Roberts Steven, Switzer Paul
School of Finance and Applied Statistics Australian National University, Australia.
Inhal Toxicol. 2004 Dec 15;16(14):879-88. doi: 10.1080/08958370490519598.
Numerous time-series studies have investigated the association between daily mortality and daily ambient particulate air pollution concentrations (PM). The consensus from these studies is that increases in PM are associated with increases in daily mortality. However, it may be that increases in PM only hasten the deaths of individuals in a small, frail subset of the population whose longevity is short even in the absence of particulate air pollution. This hypothesis has been termed mortality displacement or harvesting. Distributed lag models (DLM) have been used to explore mortality effects of air pollution that are spread over multiple days, and DLM coefficients have been proposed as indicators of mortality displacement. We investigate statistical properties of DLM coefficients in the context of mortality displacement using simulation studies with frail population models. Our simulations use actual PM time series, as well as actual weather time series included as confounders. Our simulations show that DLM coefficients can have large bias when the mean lifetime of individuals in the frail subset of the population is more than a few weeks, and that the magnitude of this bias increases as the mean lifetime of individuals in the frail subset of the population increases. We conclude that DLM coefficients may be misleading as an indicator of mortality displacement, in the context of the frail population models that we explored.
众多时间序列研究调查了每日死亡率与每日环境空气中颗粒物污染浓度（PM）之间的关联。这些研究的共识是，PM的增加与每日死亡率的增加相关。然而，可能PM的增加仅会加速一小部分体弱人群的死亡，即使在没有颗粒物空气污染的情况下，这部分人群的寿命也很短。这一假设被称为死亡替代或收割效应。分布滞后模型（DLM）已被用于探究空气污染在多日期间的死亡效应，并且DLM系数已被提议作为死亡替代的指标。我们使用体弱人群模型的模拟研究，在死亡替代的背景下研究DLM系数的统计特性。我们的模拟使用实际的PM时间序列以及作为混杂因素纳入的实际气象时间序列。我们的模拟表明，当体弱人群子集中个体的平均寿命超过几周时，DLM系数可能会有很大偏差，并且随着体弱人群子集中个体平均寿命的增加，这种偏差的幅度也会增加。我们得出结论，在所探究的体弱人群模型背景下，DLM系数作为死亡替代的指标可能会产生误导。
