Abstract
Numerous incidences in the world have been occurring and causing trauma to humans. Trauma that can be physical or psychological causes not only great harms and deaths to patients but also huge burdens of expenses to the families and public health sectors for due to treatments in China. Many studies have been researching on this subject. However, such studies lack to provide comprehensive information on the relationships between trauma incidences and their occurring environment. This study used GIS and trauma patients’ data from Qingpu district in Shanghai to investigate the relationships between trauma incidences and their occurring environment. Such environments were studied in two levels of the socio-economic status (SES): Individual and sub-district. At the individual level, trauma incidences were studied with the housing prices, and at the sub-district level, were studied with the per capita disposable income in neighborhoods. We used descriptive and regression methods to count trauma incidences and analyze their relationships with SES. The results showed that trauma incidences are statistically negatively correlated with the the house prices and the per capita disposable income by the Pearson correlation coefficients of 0.71 and 0.72, respectively. The hot spot analyses showed that many trauma cases occurred in the Xiayang and Jinze streets as compared with other streets. When taken together, t These results provide a new baseline information that the researchers and health practitioners that could be used for learning and preparing effective measures for of mitigating and reducing trauma incidences and their resulting adverse impacts.
| Original language | English |
|---|---|
| Title of host publication | Spatial Data and Intelligence - 4th International Conference, SpatialDI 2023, Proceedings |
| Editors | Xiaofeng Meng, Xiang Li, Jianqiu Xu, Xueying Zhang, Yuming Fang, Bolong Zheng, Yafei Li |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 140-153 |
| Number of pages | 14 |
| ISBN (Print) | 9783031329098 |
| DOIs | |
| State | Published - 2023 |
| Event | 4th International Conference on Spatial Data and Intelligence, SpatialDI 2023 - Nanchang, China Duration: 13 Apr 2023 → 15 Apr 2023 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 13887 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 4th International Conference on Spatial Data and Intelligence, SpatialDI 2023 |
|---|---|
| Country/Territory | China |
| City | Nanchang |
| Period | 13/04/23 → 15/04/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- GIS
- Socio-economic status
- Trauma incidences
- Trauma patients
- house prices
- per capita disposable income
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