behaviors and eating patterns from a multifaceted perspective. In turn, public health professionals can develop community-based, cross-culturally relevant programs and interventions that are equally effective across all ethno-cultural groups in their target population.
Branislav Vidakovic, Ph.D. (Advisor), Georgia Institute of Technology, School of Industrial and Systems Engineering
Paula Edwards, Ph.D., Himformatics, LLC
Paul Griffin, Ph.D., Georgia Institute of Technology, School of Industrial and Systems Engineering
Rebecca Grinter, Ph.D., Georgia Institute of Technology, College of Computing
Rebecca Mullis, Ph.D., University of Georgia, Department of Foods and Nutrition
Principal Investigator: W. Brad Jones, Ph.D.
Download link: http://hdl.handle.net/1853/29718