Understanding eating choices among university students: A study using data from cafeteria cashiers' transactions

To illustrate the use of automatically collected data from cashier transactions to understand eating habits among university students using cafeteria and to identify individual characteristics associated with the diverse behaviors.

The study was carried out at a large university located in Pisa, central Italy, using data about meals automatically recorded from cashier transaction meals during the academic year 2015-16 as well as data from the administrative archive of the university. A model-based clustering relying on multivariate beta distribution was used to cluster eating choices while multivariate multinomial logistic regressions were applied to identify variables associated to diverse clusters identified.

Considering 4643 students and about 200,000 meals consumed, results suggest that healthy eaters represented a minority (11.2 %) of the study population while the large part of students composed their meals combining grains with processed food or proteins (32.7 %) and limiting the choice of fruit (42.9 %). Male gender and younger age were associated with eating behavior not in line with recommendations for a healthy diet.

Eating choice resulted to be "compromised" in most of students and specific characteristics associated with unhealthy choice were also identified that can help inform and target specific policy. The use of routinely collected data gives the opportunity to both cafeterias and university to take an active role in policy development.