Spatial Analysis Methods for Health Promotion and Education

Abstract

This article provides a review of spatial analysis methods for use in health promotion and education research and practice. Spatial analysis seeks to describe or make inference about variables with respect to the places they occur. This includes geographic differences, proximity issues, and access to resources. This is important for understanding how health outcomes differ from place to place; and in terms of understanding some of the environmental underpinnings of health outcomes data by placing it in context of geographic location. This article seeks to promote spatial analysis as a viable tool for health promotion and education research and practice. Four more commonly used spatial analysis techniques are described in-text. An illustrative example of motor vehicle collisions in a large metropolitan city is presented using these techniques. The techniques discussed are as follows: descriptive mapping, global spatial autocorrelation, cluster detection, and identification and spatial regression analysis. This article provides useful information for health promotion and education researchers and practitioners seeking to examine research questions from a spatial perspective.