Developing an Automated Toolkit for Health Studies-An Exploration Using a Geographical Information System

This study integrates two important spatial analytical techniques available within GIS, spatial clustering and spatial auto correlation to design an automated toolfor health professionals. This tool is a prototype that identifies hot-spots of obesity and then for each hot-spot it identifies the significant factors leading to obesity. It also allows a user to visualize the significant factors on a map of obesity hot-spots. Like many other health issues obesity is a chronic problem and is caused for a variety of reasons. Most studies that have utilized quantitative techniques to examine obesity have relied on statistical methods. Very few studies have used GIS in obesity studies and majority of such studies have used GIS for visualization purposes. Those studies that have gone beyond the visualization capabilities and have used analytical capabilities of GIS mainly focus on spatial clustering techniques. It is important to identify hot-spots of obesity but in order to effectively address the issue it is equally important to identify the factors responsible for obesity. The tool designed in this study addresses this two-pronged issue. This tool can be used by health professionals to address not just obesity but any other health related issue. Also, the automated tool designed in this study can be used with basic GIS and statistical background thereby minimizing the learning curve that act as a barrier to using spatial statistical capabilities of GIS.