论文标题

死亡的社会空间因素:在香港贝叶斯死亡模型中分析地理空间分布变量的效果

The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong

论文作者

Alshaabi, Thayer, Dewhurst, David Rushing, Bagrow, James P., Dodds, Peter Sheridan, Danforth, Christopher M.

论文摘要

人类死亡率部分是多种社会经济因素的函数,它们在空间和时间上都不同。为了调整其他协变量,人类的寿命与家庭财富呈正相关。但是,地理区域中的死亡率在该地区及其邻国的社会经济因素的函数尚不清楚。关于这种关系的时间组成部分的信息也很少。作为一个案例研究,使用香港的多个人口普查几年,我们证明,财富指标变量与(a)富裕地区但受社会贫困地区与(b)富裕地区包围的富裕地区相邻但邻近的地区存在差异。我们还表明,与基线模型相比,每个人口普查年的包括空间分布变量的包含可降低死亡率预测的不确定性。我们的结果表明,地理死亡率模型应纳入非本地信息(例如,空间邻居),以降低其死亡率估计的差异,并指出对社会空间溢出对死亡率影响的更深入分析。

Human mortality is in part a function of multiple socioeconomic factors that differ both spatially and temporally. Adjusting for other covariates, the human lifespan is positively associated with household wealth. However, the extent to which mortality in a geographical region is a function of socioeconomic factors in both that region and its neighbors is unclear. There is also little information on the temporal components of this relationship. Using the districts of Hong Kong over multiple census years as a case study, we demonstrate that there are differences in how wealth indicator variables are associated with longevity in (a) areas that are affluent but neighbored by socially deprived districts versus (b) wealthy areas surrounded by similarly wealthy districts. We also show that the inclusion of spatially-distributed variables reduces uncertainty in mortality rate predictions in each census year when compared with a baseline model. Our results suggest that geographic mortality models should incorporate nonlocal information (e.g., spatial neighbors) to lower the variance of their mortality estimates, and point to a more in-depth analysis of sociospatial spillover effects on mortality rates.

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