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Mapping gender variation in the spatial pattern of alcohol-related mortality: A Bayesian analysis using data from South Yorkshire, United Kingdom

机译:绘制与酒精相关的死亡率的空间格局中的性别变异:使用来自英国南约克郡的数据进行的贝叶斯分析

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Gender variation in the spatial pattern of alcohol-related deaths in South Yorkshire, UK for the period 1999 and 2003 was explored using two Bayesian modelling approaches. Firstly, separate models were fitted to male and female deaths, each with a fixed effect deprivation covariate and a random effect with unstructured and spatially structured terms. In a modification to the initial models, covariates were assumed estimated with error rather than known with certainty. In the second modelling approach male and female deaths were modelled jointly with a shared component for random effects. A range of different unstructured and spatially structured specifications for the shared and gender-specific random effects were fitted. In the best fitting shared component model a spatially structured prior was assumed for the shared component, while gender-specific components were assumed unstructured. Deprivation coefficients and random effect standard deviations were very similar between the gender-specific and shared component models. In each case the effect of deprivation was observed to be greater in males than in females, and slightly larger in the measurement error models than in the fixed covariate models. Greater variation was observed in the spatially smoothed estimates of risk for males versus females in both gender-specific and shared component models. The shared component explained a greater proportion of the male risk than it did the female risk. The analysis approach reveals the residual (unexplained by deprivation) gender-specific and shared risk surfaces, information which may be useful for guiding public health action.
机译:使用两种贝叶斯建模方法研究了英国南约克郡1999年和2003年酒精相关死亡的空间格局中的性别差异。首先,分别针对男性和女性死亡分别拟合模型,每个模型具有固定效应剥夺协变量和具有非结构化和空间结构化术语的随机效应。在对初始模型的修改中,假设协变量估计有误差,而不是确定地知道。在第二种建模方法中,将男性和女性死亡与共享组件共同建模以产生随机效应。拟合了一系列不同的非结构化和空间结构化规范,以实现共享和特定于性别的随机效应。在最合适的共享组件模型中,假定共享组件具有空间结构先验,而特定性别组件则假定为非结构化。性别特定和共享成分模型之间的剥夺系数和随机效应标准偏差非常相似。在每种情况下,观察到剥夺的影响在男性中都大于女性,而在测量误差模型中则比固定协变量模型稍大。在针对性别和共享成分模型中,男性和女性的风险风险在空间平滑估计中观察到更大的差异。共同构成部分解释了男性风险比女性风险更大的比例。分析方法揭示了残留的(无法解释的)性别特定和共同的风险面,这些信息可能对指导公共卫生行动有用。

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