Using Spatial Aggregation Method outcome to explain the influences of built environment on health profile
| dc.contributor.author | Shen, Yuanyi | |
| dc.contributor.author | Zhong, Mengqi | |
| dc.contributor.author | Zhang, Qingla | |
| dc.contributor.author | Bu, Jiatian | |
| dc.contributor.author | Yu, Yifan | |
| dc.date.accessioned | 2023-07-28T07:22:15Z | |
| dc.date.available | 2023-07-28T07:22:15Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Health profile is becoming more significant in Developing country such as China. Research into the effects of the built environment on health has increased dramatically in recent years. Researchers are trying to understand and research explores the role of the built environment and transport system on an individual's health. Data from recent reviews have shown associations between environmental features, such as presence of sidewalks, proximity to parks and presence of certain types of food outlets, and outcomes such as physical activity. However, results from many studies conducted have been non-significant. A primary cause of these non-significant is due to how neighborhood areas are defined, which directly affects how the built environment variables are calculated in geographic information systems. In this paper tests to what extent the potential impacts on regression analysis resulting from different data aggregation methods are well documented in spatial studies by varying the initial geographical scale of analysis which is primarily referred to as the modifiable aerial unit problem. As explained earlier, the focus is on reducing the error caused by the modifiable aerial unit problem by introducing a data aggregation method. Individual health and lifestyle data are obtained from the survey of income, and labor dynamics in census figures of China, and the relationship between the built environment and health profile is evaluated by using a discrete choice model. The intended results is identify which variable is more closely related to health status by the proposed aggregation method is evaluated across three spatial scales | |
| dc.description.version | publishedVersion | |
| dc.identifier.isbn | 978-88-99243-93-7 | |
| dc.identifier.pageNumber | 2466-2472 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14235/392 | |
| dc.language.iso | en | |
| dc.publisher | AESOP | |
| dc.source | Planning for Transition – book of proceedings 31; 2 | en |
| dc.subject | built environment | |
| dc.subject | spatial | |
| dc.subject | geographic | |
| dc.subject | health profile | |
| dc.subject | regression analysis | |
| dc.title | Using Spatial Aggregation Method outcome to explain the influences of built environment on health profile | |
| dc.type | Article |