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空气污染与每日死亡之间的分布滞后。

The distributed lag between air pollution and daily deaths.

作者信息

Schwartz J

机构信息

Environmental Epidemiology Program, Harvard School of Public Health, Boston, MA 02115, USA.

出版信息

Epidemiology. 2000 May;11(3):320-6. doi: 10.1097/00001648-200005000-00016.

DOI:10.1097/00001648-200005000-00016
PMID:10784251
Abstract

Many studies have reported associations between air pollution and daily deaths. Those studies have not consistently specified the lag between exposure and response, although most have found associations that persisted for more than 1 day. A systematic approach to specifying the lag association would allow better comparison across sites and give insight into the nature of the relation. To examine this question, I fit unconstrained and constrained distributed lag relations to the association between daily deaths of persons 65 years of age and older with PM10 in 10 U.S. cities (New Haven, Birmingham, Pittsburgh, Canton, Detroit, Chicago, Minneapolis, Colorado Springs, Spokane, and Seattle) that had daily monitoring for PM10. After control for temperature, humidity, barometric pressure, day of the week, and seasonal patterns, I found evidence in each city that the effect of a single day's exposure to PM10 was manifested across several days. Averaging over the 10 cities, the overall effect of an increase in exposure of 10 microg/m3 on a single day was a 1.4% increase in deaths (95% confidence intervals (CI) = 1.15-1.68) using a quadratic distributed lag model, and a 1.3% increase (95% CI = 1.04-1.56) using an unconstrained distributed lag model. In contrast, constraining the model to assume the effect all occurs in one day resulted in an estimate of only 0.65% (95% CI = 0.49-0.81), indicating that this constraint leads to a substantial underestimate of effect. Combining the estimated effect at each day's lag across the 10 cities showed that the effect was spread over several days and did not reach zero until 5 days after the exposure. Given the distribution of sensitivities likely in the general population, this result is biologically plausible. I also found a protective effect of barometric pressure in all 10 locations.

摘要

许多研究报告了空气污染与每日死亡人数之间的关联。尽管大多数研究发现这种关联会持续超过1天,但这些研究并未始终明确暴露与反应之间的滞后时间。一种系统的方法来确定滞后关联将有助于更好地在不同地点之间进行比较,并深入了解这种关系的本质。为了研究这个问题,我对美国10个城市(纽黑文、伯明翰、匹兹堡、坎顿、底特律、芝加哥、明尼阿波利斯、科罗拉多斯普林斯、斯波坎和西雅图)65岁及以上人群的每日死亡人数与PM10之间的关联进行了无约束和约束分布滞后关系拟合,这些城市对PM10进行了每日监测。在控制了温度、湿度、气压、星期几和季节模式后,我在每个城市都发现有证据表明,单日暴露于PM10的影响会在几天内显现出来。对这10个城市进行平均,使用二次分布滞后模型,单日暴露量增加10微克/立方米的总体影响是死亡人数增加1.4%(95%置信区间(CI)=1.15 - 1.68),使用无约束分布滞后模型则是增加1.3%(95%CI = 1.04 - 1.56)。相比之下,将模型约束为假设所有影响都发生在一天内,结果估计仅为0.65%(95%CI = 0.49 - 0.81),这表明这种约束导致对影响的大幅低估。综合这10个城市在每个滞后日的估计影响表明,这种影响会持续几天,直到暴露后5天才降至零。考虑到一般人群中可能存在的敏感性分布,这一结果在生物学上是合理的。我还在所有10个地点发现了气压的保护作用。

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