空气污染与健康:欧洲和北美的做法(APHENA)。

Klea Katsouyanni, Jonathan M Samet, H Ross Anderson, Richard Atkinson, Alain Le Tertre, Sylvia Medina, Evangelia Samoli, Giota Touloumi, Richard T Burnett, Daniel Krewski, Timothy Ramsay, Francesca Dominici, Roger D Peng, Joel Schwartz, Antonella Zanobetti
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引用次数: 0

摘要

前言:本报告提供了“空气污染与健康:欧洲和北美方法”项目的方法和研究结果。该项目的主要目的是了解关于北美和欧洲几个城市空气污染对死亡率和住院率影响的多城市时间序列研究结果之间的一致性程度。该项目包括对现有数据的并行和综合分析。研究人员试图了解不同研究的方法差异如何导致效果估计的差异,描述效果估计的异质性程度,并评估异质性的决定因素。空气污染与健康:一种欧洲方法(空气污染与健康:一种欧洲方法),其中包括欧洲的两个多城市项目。(一期[APHEA1]涉及15个城市,二期[APHEA2]涉及32个城市);(2)在美国90个最大城市进行的全国发病率、死亡率和空气污染研究(NMMAPS);(3)加拿大12个城市空气污染对健康影响的多城市研究。方法:该项目涉及对时间序列数据进行第一阶段和第二阶段分析的分析方法的初步开发,以及随后将所得方法应用于时间序列数据。关于第一阶段的分析,各调查小组对控制时间混淆和温度等关键问题使用了概念上类似的方法;然而,具体方法有所不同。因此,调查人员需要建立一个标准方案,但该方案将与先前的方法联系起来。基于探索性分析和模拟研究,开发了一种第一阶段的分析方案,该方案使用带有惩罚样条(PS)或自然样条(NS)的广义线性模型(GLM)来调整季节性,每年有3、8或12个自由度(df),以及通过最小化模型残差的部分自相关函数(PACF)选择的自由度数。对于住院数据,模型规范的方法遵循了用于死亡率的方法,考虑了季节性模式,但也考虑了周末和假期的影响,以及呼吸系统疾病的流行。还对数据进行了分析,以检测浓度-反应关系中的潜在阈值。第二阶段的分析采用汇集方法,并通过研究区域的社会人口特征和污染混合指标评估潜在的影响修正。还进行了具体的质量控制工作。对两种污染物的风险进行了估计:空气动力学直径为10 pm的颗粒物(PM10)和臭氧(O3)。结果:第一阶段的分析产生了对潜在平滑方法和自由度数量相对稳健的估计。第一阶段的APHENA结果通常重复了之前由三组研究者进行的独立分析。来自APHEA2和NMMAPS数据库的PM10对死亡风险估计的影响非常接近,而来自加拿大研究的估计则高得多。对于住院治疗,结果变化更大,在三个数据集之间没有可识别的变化模式。仅针对有每日污染数据的城市(即欧洲的22个城市和美国的15个城市)研究的PM10效应修正模式,在各中心并不完全一致。因此,欧洲和美国的污染物水平对影响的影响是不同的。气候变量只有在欧洲才重要。在欧洲和美国,研究人群中老年人比例较高与PM10风险估计值增加有关,失业率较高也是如此——失业率是所有数据集中统一可用的唯一社会经济地位指标。APHENA关于臭氧对死亡率影响的研究结果不如PM10的研究结果全面,因为来自三个地区的研究在分析全年数据或仅分析夏季数据方面存在差异。在欧洲和美国的夏季,这种影响往往更大。在美国,当对PM10进行控制时,它们的浓度更低。O3的估计影响因自由度和三个地理区域而异。在加拿大,臭氧对死亡率的影响更大,在任何地方都没有一致的影响改变的迹象。结论:APHENA已经表明,通过新的标准化分析获得的死亡率结果通常与早期研究中获得的结果相当,并且它们相对于所使用的数据分析方法是稳健的。 对于PM10,观察到的效应修正模式在欧洲和美国并不完全一致。对于O3,没有迹象表明在三个数据集中的任何一个都有强烈的效果改变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Air pollution and health: a European and North American approach (APHENA).

Introduction: This report provides the methodology and findings from the project: Air Pollution and Health: a European and North American Approach (APHENA). The principal purpose of the project was to provide an understanding of the degree of consistency among findings of multicity time-series studies on the effects of air pollution on mortality and hospitalization in several North American and European cities. The project included parallel and combined analyses of existing data. The investigators sought to understand how methodological differences might contribute to variation in effect estimates from different studies, to characterize the extent of heterogeneity in effect estimates, and to evaluate determinants of heterogeneity. The APHENA project was based on data collected by three groups of investigators for three earlier studies: (1) Air Pollution and Health: A European Approach (APHEA), which comprised two multicity projects in Europe. (Phase 1 [APHEA1] involving 15 cities, and Phase 2 [APHEA2] involving 32 cities); (2) the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), conducted in the 90 largest U.S. cities; and (3) multicity research on the health effects of air pollution in 12 Canadian cities.

Methods: The project involved the initial development of analytic approaches for first-stage and second-stage analyses of the time-series data and the subsequent application of the resulting methods to the time-series data. With regard to the first-stage analysis, the various investigative groups had used conceptually similar approaches to the key issues of controlling for temporal confounding and temperature; however, specific methods differed. Consequently, the investigators needed to establish a standard protocol, but one that would be linked to prior approaches. Based on exploratory analyses and simulation studies, a first-stage analysis protocol was developed that used generalized linear models (GLM) with either penalized splines (PS) or natural splines (NS) to adjust for seasonality, with 3, 8, or 12 degrees of freedom (df) per year and also the number of degrees of freedom chosen by minimizing the partial autocorrelation function (PACF) of the model's residuals. For hospitalization data, the approach for model specification followed that used for mortality, accounting for seasonal patterns, but also, for weekend and vacation effects, and for epidemics of respiratory disease. The data were also analyzed to detect potential thresholds in the concentration-response relationships. The second-stage analysis used pooling approaches and assessed potential effect modification by sociodemographic characteristics and indicators of the pollution mixture across study regions. Specific quality control exercises were also undertaken. Risks were estimated for two pollutants: particulate matter - 10 pm in aerodynamic diameter (PM10) and ozone (O3).

Results: The first-stage analysis yielded estimates that were relatively robust to the underlying smoothing approach and to the number of degrees of freedom. The first-stage APHENA results generally replicated the previous independent analyses performed by the three groups of investigators. PM10 effects on mortality risk estimates from the APHEA2 and NMMAPS databases were quite close, while estimates from the Canadian studies were substantially higher. For hospitalization, results were more variable without discernable patterns of variation among the three data sets. PM10 effect-modification patterns, explored only for cities with daily pollution data (i.e., 22 in Europe and 15 in the U.S.), were not entirely consistent across centers. Thus, the levels of pollutants modified the effects differently in Europe than in the United States. Climatic variables were important only in Europe. In both Europe and the United States, a higher proportion of older persons in the study population was associated with increased PM10 risk estimates, as was a higher rate of unemployment - the sole indicator of socioeconomic status uniformly available across the data sets. APHENA study results on the effects of O3 on mortality were less comprehensive than for PM10 because the studies from the three regions varied in whether they analyzed data for the full year or only for the summer months. The effects tended to be larger for summer in Europe and the United States. In the United States they were lower when controlled for PM10. The estimated effect of O3 varied by degrees of freedom and across the three geographic regions. The effects of O3 on mortality were larger in Canada, and there was little consistent indication of effect modification in any location.

Conclusions: APHENA has shown that mortality findings obtained with the new standardized analysis were generally comparable to those obtained in the earlier studies, and that they were relatively robust to the data analysis method used. For PM10, the effect-modification patterns observed were not entirely consistent between Europe and the United States. For O3, there was no indication of strong effect modification in any of the three data sets.

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