Qian Zhengmin, Zhang Bin, Liang Shengwen, Wang Jing, Yang Shaoping, Hu Ke, Trevathan Edwin, Yang Rong, Li Qijie, Flick Louise H, Hu Ronghua, Huang Zhen, Zhang Yimin, Hu Shixiang, Wang Jing, Shen Longjiao, Lu Yuan, Peng Hui, Yu Yuzhen, Yang Li, Chen Wei, Liu Wenjin, Zhang Wei
Res Rep Health Eff Inst. 2016 Sep(189):1-65.
Several recent studies have suggested that maternal exposures to air pollution and temperature extremes might contribute to low birth weight (LBW), preterm birth (PTB), and other outcomes that can adversely affect infant health. At the time the current study began, most other studies had been conducted in the United States or Europe. Dr. Zhengmin Qian proposed to extend work he had done on ambient particulate air pollution and daily mortality in Wuhan, China (Qian et al. 2010), as part of the HEIsponsored Public Health and Air Pollution in Asia program, to study adverse birth outcomes. Wuhan is the capital city of Hubei province, has a large population of about 6.4 million within the urban study area, experiences temperature extremes, and generally has higher air pollution levels than those observed in the United States and Europe, thus providing a good opportunity to explore questions about air pollution and health.
Qian and colleagues planned a cohort and nested case–control design with four specific aims, examining whether increased exposures to air pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) during vulnerable pregnancy periods were associated with increased rates of PTB, LBW (<2500 g), or intrauterine growth retardation (IUGR, defined as having a birth weight below the 10th percentile of singleton live births in Wuhan) after adjusting for major risk factors and whether the associations were confounded by copollutant exposures, affected by residual confounding, or modified by temperature extremes, socioeconomic status (SES), or secondhand smoke (SHS) exposure. The cohort study included 95,911 births that occurred from June 10, 2011, to June 9, 2013, and met typical prespecified inclusion criteria used in other birth outcome studies. The case–control study included 3146 cases (PTB, LBW, or both, but not IUGR) and 4263 controls (matched to the cases by birth month) for whom investigators were able to complete home visits and questionnaires. The investigators obtained air pollution and daily weather data for August 2010 to June 2013 from nine monitoring stations representing background air pollution sites in seven Wuhan inner-city districts. Only two of these stations provided PM2.5 data. For the cohort study, the investigators assigned exposures to mothers according to the daily mean concentrations from the monitor nearest the residential community in which the mother lived at the time of the birth. For the case–control study, they assigned exposures based on the inverse distance weighted average of daily mean concentrations from the three nearest monitors, for all but PM2.5 for which the method was not specified. They also collected data on various factors that might confound or modify the impact of the pollutants on the adverse outcomes, including data collected in the cohort from mothers at the time of delivery and, in the case–control study, from questionnaires administered to mothers. In the case–control study, covariates representing SES (as indicated by the mother’s educational attainment and household income) and SHS exposures were of particular interest. The primary statistical analyses of the pollutant associations with PTB, LBW, and IUGR were conducted using logistic regression models. In the cohort study, exposures during the pregnancy period of interest (full term, trimesters, and selected months) were included as continuous variables. In the case–control study, the exposures were modeled as binary variables (i.e., above or below the median pollutant concentrations). Numerous sensitivity analyses were conducted.
Although originally planning a nested case–control study, the investigators encountered challenges that led them to analyze the cohort and case–control studies using different ways of assigning exposures and characterizing them in their statistical models. These decisions precluded direct comparisons between the sets of results, making it difficult to answer the questions about residual confounding that nested case–control studies are designed to answer. The odds ratios from the two study designs using different exposures also have different interpretations. Still, one can ask whether the sets of findings were qualitatively consistent with each other or with those of similar studies. There were some similarities. Both studies suggested that increased PM(2.5), PM(10), CO, and O(3) exposures over the full pregnancy were associated with small increases in the odds of PTB (the case–control study also showed an association with NO2) and that increased PM(2.5) exposures were associated with significantly increased odds of LBW. However, most of the other pollutants had no effect on LBW, except CO in the cohort study and O(3) in the case–control study, both of which increased the odds of LBW. The exposures over the entire pregnancy were generally associated with decreased odds of IUGR. Adjustments for potential confounders were greatest for the delivery covariates. The investigators found no systematic association of any of these outcomes with particular trimesters or months, another result that differed from those of some other studies. They found little evidence that their main results were confounded or modified by the presence of copollutants, although with the exception of O3, most of the pollutants were highly correlated, making it difficult to disentangle the effects of individual pollutants. Could the two sets of data be analyzed in a more comparable way, as in a standard nested case–control study? At the Committee’s request, the investigators reanalyzed the case–control data using the same exposures and models as in the cohort study. The results were strikingly different from those using the inverse distance weighted exposures, modeled as binary variables — the pollutants had either no effect or an apparent beneficial effect on PTB and LBW. The Committee was not convinced by the explanations offered for these differences, leaving the reasons for them unresolved.
This study set out to answer important questions about the effects of air pollution exposure on three measures of adverse birth outcomes — LBW, PTB, and IUGR — in a large cohort of mothers and newborns in Wuhan, China. Given the cohort size, high pollution levels and temperatures, and detailed covariate data, the investigators were well poised to address these questions. They sought to pattern their work on other studies of birth outcomes, were very responsive to Committee questions, and provided many additional analyses and explanations. In the Committee’s view, however, the study was unable to address with confidence several of its specific aims. Most important, the differences in results when the case–control data were analyzed with different exposure metrics remain unexplained, raising concerns about the ability to draw conclusions from subsequent analyses assessing residual confounding and effect modification by temperature extremes, SES, and SHS exposure. Consequently, any individual findings from the cohort and case–control studies should be considered suggestive rather than conclusive, and should be interpreted carefully together.
近期的多项研究表明，孕期接触空气污染和极端温度可能会导致低出生体重（LBW）、早产（PTB）以及其他可能对婴儿健康产生不利影响的后果。在本研究开始时，大多数其他研究是在美国或欧洲进行的。钱正民博士提议将他在中国武汉开展的关于环境颗粒物空气污染与每日死亡率的研究（Qian等人，2010年）进行扩展，作为健康效应研究所资助的亚洲公共卫生与空气污染项目的一部分，以研究不良出生结局。武汉是湖北省省会，城市研究区域内人口众多，约640万，经历极端温度，且空气污染水平总体高于美国和欧洲，因此为探讨空气污染与健康问题提供了良好契机。
钱博士及其同事计划采用队列研究和嵌套病例对照设计，有四个具体目标，即研究在调整主要风险因素后，孕期易受影响阶段接触空气污染物（PM2.5、PM10、SO2、NO2、O3和CO）增加是否与PTB、LBW（<2500克）或宫内生长受限（IUGR，定义为出生体重低于武汉单胎活产第10百分位数）发生率增加相关，以及这些关联是否受到共污染物暴露的混杂、残余混杂的影响，或是否因极端温度、社会经济地位（SES）或二手烟（SHS）暴露而改变。队列研究纳入了2011年6月10日至2013年6月9日期间发生的95911例出生病例，这些病例符合其他出生结局研究中常用的典型预设纳入标准。病例对照研究包括3146例病例（PTB、LBW或两者皆有，但不包括IUGR）和4263例对照（按出生月份与病例匹配），研究人员能够对这些对象完成家访并进行问卷调查。研究人员从代表武汉七个内城区背景空气污染站点的九个监测站获取了2010年8月至2013年6月的空气污染和每日天气数据。其中只有两个站点提供PM2.5数据。对于队列研究，研究人员根据出生时母亲居住社区最近监测站的每日平均浓度为母亲分配暴露量。对于病例对照研究，除未明确说明方法的PM2.5外，他们根据三个最近监测站每日平均浓度的反距离加权平均值为对象分配暴露量。他们还收集了可能混杂或改变污染物对不良结局影响的各种因素的数据，包括队列研究中母亲分娩时收集的数据，以及病例对照研究中通过对母亲进行问卷调查收集的数据。在病例对照研究中，代表SES（由母亲的教育程度和家庭收入表示）和SHS暴露的协变量特别受关注。使用逻辑回归模型对污染物与PTB、LBW和IUGR的关联进行了主要统计分析。在队列研究中，感兴趣的孕期（足月、各孕期和选定月份）的暴露量作为连续变量纳入。在病例对照研究中，暴露量被建模为二元变量（即高于或低于污染物浓度中位数）。进行了大量敏感性分析。
尽管最初计划进行嵌套病例对照研究，但研究人员遇到了一些挑战，导致他们以不同的方式分配暴露量并在统计模型中对其进行表征，从而对队列研究和病例对照研究进行分析。这些决策排除了两组结果之间的直接比较，使得难以回答嵌套病例对照研究旨在回答的关于残余混杂的问题。使用不同暴露量的两种研究设计的优势比也有不同的解释。不过，人们可以询问这两组研究结果在定性上是否相互一致，或者是否与类似研究的结果一致。存在一些相似之处。两项研究均表明，整个孕期PM(2.5)、PM(10)、CO和O(3)暴露增加与PTB几率略有增加相关（病例对照研究还显示与NO2有关联），且PM(2.5)暴露增加与LBW几率显著增加相关。然而除队列研究中的CO和病例对照研究中的O(3)均增加LBW几率外，大多数其他污染物对LBW无影响。整个孕期的暴露通常与IUGR几率降低相关。对潜在混杂因素的调整在分娩协变量方面最为显著。研究人员发现这些结局与特定孕期或月份之间没有系统性关联，这一结果也与其他一些研究不同。他们几乎没有发现证据表明其主要结果受到共污染物存在的混杂或改变，不过除O3外，大多数污染物高度相关，使得难以区分单个污染物的影响。能否像在标准嵌套病例对照研究中那样，以更具可比性的方式分析这两组数据？应委员会要求，研究人员使用与队列研究相同的暴露量和模型重新分析了病例对照数据。结果与使用反距离加权暴露量建模为二元变量时的结果截然不同——污染物对PTB和LBW要么没有影响，要么有明显的有益影响。委员会对为这些差异提供的解释并不信服，这些差异的原因仍未得到解决。
本研究旨在回答关于空气污染暴露对中国武汉一大群母亲和新生儿的三种不良出生结局指标——LBW、PTB和IUGR——影响的重要问题。鉴于队列规模、高污染水平和温度以及详细的协变量数据，研究人员有充分条件解决这些问题。他们试图以其他出生结局研究为模式开展工作，对委员会的问题反应非常迅速，并提供了许多额外的分析和解释。然而，在委员会看来，该研究无法自信地实现其几个具体目标。最重要的是，用不同暴露指标分析病例对照数据时结果存在差异，这一点仍无法解释，这引发了人们对后续评估残余混杂以及极端温度、SES和SHS暴露导致的效应改变的分析能否得出结论的担忧。因此，队列研究和病例对照研究的任何个别发现都应被视为具有启发性而非结论性的，并且应一起仔细解读。
