A preconception cohort study of air pollution, fertility, and miscarriage

摘要 不孕不育和自然流产（SAB）是重大的公共卫生问题，每种问题都影响多达20%的人 美国的育龄夫妇。随着越来越多的夫妇推迟生育， 生育年，许多人寻求不孕症治疗，其成功率相对较低，估计费用 每年50亿美元，与不良妊娠结局有关。因此，识别可修改的风险 低生育力和SAB的因素是一个重要的公共卫生目标。空气污染对危险的潜在影响 低育性和SAB研究不足。现有的几项人类研究有很大的局限性， 回顾性研究设计，研究规模小，暴露和结局评估欠佳，不充分 控制潜在的混杂变量，以及有限的概括性。拟议的研究将评估 在两个相关的孕前前瞻性队列中几种空气污染物与生育力低下和SAB风险的关系 在北美和丹麦学习。使用基于网络的招聘，数据收集和后续行动，我们有 招募了超过16，500名试图怀孕的女性，共同组成了最大的孕前队列 关于生育和SAB相关因素的研究。我们收集了关于时间的前瞻性数据， 基线和每两个月一次时的妊娠、SAB、伴侣双方的潜在混杂因素和居住地址 对所有参与者进行后续调查问卷，为准确评估 在孕前和怀孕早期暴露于空气污染。我们的具体目标是 为感兴趣的病因时间段开发环境PM2.5、NO2和O3的时空模型，构建 使用地理信息系统软件测量每个住宅周围的交通和道路密度， 并分配适当的随时间变化的暴露估计值。在18，500名女性中，我们将检查 个别空气污染指标（PM2.5、NO2、O3和交通密度指标）之间的关联， 生育力，周期特定的受孕概率。我们将评估同样的空气污染措施 有SAB的风险。我们还将利用最先进的统计方法，包括预测k均值聚类， 研究污染物混合物的影响，重点是PM成分的形态。强度 该申请包括其大的研究规模、地理和种族多样性的先入为主的入组 妊娠计划者队列，评估孕前期间重复测量的暴露， 妊娠早期，通过收集对个人水平和社区水平的混淆进行出色的控制 广泛的协变量的数据，并使用多污染物建模技术。本申请 在利用NICHD资助的已建立的队列研究方面具有成本效益。拟定研究 解决了新的和重要的生殖健康结果，只有有限的研究，有关空气 污染研究结果可能为不孕症和SAB的一级预防提供信息，并增加使用的证据 通过监管机构来改善空气质量。

ABSTRACT Infertility and spontaneous abortion (SAB) are significant public health problems, each affecting up to 20% of reproductive-aged couples in the United States. As couples increasingly postpone childbearing to the later reproductive years, many seek infertility treatment, which has relatively low success rates, costs an estimated $5 billion per year, and is associated with adverse pregnancy outcomes. Therefore, identifying modifiable risk factors for subfertility and SAB is an important public health goal. The potential effects of air pollution on risk of subfertility and SAB are understudied. The few existing human studies have major limitations including retrospective study design, small study size, suboptimal assessment of exposure and outcome, inadequate control for potential confounding variables, and limited generalizability. The proposed study will assess the relation of several air pollutants to risk of subfertility and SAB in two interrelated preconception prospective cohort studies in North America and Denmark. Using web-based recruitment, data collection, and follow-up, we have enrolled over 16,500 women attempting pregnancy, collectively comprising the largest preconception cohort study ever conducted on factors related to fertility and SAB. We have collected prospective data on time-to- pregnancy, SAB, potential confounders in both partners, and residential addresses at baseline and on bi-monthly follow-up questionnaires for all participants, providing the foundation for accurate time-varying assessment of exposure to air pollution throughout the preconception and early pregnancy periods. Our specific aims are to develop spatio-temporal models of ambient PM2.5, NO2, and O3 for the etiologic time periods of interest, construct measures of traffic and roadway density around each residence using geographic information system software, and assign appropriate time-varying estimates of exposure. Among 18,500 women, we will examine the association between individual measures of air pollution (PM2.5, NO2, O3 and measures of traffic density) and fecundability, the cycle-specific probability of conception. We will evaluate the same measures of air pollution with risk of SAB. We will also utilize state-of-the-art statistical methods, including predictive k-means clustering, to examine the effects of pollutant mixtures, with an emphasis on speciation of PM components. Strengths of this application include its large study size, preconception enrollment of a geographically and ethnically diverse cohort of pregnancy planners, assessment of repeated measures of exposure during the preconception and early pregnancy periods, excellent control for individual-level and neighborhood-level confounding via collection of data on a wide range of covariates, and the use of multi-pollutant modeling techniques. The present application is cost-effective in leveraging already-established cohort studies funded by the NICHD. The proposed study addresses novel and important reproductive health outcomes that have had only limited study in relation to air pollution. Study results are likely to inform primary prevention of infertility and SAB, and add to evidence used by regulators to improve air quality.