Obesity; Spatial Accessibility and SEIFA Case Study: Greater Melbourne Area (GMA)

Abstract Today, the inequality of distribution of built environments leads to the formation of advantaged and disadvantaged neighborhoods. Advantage neighborhoods have good accessibility (Distance to) and availability (Number of) service centers. If the neighborhoods have some service centers that don’t provide healthy lifestyles, especially in increasing obesity, they can decline community health in these areas. So, this research tries to have a spatial view of obesity as a dependent variable. Independent variables are the number of and distance to food, smoking, and physical activity centers that are based on theoretical concepts. We analyzed them with dependent variables on SEIFA Clusters at SA2 level. This research has used spatial analysis methods such as BILISA Cluster on Local Moran I for clustering, GWR for spatial correlation which is a base of the analysis method. The results in the Great Melbourne Area (GMA) show that the level of accessibility is more important than availability and some SA2s in the low levels of SEIFA haven’t good access to a healthy built environment and which makes them more obese.