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Investigate the Relationship Between Traumatic Occurrences and Socio-Economic Status Based on Geographic Information System (GIS): The Case of Qingpu in Shanghai, China

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Spatial Data and Intelligence (SpatialDI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13887))

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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.

H. Jin and H. Xia—Contributed equally to this work.

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Acknowledgements

We thank the editors and reviewers for their valuable comments. This work is partially supported by the projects funded by the Chongqing Natural Science Foundation (Grant Number: CSTB2022NSCQMSX2069) and the Ministry of Education of China (Grant Number: 19JZD023).

Author information

Authors and Affiliations

  1. Key Laboratory of Geographic Information Science (Ministry of Education) and School of Geographic Sciences, East China Normal University, Shanghai, 200241, China

    Huili Jin, Jing Wang & Xiang Li

  2. Department of Thoracic Surgery, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, 201700, China

    Hongwei Xia

  3. Department of Transportation and Geotechnical Engineering, University of Dar Es Salaam, Dar Es Salaam, Tanzania

    Joseph Mango

  4. Faculty of Economics and Management, East China Normal University, Shanghai, 200241, China

    Hong Yi

  5. Department of Radiology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, 201700, China

    Xiaoming Yu

  6. Chongqing Key Laboratory of Precision Optics, Chongqing Institute of East China Normal University, Chongqing, 404100, China

    Xiang Li

Authors
  1. Huili Jin
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  2. Hongwei Xia
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  3. Joseph Mango
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  4. Jing Wang
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  5. Hong Yi
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  6. Xiaoming Yu
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  7. Xiang Li
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Corresponding author

Correspondence to Xiang Li .

Editor information

Editors and Affiliations

  1. Renmin University of China, Beijing, China

    Xiaofeng Meng

  2. East Normal China University, Shanghai, China

    Xiang Li

  3. Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Jianqiu Xu

  4. Nanjing Normal University, Nanjing, China

    Xueying Zhang

  5. Jiangxi University of Finance and Economics, Nanchang, China

    Yuming Fang

  6. Huazhong University of Science and Technology, Wuhan, China

    Bolong Zheng

  7. Zhengzhou University, Zhengzhou, China

    Yafei Li

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Jin, H. et al. (2023). Investigate the Relationship Between Traumatic Occurrences and Socio-Economic Status Based on Geographic Information System (GIS): The Case of Qingpu in Shanghai, China. In: Meng, X., et al. Spatial Data and Intelligence. SpatialDI 2023. Lecture Notes in Computer Science, vol 13887. Springer, Cham. https://doi.org/10.1007/978-3-031-32910-4_10

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  • DOI: https://doi.org/10.1007/978-3-031-32910-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-32909-8

  • Online ISBN: 978-3-031-32910-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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