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

空气污染、生育力和流产的孕前队列研究

• 批准号: 9892011
• 负责人: ELIZABETH E HATCH
• 金额: $ 57.62万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9892011
• 关键词: Address; Affect; Air; Air Pollutants; Air Pollution; Canada; Cardiovascular system; Chemicals; Child; Clinical; Cohort Studies; Conceptions; Confounding Factors (Epidemiology); Couples; Data; Data Collection; Denmark; Enrollment; Environmental Hazards; Epidemiology; Etiology; Exposure to; Fertility; Follow-Up Studies; Foundations; Funding; Future; Geographic Information Systems; Geography; Grant; Gravid; Health; Human; Individual; Infertility; Interdisciplinary Study; Internet; Joints; Lead; Link; Literature; Low Birth Weight Infant; Measures; Medical; Modeling; Mothers; National Institute of Child Health and Human Development; Neighborhoods; Nitrogen Dioxide; North America; Online Systems; Outcome; Ozone; Participant; Particulate Matter; Pollution; Pre-Eclampsia; Predisposition; Pregnancy; Pregnancy loss; Pregnant Women; Premature Birth; Primary Prevention; Probability; Prospective Studies; Prospective cohort study; Proxy; Public Health; Questionnaires; Reproductive Health; Research Design; Retrospective Studies; Risk; Risk Factors; Sample Size; Spontaneous abortion; Statistical Methods; Techniques; Time; United States; Universities; Unsafe Sex; Washington; Woman; adverse pregnancy outcome; aged; base; child bearing; cohort; cost; cost effective; cost estimate; density; early pregnancy; ethnic diversity; fine particles; follow-up; health goals; high risk; improved; infertility treatment; insight; interest; modifiable risk; novel; particle; pollutant; pregnant; prospective; psychologic; recruit; reproductive; residence; software systems; spatiotemporal; stillbirth; subfertility; success; time-to-pregnancy; traffic-related air pollution

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.

抽象的 不育和自发堕胎（SAB）是重大的公共卫生问题，每种都会影响多达20％ 美国生殖时代的夫妇。随着夫妻越来越多地推迟到后来的生育 生殖年，许多人寻求不孕治疗，成功率相对较低，估计成本 每年50亿美元，与不良怀孕结局有关。因此，确定可修改的风险 不属性和SAB的因素是重要的公共卫生目标。空气污染对风险的潜在影响 副作用和SAB进行了研究。现有的少数人类研究具有重大局限性 回顾性研究设计，较小的研究规模，暴露和结果的次优评估，不足 控制潜在的混杂变量和有限的概括性。拟议的研究将评估 在两个相互关联的前瞻性队列中，几种空气污染物与少量和SAB的风险 北美和丹麦的研究。使用基于Web的招聘，数据收集和后续行动，我们有 招募了16,500多名企图怀孕的妇女，统称为最大的先选人群 研究与生育和SAB有关的因素进行了研究。我们已经收集了预期数据 怀孕，SAB，两个伴侣的潜在混杂因素以及基线和双月份的住宅地址 所有参与者的后续问卷，为准确的时变评估提供了基础 在整个祖先和怀孕早期期间，暴露于空气污染。我们的具体目的是 在病因学期间，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，在每个住宅周围的交通和道路密度的度量， 并分配适当的曝光时间变化估计。在18,500名妇女中，我们将检查 个人空气污染措施（PM2.5，NO2，O3和交通密度的度量）和 可闻性，构想的特定周期概率。我们将评估相同的空气污染措施 有SAB的风险。我们还将利用最先进的统计方法，包括预测性K-均值聚类， 检查污染物混合物的影响，重点是PM组件的形成。优势 该应用程序包括其庞大的研究规模，地理和种族多样的祖先的入学率 妊娠计划者队列，评估曾经的反复暴露措施和 怀孕早期，通过收集来控制个人级别和邻里级别的混淆 有关广泛协变量的数据，以及使用多污染物建模技术。本申请 在利用NICHD资助的已经建立的队列研究方面具有成本效益。拟议的研究 解决仅在空气方面的研究有限的新颖和重要的生殖健康结果 污染。研究结果可能会为不育和SAB的初级预防提供信息，并增加了所使用的证据 通过监管机构提高空气质量。