Using moving total mortality counts to obtain improved estimates for the effect of air pollution on mortality.
Using moving total mortality counts to obtain improved estimates for the effect of air pollution on mortality.
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DOI：
10.1289/ehp.7774
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发表时间：
2005-09
影响因子：
10.4
通讯作者：
Roberts S
中科院分区：
文献类型：
--
作者：
Roberts S
在美国的许多城市，环境颗粒物空气污染（PM）的测量每6天才进行一次。在这些城市进行的调查死亡率和PM之间关系的时间序列研究仅限于使用一天的PM作为PM暴露的度量。这是不可取的，因为目前的证据表明，PM对死亡率的影响是在多天内传播的。研究表明，使用一天的PM作为PM暴露的衡量标准可能会导致估计值有很大的负偏差。在这篇文章中，我介绍了一个新的模型来估计PM的死亡率影响时，只有每六天PM数据。这个新模型使用每日死亡率时间序列中的可用信息来推断PM对死亡率影响的信息，否则会丢失超过一天的时间。与现有模型相比，这种新模型通常提供了统计估计精度和准确性的增加。
In many cities of the United States, measurements of ambient particulate matter air pollution (PM) are available only once every 6 days. Time-series studies conducted in these cities that investigate the relationship between mortality and PM are restricted to using a single day’s PM as the measure of PM exposure. This is undesirable because current evidence suggests that the effects of PM on mortality are spread over multiple days. And studies have shown that using a single day’s PM as the measure of PM exposure can result in estimates that have a large negative bias. In this article, I introduce a new model for estimating the mortality effects of PM when only every-sixth-day PM data are available. This new model uses information available in the daily mortality time series to infer otherwise lost information about the effect of PM on mortality over a period of more than a single day. This new model typically offers an increase in both statistical estimation precision and accuracy compared with existing models.
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影响因子：
10.4
作者：
Roberts, Steven
通讯作者：
Roberts, Steven
影响因子：
2.1
作者：
ITO, K;KINNEY, PL;THURSTON, GD
通讯作者：
THURSTON, GD
DOI：
10.1080/10473289.2005.10464620
发表时间：
2005-03-01
影响因子：
2.7
作者：
Roberts, S
通讯作者：
Roberts, S
影响因子：
5.4
作者：
Schwartz, J
通讯作者：
Schwartz, J
影响因子：
8.3
作者：
Ostro, BD;Hurley, S;Lipsett, MJ
通讯作者：
Lipsett, MJ