Authors: Elisabeth Titis*, Warwick Institute for the Science of Cities, University of Warwick, Rob Procter, Warwick Institute for the Science of Cities at the University of Warwick, Department of Computer Science at the University of Warwick, The Alan Turing Institute in London, Stephen A. Jarvis, Warwick Institute for the Science of Cities at the University of Warwick, Department of Computer Science at the University of Warwick, The Alan Turing Institute in London, Henry Crosby, Warwick Institute for the Science of Cities, University of Warwick
Topics: Spatial Analysis & Modeling, Urban and Regional Planning, Geographic Information Science and Systems
Keywords: Food deserts, geographic information system, agent-based modeling, diet-related ill-health
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Gallier A, Sheraton, 4th Floor
Presentation File: No File Uploaded
Considering the high costs of health problems in terms of both healthcare and lost productivity, regions of the country likely to be or become food deserts (FDs) have become increasingly important to public health. This research will investigate issues of FDs in the context of low-income, poor accessibility in terms of retail geography and diet-related ill-health, utilising agent-based modeling (ABM) to explore the emergent of FD environment and to build data model useful to policymakers when proposing policy interventions, such as introducing a junk food tax, store incentives or new healthful food stores in the FDs. In examining spatial inequalities, there has been little examination of the interdependencies across space and time that contribute to the creation of FDs (Rice 2012). Simulation models allow to simulate a theoretically realistic environment and generate synthetic data for evaluation of hypothetical policies in real time based on the feedback between incorporated variables; therefore, modelling efforts will be on examining these interdependencies across space, time and FD consequences. ABM and other simulation techniques have been used in health studies to examine income inequalities in diet in the context of residential segregation (Auchincloss et al. 2017). The model components will include characteristics of both physical (food access) and social environment, as well as several individual demographic and socioeconomic factors attributed to disparities in diet and health (e.g. race, income), with each factor continuously affecting the others. The model will provide greater insight into additional data for statistical research and new research areas for policy analysts.