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[2000年至2010年巴西圣保罗州肥胖和高血压所致疾病空间分布关系分析]

[Analysis of the relation between the spatial distribution of morbidities due to obesity and hypertension for the State of São Paulo, Brazil, from 2000 to 2010].

作者信息

Cunha E Silva Darllan Collins da, Lourenço Roberto Wagner, Cordeiro Ricardo Carlos, Cordeiro Maria Rita Donalisio

出版信息

Cien Saude Colet. 2014 Jun;19(6):1709-19. doi: 10.1590/1413-81232014196.15002013.

Abstract

The increased prevalence of obesity in many countries in the last decade has resulted in increased morbidity and mortality from hypertension and associated complications. The objective of this work is to analyze the spatial distribution of obesity and hypertension in the state of São Paulo in the period from 2000 to 2010, based on hospital records and admissions from the Hospital Information System of the Unified Health System (HIS - SUS). Coefficients were used for the prevalence of the disease in each municipality averaged out by the empirical Bayesian method, enabling visualization of the spatial pattern of these morbidities in the state. The spatial dependence of these standards was assessed by checking the autocorrelation between the indicators by calculating Moran's Index of Spatial Autocorrelation. Furthermore, the positive correlation (Pearson) between obesity and hypertension was investigated. Data and maps showed clusters of 87 municipalities where there are higher and lower prevalence of hypertension and obesity in the location with marked autocorrelation between neighboring municipalities. The Pearson correlation coefficient found for these municipalities was 0.404 and suggests an association between the morbidities. The spatial analysis techniques proved useful for planning public health actions.

摘要

过去十年中,许多国家肥胖症患病率上升,导致高血压及相关并发症的发病率和死亡率增加。本研究的目的是基于统一卫生系统医院信息系统(HIS - SUS)的医院记录和入院数据,分析2000年至2010年期间圣保罗州肥胖症和高血压的空间分布情况。采用经验贝叶斯方法计算每个市疾病患病率的系数,从而能够直观呈现该州这些疾病的空间分布模式。通过计算空间自相关的莫兰指数来检验指标之间的自相关性,以此评估这些标准的空间依赖性。此外,还研究了肥胖症与高血压之间的正相关关系(皮尔逊相关性)。数据和地图显示,在87个市形成了集群,这些市高血压和肥胖症的患病率较高和较低,且相邻市之间存在明显的自相关性。这些市的皮尔逊相关系数为0.404,表明这两种疾病之间存在关联。空间分析技术被证明对规划公共卫生行动很有用。

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