Measuring Consumer Preferences in Changing Food Environments: A Methods Review. (29th May 2020) - Bell, Winnie; Coates, Jennifer; Masters, William; Wilson, Norbert
Abstract: Objectives: Measuring consumer preferences for different food quality attributes in low- and middle-income countries (LMICs) is increasingly important for interventions and policies to better address poor nutrition and health outcomes in the context of rapidly changing food environments. Despite the importance of measuring preferences, limited research has been conducted in LMICs to develop a better understanding of what matters most to consumers. This study reviews existing methods for measuring preferences and proposes a way forward for the nutrition public health community to address this important gap. Methods: Relevant papers were identified in PubMed using pre-selected Mesh terms and by searching reference lists of key review articles. Approaches identified span the fields of marketing, economics, psychology, and nutrition public health. The papers reviewed used different methods to measure preferences of various types of food attributes. Results: In marketing and economics, the term conjoint analysis is used to describe a category of methods that measure the stated preference of respondents by asking them to rate, rank, or choose between competing alternatives. Within conjoint analysis, several different methods exist including discrete choice experiences, ranking conjoint analysis, and best-worst scaling and each can be used to elicit preferences about observable and unobservable attributes of foods (e.g., price, taste etc.). Within the field of psychology, several techniques have been used including the Food Choice Questionnaire and Food Choice Values. Other approaches include qualitative interviews, pile sorting, and Likert scale-based instruments. Each method has strengths and weaknesses but in general, those from marketing and economics have the benefit of resulting in a ranked choice, in contrast to Likert scales and pile sorting which can be difficult to interpret and cognitively burdensome. Conclusions: Most methods have been primarily developed, validated, and used in high-income countries with much less application in LMICs. Further research is required to adapt and develop preference elicitation methods for LMICs to better measure food preferences in the context of rapidly evolving food environments. Funding Sources: N/A.