Improved use of routine data to assess and evaluate food environments
Improved use of routine data to assess and evaluate food environments (WSB WS2 WP1)
Research Team: Dr Tom Burgoine & Dr Heather Brown
Who's involved: University of Cambridge, Fuse, University of Bristol & LiLaC
June 2019 - May 2020
Mounting evidence links quantity and mix of high street food retailing, in particular, easy access to takeaway (‘fast-food’) outlets selling energy-dense, nutrient poor hot food for consumption off the premises, with socioeconomic inequalities, unhealthy diet. This science has direct links to policy through informing ‘healthy’ neighbourhood design. However, most evidence is cross-sectional and descriptive, limiting scope for causal inference. Longitudinal and quasi-experimental studies are rare. This is partly a reflection of insufficient or inadequate data pertaining to the neighbourhood food environment and locations of food outlets as environmental risk factors for diet and disease, over time.
The purpose of this project is to generate a longitudinal dataset of the food environment for use in research and food environment surveillance using data using the Food Standards Agency Food Hygiene Rating System (FHRS) food outlet database, which is available freely online. Our goal is for this new dataset to foster academic research, of direct relevance to policymakers, through ultimately enabling research on the effectiveness and cost-effectiveness of policies to modify the food environment. This new dataset will play a key decision-support role, assisting those in policy and practice roles within local and national government in making evidence-based decisions that contribute to public health improvement.
The aim of this project is to develop an understanding about online food ordering and delivery services. Across multiple work packages, how frequently online food ordering and delivery services are used and by whom, reasons for choosing this purchasing format, and the extent to which these services provide access to food and inequalities therein, will be explored.