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Analysis of the spatial variation of hospitalization admissions for hypertension disease in Shenzhen, China.

Wang Z, Du Q, Liang S, Nie K, Lin DN, Chen Y, Li JJ - Int J Environ Res Public Health (2014)

Bottom Line: In addition, spatial scan statistics and spatial analysis were utilized to identify the spatial pattern and to map the clusters.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.

View Article: PubMed Central - PubMed

Affiliation: School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China. wangzhens@whu.edu.cn.

ABSTRACT
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.

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Related in: MedlinePlus

A map of China showing the location of Shenzhen.
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ijerph-11-00713-f001: A map of China showing the location of Shenzhen.

Mentions: Shenzhen is a major city in the south of Southern China’s Guangdong Province, and it is situated immediately north of Hong Kong (Figure 1 and Figure 2). Since late 1979, this area has become one of the most successful Special Economic Zones in China and is considered one of the fastest-growing cities in the World. The total annual investment in medical and health in 2008 was 3.3 billion Yuan, and this investment reached almost 7.9 billion Yuan in 2011 [34].


Analysis of the spatial variation of hospitalization admissions for hypertension disease in Shenzhen, China.

Wang Z, Du Q, Liang S, Nie K, Lin DN, Chen Y, Li JJ - Int J Environ Res Public Health (2014)

A map of China showing the location of Shenzhen.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3924470&req=5

ijerph-11-00713-f001: A map of China showing the location of Shenzhen.
Mentions: Shenzhen is a major city in the south of Southern China’s Guangdong Province, and it is situated immediately north of Hong Kong (Figure 1 and Figure 2). Since late 1979, this area has become one of the most successful Special Economic Zones in China and is considered one of the fastest-growing cities in the World. The total annual investment in medical and health in 2008 was 3.3 billion Yuan, and this investment reached almost 7.9 billion Yuan in 2011 [34].

Bottom Line: In addition, spatial scan statistics and spatial analysis were utilized to identify the spatial pattern and to map the clusters.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.

View Article: PubMed Central - PubMed

Affiliation: School of Resource and Environmental Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China. wangzhens@whu.edu.cn.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus