ArticleInternational journal of environmental research and public health2014
Analysis of the spatial variation of hospitalization admissions for hypertension disease in Shenzhen, China.
Article in International journal of environmental research and public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Observational evidence for detrimental impact of inhaled ozone on human respiratory system.BMC public health · 2023Observational
- Measuring Spatial Patterns of Health Care Facilities and Their Relationships with Hypertension Inpatients in a Network-Constrained Urban System.International journal of environmental research and public health · 2019Article
- Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany.BMC public health · 2018Article
- Geographic clustering of emergency department presentations for acute coronary syndromes and heart failure in Alberta: a population-based study.CMAJ open · 2017Article
- Characteristics of Inpatient Hypertension Cases and Factors Associated with Admission Outcomes in Ashanti Region, Ghana: An Analytic Cross-Sectional Study.International journal of hypertension · 2017Article
- Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies.International journal of environmental research and public health · 2016Article
- Spatial analysis of the distribution, risk factors and access to medical resources of patients with hepatitis B in Shenzhen, China.International journal of environmental research and public health · 2014Article
- Spatio-temporal variation and prediction of ischemic heart disease hospitalizations in Shenzhen, China.International journal of environmental research and public health · 2014Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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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