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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Tehran University of Medical Sciences
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935705/ https://www.ncbi.nlm.nih.gov/pubmed/27398334 |
Sumario: | 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. |
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