FoodDataQuest partner Tampere University, as part of UC4, has published a new study in Springer Nature titled “Uncovering food purchase behaviors and their shifts using Hidden Markov Modeling.” 

The study introduces a novel method for nutrition research by using Hidden Markov Models (HMMs) to analyze large, longitudinal food purchase datasets and track changes in food purchase behaviour over time, while also providing a practical methodological toolkit for future research using large-scale purchase data. 

Based on longitudinal purchase data from almost 30,000 Finnish consumers, the research shows that food purchasing behaviour is highly stable from month to month, with changes generally occurring between similar purchase rather than major shift. Food purchase behaviour also varied by age, gender, and family structure, with young adults and families with children showing greater flexibility in their purchasing behaviours. 

These insights will contribute to FoodDataQuest UC4 by helping transform food purchase data into more personalized, user-friendly feedback across different media, with aims of empowering consumers to make healthier and more sustainable choices. 

You can find the full article here. 
Information about article in Finnish: here