Spatial Analysis of China Province-Level Perinatal Mortality
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Abstract
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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| Issue | Vol 45 No 5 (2016) | |
| Section | Original Article(s) | |
| Keywords | ||
| Perinatal mortality Spatial data Spatial autocorrelation | ||
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