Spatial Analysis of China Province-Level Perinatal Mortality
Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Tehran University of Medical Sciences
2016-05-01
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| Series: | Iranian Journal of Public Health |
| Subjects: | |
| Online Access: | https://ijph.tums.ac.ir/index.php/ijph/article/view/6797 |
| _version_ | 1818864640922222592 |
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| author | Kun XIANG Deyong SONG |
| author_facet | Kun XIANG Deyong SONG |
| author_sort | Kun XIANG |
| collection | DOAJ |
| description | Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality.
Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors.
Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors.
Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. |
| first_indexed | 2024-12-19T10:34:53Z |
| format | Article |
| id | doaj.art-d3735cf5382e4da2ba2d18e9b7429ab2 |
| institution | Directory Open Access Journal |
| issn | 2251-6085 2251-6093 |
| language | English |
| last_indexed | 2024-12-19T10:34:53Z |
| publishDate | 2016-05-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Iranian Journal of Public Health |
| spelling | doaj.art-d3735cf5382e4da2ba2d18e9b7429ab22022-12-21T20:25:39ZengTehran University of Medical SciencesIranian Journal of Public Health2251-60852251-60932016-05-014554903Spatial Analysis of China Province-Level Perinatal MortalityKun XIANG0Deyong SONG1The Research Center of Population, Resources and Environment, School of Economics, Huazhong University of Science and Technology, Wuhan, ChinaThe Research Center of Population, Resources and Environment, School of Economics, Huazhong University of Science and Technology, Wuhan, ChinaBackground: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions.https://ijph.tums.ac.ir/index.php/ijph/article/view/6797Perinatal mortalitySpatial dataSpatial autocorrelation |
| spellingShingle | Kun XIANG Deyong SONG Spatial Analysis of China Province-Level Perinatal Mortality Iranian Journal of Public Health Perinatal mortality Spatial data Spatial autocorrelation |
| title | Spatial Analysis of China Province-Level Perinatal Mortality |
| title_full | Spatial Analysis of China Province-Level Perinatal Mortality |
| title_fullStr | Spatial Analysis of China Province-Level Perinatal Mortality |
| title_full_unstemmed | Spatial Analysis of China Province-Level Perinatal Mortality |
| title_short | Spatial Analysis of China Province-Level Perinatal Mortality |
| title_sort | spatial analysis of china province level perinatal mortality |
| topic | Perinatal mortality Spatial data Spatial autocorrelation |
| url | https://ijph.tums.ac.ir/index.php/ijph/article/view/6797 |
| work_keys_str_mv | AT kunxiang spatialanalysisofchinaprovincelevelperinatalmortality AT deyongsong spatialanalysisofchinaprovincelevelperinatalmortality |