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首页> 外文期刊>BMC Public Health >Spatial analysis of gender variation in the prevalence of hypertension among the middle-aged and elderly population in Zhejiang Province, China
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Spatial analysis of gender variation in the prevalence of hypertension among the middle-aged and elderly population in Zhejiang Province, China

机译:浙江省中老年人群高血压患病率性别变化的空间分析

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Background Previous studies have shown that there may be gender disparities in the prevalence of hypertension; however, these studies do not address the spatial information contained in the sample which may limit the analytical results. Our study extends the existing Shared Component Model (SCM) and compares its utility with a logistic regression model to evaluate the significance of spatial information for identifying risk factors for hypertension and other non-rare diseases. Methods A total of 1267 residents aged 45?years of age and over were included in our study, of which 48.1?% were males. The overall prevalence of hypertension was 33.2?%, with females experiencing a higher prevalence than males (35.5?% vs. 30.6?%). The research variables included body mass index (BMI), Waist -to-Height Ratio (WHtR), smoking status, alcohol consumption etc. The extended SCM is employed to investigate regional gender variations in the risk of hypertension and assess the gender variation in the middle-aged and elderly populations of Zhejiang Province in eastern China and then its performance is compared with that of a traditional multiple logistic regression model. Results Our SCM analysis determined that the spatial pattern of hypertension risk for the middle-aged and elderly populations of Zhejiang Province in eastern China is quite different for males and females. Furthermore, Waist -to-Height Ratio (WHtR) continues to be a simple and effective predictor of hypertension risk for males at the regional level. Conclusions We believe that the extended SCM spatial model is a useful tool for identifying risk factors at the regional level.
机译:背景先前的研究表明,高血压的患病率可能存在性别差异。但是,这些研究并未针对样品中包含的空间信息,这可能会限制分析结果。我们的研究扩展了现有的共享组件模型(SCM),并将其效用与逻辑回归模型进行了比较,以评估空间信息对于识别高血压和其他非罕见疾病的危险因素的重要性。方法:本研究共纳入1267名年龄在45岁及以上的居民,其中男性占48.1%。高血压的总患病率为33.2%,女性患病率高于男性(35.5%对30.6%)。研究变量包括体重指数(BMI),腰围身高比(WHtR),吸烟状况,饮酒量等。扩展的SCM用于调查高血压风险中的区域性别差异并评估高血压的性别差异。然后将其在中国东部浙江省的中老年人群与传统多元logistic回归模型进行比较。结果我们的SCM分析确定,中国东部浙江省中老年人群的高血压风险空间格局在男性和女性之间存在很大差异。此外,腰高比(WHtR)仍然是区域一级男性高血压风险的简单有效预测指标。结论我们认为,扩展的SCM空间模型是识别区域性风险因素的有用工具。

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