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首页> 外文期刊>International Journal of Environmental Research and Public Health >Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China
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Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China

机译：深圳市高血压病住院收治的空间变化分析

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摘要

In China, awareness about hypertension, the treatment rate and the control rate are low compared to developed countries, even though China’s aging population has grown, especially in those areas with a high degree of urbanization. However, limited epidemiological studies have attempted to describe the spatial variation of the geo-referenced data on hypertension disease over an urban area of China. In this study, we applied hierarchical Bayesian models to explore the spatial heterogeneity of the relative risk for hypertension admissions throughout Shenzhen in 2011. The final model specification includes an intercept and spatial components (structured and unstructured). Although the road density could be used as a covariate in modeling, it is an indirect factor on the relative risk. In addition, spatial scan statistics and spatial analysis were utilized to identify the spatial pattern and to map the clusters. The results showed that the relative risk for hospital admission for hypertension has high-value clusters in the south and southeastern Shenzhen. This study aimed to identify some specific regions with high relative risk, and this information is useful for the health administrators. Further research should address more-detailed data collection and an explanation of the spatial patterns.
机译：在中国，尽管中国的老龄化人口在增长，特别是在那些城市化程度较高的地区，但与发达国家相比，他们对高血压，治疗率和控制率的认识仍然很低。然而，有限的流行病学研究试图描述中国城市地区高血压疾病的地理参考数据的空间变化。在这项研究中，我们应用了分层贝叶斯模型来探索2011年整个深圳高血压住院相对风险的空间异质性。最终的模型规范包括拦截和空间成分（结构化和非结构化）。尽管道路密度可以用作建模的协变量，但它是相对风险的间接因素。另外，利用空间扫描统计和空间分析来识别空间模式并绘制聚类图。结果表明，在深圳南部和东南部，高血压患者入院的相对风险具有高价值群。这项研究旨在确定一些具有较高相对风险的特定区域，该信息对于健康管理人员很有用。进一步的研究应针对更详细的数据收集和空间格局的解释。

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