The importance of built environment : Characteristics of the built environment and spatial patterning of type 2 diabetes in pudong district, Shanghai

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The built environment encompasses the major physical spaces, including buildings, streets, homes, schools, parks, playgrounds and other infrastructure in which we live, work and play. In an ideal world, the built environment should support and promote physical activity across the lifespan. However, with increased mechanization and urbanization, physical inactivity and higher levels of chronic diseases such as obesity become common among urban residents. Pudong District covers an area of 1,210 square kilometers with 12 streets and 24 towns. With urbanization in China, it formed unique built environment that high levels of residential density and low-density township environment both exist in this District. Physical inactivity increases risk of chronic disease, this study examine relationships between built environment and chronic diseases using spatial models. We use gis-data to explore whether mixed land-use, high levels of street connectivity, and accessible facilities can reduce the incidence of urban residents' chronic diseases. The survey consists two parts: First, the public service facilities poi and road data are used to calculate the built environment feature in Pudong District. Second, the sample address information is re-encoded, and the spatial distribution characteristics of chronic disease patients are obtained through point density analysis of gis. We conduct follow analysis : 1) overlay analysis of high-density residential areas and high chronic disease incidence, to figure out whether supportive built environment may have lower prevalence of chronic disease. 2) Comparative analysis of the built environment characteristics between urban streets and township streets in Pudong District and the spatial distribution characteristics of chronic disease patients. Our analysis suggests there is an association between built environment and chronic disease.
health city, built environment, type 2 diabetes, gis, linear regression analysis