Local Modeling of U.S. Mortality Rates: A Multiscale Geographically Weighted Regression Approach

Kyran Cupido, A. Fotheringham, Petar Jevtic
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引用次数: 5

Abstract

The majority of work in mortality modeling involves factor-based approaches, with little use of information on the determinants and interpretable risk factors of mortality. At the same time, in the demographic community, there has been a lack of research attention towards the study of mortality from a spatial perspective. This work is a step towards addressing this, by providing an investigation of the presence of spatial variability in the determinants of mortality rates. Speci�?cally, by using the age-adjusted mortality rates of the counties of the contiguous United States, this research applies a multiscale geographically weighted regression (MGWR) approach to examine the spatial variations in the relationships between mortality rates and a diverse group of associated determinants. The results of this study demonstrate that the MGWR approach produces an interpretable and accurate account of the global, regional and local effects acting on the mortality rates of the United States. Thus, this work lays the groundwork for the consideration of spatial varying effects on mortality rates which operate at different spatial scales.
美国死亡率的局部建模:多尺度地理加权回归方法
死亡率建模的大部分工作涉及基于因素的方法,很少使用关于死亡率决定因素和可解释风险因素的信息。与此同时,在人口学界,对从空间角度研究死亡率的研究一直缺乏关注。通过对死亡率决定因素中存在的空间变异性进行调查,这项工作是朝着解决这一问题迈出的一步。Speci�?此外,通过使用美国相邻县的年龄调整死亡率,本研究采用多尺度地理加权回归(MGWR)方法来检查死亡率与各种相关决定因素之间关系的空间变化。这项研究的结果表明,MGWR方法对影响美国死亡率的全球、区域和地方影响作出了可解释和准确的说明。因此,这项工作为考虑在不同空间尺度上对死亡率的空间变化影响奠定了基础。
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