Katsouyanni Klea, Samet Jonathan M, Anderson H Ross, Atkinson Richard, Le Tertre Alain, Medina Sylvia, Samoli Evangelia, Touloumi Giota, Burnett Richard T, Krewski Daniel, Ramsay Timothy, Dominici Francesca, Peng Roger D, Schwartz Joel, Zanobetti Antonella
Department of Hygiene and Epidemiology, University of Athens Medical School, Athens, Greece.
Res Rep Health Eff Inst. 2009 Oct(142):5-90.
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.
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).
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.
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.
本报告介绍了“空气污染与健康:欧洲和北美方法”(APHENA)项目的方法和研究结果。该项目的主要目的是了解北美和欧洲多个城市开展的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程度。该项目包括对现有数据的并行分析和综合分析。研究人员试图了解方法上的差异如何导致不同研究的效应估计值出现差异,确定效应估计值的异质性程度,并评估异质性的决定因素。APHENA项目基于三组研究人员为三项早期研究收集的数据:(1)“空气污染与健康:欧洲方法”(APHEA),该研究在欧洲包括两个多城市项目(第一阶段[APHEA1]涉及15个城市,第二阶段[APHEA2]涉及32个城市);(2)在美国90个最大城市开展的“国家发病率、死亡率与空气污染研究”(NMMAPS);(3)对加拿大12个城市空气污染健康影响的多城市研究。
该项目涉及为时间序列数据的第一阶段和第二阶段分析初步开发分析方法,随后将所得方法应用于时间序列数据。关于第一阶段分析,各个研究团队在控制时间混杂因素和温度的关键问题上采用了概念上相似的方法;然而,具体方法有所不同。因此,研究人员需要建立一个标准方案,但该方案要与先前的方法相关联。基于探索性分析和模拟研究,制定了第一阶段分析方案,该方案使用广义线性模型(GLM),采用惩罚样条(PS)或自然样条(NS)来调整季节性,每年有3、8或12个自由度(df),并且通过最小化模型残差的偏自相关函数(PACF)来选择自由度数量。对于住院数据,模型设定方法遵循死亡率数据的方法,考虑季节性模式,同时也考虑周末和假期效应以及呼吸道疾病流行情况。还对数据进行了分析以检测浓度 - 反应关系中的潜在阈值。第二阶段分析采用合并方法,并评估社会人口特征和研究区域内污染混合物指标对潜在效应修正的影响。还进行了特定的质量控制工作。对两种污染物进行了风险估计:空气动力学直径为10微米的颗粒物(PM10)和臭氧(O3)。
第一阶段分析得出的估计值对基础平滑方法和自由度数量相对稳健。APHENA第一阶段的结果总体上重现了三组研究人员先前进行的独立分析。APHEA2和NMMAPS数据库中PM10对死亡率风险估计的结果相当接近,而加拿大研究的估计值则高得多。对于住院情况,结果的变异性更大,三个数据集之间没有明显的变异模式。仅对有每日污染数据的城市(欧洲22个,美国15个)探索的PM10效应修正模式在各中心并不完全一致。因此,污染物水平在欧洲和美国对效应的修正方式不同。气候变量仅在欧洲很重要。在欧洲和美国,研究人群中老年人比例较高与PM10风险估计值增加相关,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O3对死亡率影响的研究结果不如PM10全面,因为三个地区的研究在分析全年数据还是仅夏季数据方面存在差异。在欧洲和美国,夏季的影响往往更大。在美国,当控制PM10时,O3的影响较低。O3的估计效应因自由度和三个地理区域而异。O3对死亡率的影响在加拿大更大,在任何地点都几乎没有一致的效应修正迹象。
APHENA表明,采用新的标准化分析得出的死亡率研究结果总体上与早期研究结果相当,并且对所使用的数据分析方法相对稳健。对于PM10,欧洲和美国观察到的效应修正模式并不完全一致。对于O3,在三个数据集中均未显示出强烈的效应修正迹象。