Assessing diet in a university student population: A longitudinal food card transaction data approach

Starting university is an important time with respect to dietary changes. This study reports a novel approach to assessing student diet by utilising student-level food transaction data to explore dietary patterns.

First year students living in catered accommodation at the University of Leeds (UK) received pre-credited food cards for use in University catering facilities. Food card transaction data were obtained for semester 1, 2016, and linked with student age and gender. K-means cluster analysis was applied to the transaction data to identify clusters of food purchasing behaviours. Differences in demographic and behavioural characteristics across clusters were examined using Chi-squared tests. The semester was divided into three time periods to explore longitudinal changes in purchasing patterns.

Seven dietary clusters were identified: ‘Vegetarian’, ‘Omnivores’, ‘Dieters’, ‘Dish of the Day’, ‘Grab-and-Go’, ‘Carb Lovers’ and ‘Snackers’. There were statistically significant differences in: gender (p<0.001) with women dominating the Vegetarian and Dieters; age (p = 0.003) with over 20's representing a high proportion of the Omnivores; and time of day of transactions (p<0.001) with Dieters and Snackers purchasing least at breakfast. Many students (n = 474, 60.4%) changed dietary cluster across the semester.

This study demonstrates that transactional data presents a feasible method for dietary assessment, collecting detailed dietary information over time and at scale, while eliminating participant burden and possible bias from self-selection, observation and attrition. It revealed that student diets are complex and that simplistic measures of diet, focussing on narrow food groups in isolation, are unlikely to adequately capture dietary behaviours.