Using Data Analytics to Understand Children's Food Choice Behaviour

Understanding children's food choice behaviour is critical to addressing the high levels of childhood obesity in the UK and elsewhere. Automatically collected food choice data provide a high quality, and voluminous source for investigating dietary patterns and can reveal valuable insights to how food decisions are made.
Some primary schools are beginning to utilise systems to register pupils' food selections from lunchtime menus. This now affords a unique opportunity to explore these emerging datasets in order to understand their potential, and what they can reveal about children's food choice behaviour.
This project will use food choice data across multiple schools and for full academic years. Food choice will be scrutinised with respect to available sociodemographic characteristics (such as school year group and free school meal entitlement), in order to investigate children's food choice patterns within a school food environment. This data-driven approach will look to inform food choice models and theory relating to children's food choice behaviour. There is scope to explore data-linkage to additional school-held pupil data (e.g. further student characteristics, attainment). In relation to this, logistical and other issues will be examined, in order to explore the possibilities of providing associative evidence of relationships between food choice and these student factors.
Working in collaboration with an external partner, SchoolGrid, this interdisciplinary project will demonstrate the potential of food choice data in primary schools. The intention is that findings will have policy and practice implications, and directly inform the design and delivery of future interventions to change children's food choice behaviour, thereby contributing towards improvements in children's dietary health.