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건강도시 구현을 위한 공간계획 및 정책방안 연구(Study on the spatial planning and public policies for creating a healthy city)

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  • 건강도시 구현을 위한 공간계획 및 정책방안 연구(Study on the spatial planning and public policies for creating a healthy city)
  • 김은정; 김현식; 이승복; 강민규
  • 국토연구원


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Title 건강도시 구현을 위한 공간계획 및 정책방안 연구(Study on the spatial planning and public policies for creating a healthy city)
Similar Titles
Material Type Reports
Author(Korean)

김은정; 김현식; 이승복; 강민규

Publisher

경기:국토연구원

Date 2010
ISBN 978-89-8182-756-4
Pages 237
Subject Country South Korea(Asia and Pacific)
Language Korean
File Type Link
Original Format pdf
Subject Social Development < Health
Holding 국토연구원

Abstract

During past few decades, not only public health scientists but also urban planners have concerned on the relationship between the built environment and health and have dedicated to understand the link between health and urban planning. Prevalence of obesity has reached an epidemic rate and increasing evidences suggest that the built environment has something to do with this trend. Moreover, unequal distribution of resources and services to support physical activity and healthy diet may contribute to increase obesity rates and to reduce health status. However, health is often attributed to differences in population characteristics, and is not clearly understood as a spatial phenomenon. The purpose of this study is to find built environmental correlates of obesity and health status and to suggest planning guideline of healthy cities.
This study consisted of literature reviews, case studies, empirical studies, survey, and political implication. As the literature reviews, it dealt with relevant theories, concepts, and cases. Moreover, this study reviewed the relationship between built environment and health.
For the empirical study, this tested the hypothesis that supportive built environments, with conditions to promote physical activity and healthy diet, would be associated with a lower obesity rates and/or a higher self-reported health status than environments with less supportive conditions. This study focused on the SMA(Seoul Metropolitan Ara) which specially offers a quite advantageous wetting for this study. It included areas with various levels of urbanization, including diverse rural communities.
The body of national longitudinal health data collected by the Centers for Disease Control and Prevention, called Korea National Health and Nutrition Examination Survey(KNHANES) Ⅲ, provides the individual-level health, behavioral, socio-demographic, perceived neighborhood environmental, and economic data for this study. The Korea Census Bureau provides group-level data including population density, percentage of population below poverty level, median income, and car ownership. Detailed parcel-level land use data were processed with Geographic Information System software to capture built environmental variables for both spatial units. These environmental variables covered all theoretically important constructs of land use and urban form potentially associated with health, physical activity and diet, including density, street block size, sidewalk, topography, land use mix, housing stock, and availability of particular land uses important for obesity and health, such as parks, gyms, grocery stores, and fast food restaurants.
This study used two different types of anlaytical scopes including regional-level and multi-level. As as preliminary study, regional(the city, country, or district)-level approach was used to measure the effects of built environment on obesity and self-reported health status. Hotspot analysis was used to identify the spatial aggregations of high obesity rate and low self0reported health status, and multiple regression models identified the environmental correlates of obesity and self-reported health status. Morans'I of obesity and self-reported health status were 0.2781 and -0.0413, respectively. It meant that built environments were correlates with regional obesity rates only. Results of multiple regression analysis showed that regional obesity rates were related with self-reported health status(-), number of fast food restaurants(+), and length of bicycle routes(-).