Development of a questionnaire to assay recalled liking for salt, sweet and fat.

摘要

Liking for a sweet, salty or fatty diet may induce overconsumption of simple carbohydrates, sodium or lipids. Measuring overall liking of the corresponding sensory sensations contributes to understanding the determinants of dietary behaviours. However, no standardized validated questionnaire assaying these sensations is currently available. In the present study, we developed a web-based questionnaire, "PrefQuest", which measures recalled liking for the following four sensations: salt, fat and salt, sweet, fat and sweet. PrefQuest included four types of items: (1) liking for sweet, fatty-sweet and fatty-salty foods, (2) preferences in the level of seasoning by adding salt, sweeteners, or fat, (3) preferences for types of dishes in a restaurant menu and (4) overall questions about sweet-, salt- and fat-related behaviours. A development study (n = 198) demonstrated that PrefQuest was feasible, well-perceived, only lasted about 20 min and that items were repeatable (overall mean intra-class correlation coefficient: 0.77, SD 0.08). Construct validity was then evaluated on a larger population sample (n = 47803). The underlying structure within each of the four sensations was determined by exploratory factor analysis and then internally validated by confirmatory factor analysis. After a selection of the most relevant items, the salt, fat-and-salt, sweet, and fat-and-sweet scales exhibited a theoretically meaningful factor structure, unidimensional for the salt scale and with interrelated sub-dimensions for the sweet, fat-and-salt, and fat-and-sweet scales. Based on the fat-and-sweet and fat-and-salt scales, a fat model was also unveiled. For each factor, internal consistency as well as convergent and divergent validities were demonstrated. Overall, PrefQuest is an internally valid and original tool that can be used to assay recalled liking for sweet, salt, and fat considered altogether or separately as fat and salt or fat and sweet, and can be applied to large population surveys. All rights reserved, Elsevier.