Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/77752
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Land Surveying and Geo-Informatics | - |
dc.creator | Zhao, P | - |
dc.creator | Kwan, MP | - |
dc.creator | Zhou, S | - |
dc.date.accessioned | 2018-08-28T01:34:33Z | - |
dc.date.available | 2018-08-28T01:34:33Z | - |
dc.identifier.issn | 1661-7827 | - |
dc.identifier.uri | http://hdl.handle.net/10397/77752 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Zhao, P.; Kwan, M.-P.; Zhou, S. The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou. Int. J. Environ. Res. Public Health 2018, 15, 308 is available at https | en_US |
dc.subject | Activity space | en_US |
dc.subject | Built environment | en_US |
dc.subject | Obesity | en_US |
dc.subject | Regression analysis | en_US |
dc.subject | UGCoP | en_US |
dc.title | The uncertain geographic context problem in the analysis of the relationships between obesity and the built environment in guangzhou | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 15 | - |
dc.identifier.issue | 2 | - |
dc.identifier.doi | 10.3390/ijerph15020308 | - |
dcterms.abstract | Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals’ activity space. First, a survey was conducted to collect individuals’ daily activity and weight information in Guangzhou in January 2016. Then, the data were used to calculate and compare the values of several built environment variables based on seven activity space delineations, including home buffers, workplace buffers (WPB), fitness place buffers (FPB), the standard deviational ellipse at two standard deviations (SDE2), the weighted standard deviational ellipse at two standard deviations (WSDE2), the minimum convex polygon (MCP), and road network buffers (RNB). Lastly, we conducted comparative analysis and regression analysis based on different activity space measures. The results indicate that significant differences exist between variables obtained with different activity space delineations. Further, regression analyses show that the activity space delineations used in the analysis have a significant influence on the results concerning the relationships between the built environment and obesity. The study sheds light on the UGCoP in analyzing the relationships between obesity and the built environment. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | International journal of environmental research and public health, Feb. 2018, v. 15, no. 2, 308, p. 1-20 | - |
dcterms.isPartOf | International journal of environmental research and public health | - |
dcterms.issued | 2018 | - |
dc.identifier.isi | WOS:000426721400133 | - |
dc.identifier.scopus | 2-s2.0-85042040356 | - |
dc.identifier.eissn | 1660-4601 | - |
dc.identifier.artn | 308 | - |
dc.description.validate | 201808 bcrc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Zhao_Uncertain_Geographic_Context.pdf | 2.49 MB | Adobe PDF | View/Open |
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