School of Finance, Actuarial Studies and Applied Statistics, College of Business and Economics, Australian National University, Canberra ACT 0200, Australia.
Environ Int. 2011 Apr;37(3):586-91. doi: 10.1016/j.envint.2010.12.002. Epub 2010 Dec 30.
The three-state (healthy, frail, and dead) population model is commonly used in time-series investigations of mortality displacement and particulate matter air pollution (PM). In this paper, the author proposes a new population model, called the mixture population model, that by allowing PM to have differential effects on individuals in the population, extends the population models currently used in investigations of mortality displacement. Using this new model, the properties of distributed lag models (DLM) of PM are investigated. In particular, the author derives a relationship between the parameters of the proposed population model and the estimates obtained from a DLM fitted to mortality arising from the model. This relationship provides insight into the interrelationships between the size of the frail population, the number of lags of PM included in a DLM and the proportion of the effect of PM on the healthy population that is estimable. The relationship will guide and contextualize future investigations by providing researchers with the knowledge to assess the consequences of the number of lags of PM included in a DLM in terms of what they can plausibly infer about the effect of PM on mortality based on this choice of lag.
三态（健康、虚弱和死亡）人口模型通常用于研究死亡率转移和颗粒物空气污染（PM）的时间序列。在本文中，作者提出了一种新的人口模型，称为混合人口模型，该模型通过允许 PM 对人口中的个体产生不同的影响，扩展了目前用于研究死亡率转移的人口模型。使用这个新模型，作者研究了 PM 的分布滞后模型（DLM）的性质。特别是，作者推导出了所提出的人口模型的参数与从适合于模型引起的死亡率的 DLM 中获得的估计值之间的关系。这种关系提供了对脆弱人群的大小、DLM 中包含的 PM 滞后数以及 PM 对健康人群的影响中可估计部分之间的相互关系的深入了解。该关系将为未来的研究提供指导和背景，使研究人员能够根据 DLM 中包含的 PM 滞后数评估他们根据这一滞后选择对 PM 对死亡率影响的合理推断的后果。
