The Impact of Unconventional Natural Gas Development on Maternal, Perinatal, and Childhood Health: an Electronic Health Record Approach

项目概要/摘要 最近的研究将非常规天然气开发与不良出生结果联系起来。的 特定风险因素的相对贡献，如相关的空气污染物，社会经济地位和孕产妇 然而，怀孕期间的健康状况仍然不清楚，联合国全球发展战略对儿童健康的影响也不清楚。 K99/R 00应用程序的目标是将宾夕法尼亚州的UNGD用作模型系统，因为它代表了 发出了一个快速，广泛的社会实验与化学和心理社会暴露，以及社区， 类型的变化-解开环境和社会共同暴露对孕产妇，新生儿和儿童的影响 健康拟议的项目将联合国性别问题司的活动与母亲的电子健康记录结合起来 通过问卷调查、被动空气采样器和地理信息系统收集的原始数据。EHR 数据特别适合环境健康研究，因为它们提供了廉价的访问， 关于大量和不同人群的纵向健康数据（即，在年龄、社会经济地位、种族和 地理）。需要相当多的后勤和分析技能来优化EHR数据的使用， 主要数据收集和完整的因果分析。K99旨在增强候选人的 先前的研究经验，通过课程，学徒在环境流行病学，并指导 阅读，并在以下方面进行了具体培训：（1）孕产妇和儿童健康;（2）EHR文本挖掘;（3）因果调解 分析;（4）原始数据收集;（5）共同暴露分析。在此期间获得的技能是 对于使用来自多个医疗保健系统的EHR数据进行环境epi的长期目标至关重要， 生物学研究贯穿整个生命过程，为环境决策提供信息。拟议研究 将利用Geisinger卫生系统的EHR数据，该数据提供了超过15，000个具有空间和 在时间上与宾夕法尼亚州的联合国全球发展司重叠。目标1（K99阶段）结合了文本挖掘策略和诊断 从EHR数据中提取母亲与怀孕相关的健康状况，然后应用因果推理的代码 评估妊娠相关高血压、妊娠期糖尿病、睡眠障碍、抑郁症和ANX的方法。 作为UNGD与足月出生体重和早产之间观察到的关联的中介。目的2 (K99阶段）通过问卷调查和环境空气样本收集飞行员慢性社会压力源的原始数据 盖辛格儿科病人就读的小学附近。R 00阶段建立在K99数据收集的基础上， 并跟踪初级保健婴儿，直到2021年（8-15岁），以评估类型和时间的关联 联合国全球发展司活动与哮喘诊断和急性呼吸道感染的关系。目标3-4（R 00阶段）开始至 解开儿童呼吸结果的环境和社会决定因素。建议AD- 穿着环境流行病学的后勤和分析挑战，并将为申请人做好准备， 独立的研究生涯。这项工作将评估环境和社会压力对健康的共同影响 在整个生命周期中，并在环境流行病学中提前使用EHR数据。

PROJECT SUMMARY/ABSTRACT Recent studies have linked unconventional natural gas development (UNGD) to adverse birth outcomes. The relative contributions of specific risk factors, such as related air pollutants, socioeconomic status, and maternal health during pregnancy, however, remain unclear, as do the consequences of UNGD for childhood health. The objective of this K99/R00 application is to use UNGD in Pennsylvania as a model system–because it repre- sents a rapid, widespread social experiment with chemical and psychosocial exposures and as well as communi- ty changes–to disentangle the effects of environmental and social co-exposures on maternal, neonatal, and child health. The proposed project will link UNGD activity to mothers' electronic health records (EHRs) in combination with primary data collected by questionnaires, passive air samplers, and geographic information systems. EHR data are particularly well suited for environmental health research because they provide inexpensive access to longitudinal health data on large and diverse populations (i.e., in terms of age, socioeconomic status, race, and geography). Considerable logistical and analytic skills are required to optimize use of EHR data, supplement it with primary data collection, and complete causal analyses. The K99 is designed to augment the candidate's prior research experience through coursework, apprenticeships in environmental epidemiology, and directed readings, with specific training in: (1) maternal and child health; (2) EHR text mining; (3) causal mediation analysis; (4) primary data collection; and (5) analysis of co-exposures. The skills gained during this award are critical to the long-term goal to use EHR data from multiple healthcare systems to conduct environmental epi- demiology studies across the lifecourse, in order to inform environmental policy-making. The proposed research will utilize Geisinger Health System's EHR data, which provides access to >15,000 births that have spatial and temporal overlap with UNGD in Pennsylvania. Aim 1 (K99 phase) combines text mining strategies and diagnosis codes to extract mothers' pregnancy-related health conditions from EHR data and then applies causal inference methods to evaluate pregnancy-related hypertension, gestational diabetes, sleep disorders, depression, and anx- iety as mediators of the observed associations between UNGD and term birth weight and preterm birth. Aim 2 (K99 phase) pilots primary data collection of chronic social stressors via questionnaires and ambient air samples near elementary schools attended by Geisinger pediatric patients. The R00 phase builds upon K99 data collec- tion and follows the primary care infants until 2021 (ages 8-15 years) to evaluate associations of types and timing of UNGD activity in relation to asthma diagnosis and acute respiratory infection. Aims 3-4 (R00 phase) begin to disentangle the environmental and social determinants of childhood respiratory outcomes. The proposal ad- dresses logistical and analytic challenges in environmental epidemiology and will prepare the applicant for an independent research career. This work will evaluate joint effects of environmental and social stressors on health across the lifespan and advance use of EHR data in environmental epidemiology.