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Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

机译:心血管疾病流行病学研究的空间分析:系统的文献搜索

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Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study ( e.g. , rural, deprived neighbourhoods, etc. ), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources.
机译:心血管疾病(CVD)是现实世界中死亡和残疾的主要原因,对危险人群进行检测以及对脆弱地区的定位对于适当的流行病学管理至关重要。为空间分析而开发的技术,其中包括地理信息系统和空间统计信息,例如聚类检测和空间相关性,对于研究CVD的分布非常有用。这些技术能够识别不同地理研究水平的事件(例如,农村,贫困社区等),从而使CVD与周围环境中存在的因素相关联成为可能。这里介绍的系统性文献显示,这组疾病在发病率,死亡率和住院以及肥胖,吸烟,糖化血红蛋白水平升高,高血压身体活动和年龄等方面是聚集的。此外,获得的变量,如收入,居住权(农村或城市)和教育程度,也有助于CVD聚类。局部聚类检测和空间回归技术都对结果进行统计加权,从而通过指示需要干预的位置和可用资源的分配来提供有价值的信息,这些信息可以影响卫生服务中的响应机制。

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