Project 1: Effect of Multi-Level Environmental Exposure on Birth Outcomes

项目1：多层次环境暴露对出生结果的影响

基本信息

批准号：
8215032
负责人：
Ira B Tager
金额：
$ 3.09万
依托单位：
UNIVERSITY OF CALIFORNIA BERKELEY
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-02-01 至 2013-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8215032
关键词：
Adult Adverse effects Air Air Pollution Asthma Autistic Disorder Birth Birth Certificates Birth Weight California Censuses Characteristics Chemicals Child Child health care Childhood Communities Coronary heart disease Data Data Set Environmental Exposure Environmental Health Environmental Risk Factor Epigenetic Process Exposure to Funding Genetic Genetic Polymorphism Geographic Locations Grant Health Impairment Individual Influentials Investigation Joints Life Literature Low Birth Weight Infant Malignant Neoplasms Metabolic Diseases Methods Modeling Monitor Mothers National Institute of Environmental Health Sciences Nature Neighborhoods Obesity Outcome Outcome Study Particulate Particulate Matter Plague Predisposition Premature Birth Research Research Design Risk Risk Factors Saliva Sampling Simulate Specimen Statistical Methods Subgroup Time United States air monitoring autism spectrum disorder cohort cost density design genetic analysis improved low socioeconomic status novel particle pollutant prenatal programs pulmonary function socioeconomics trafficking

项目摘要

The primary data for Project 1 will come from an R21 funded by NIEHS (R21 ES 014891-01A1, Influences of genetics and air pollution exposures on birth outcomes.) Part A of the R21 uses refined air pollution and traffic density data to examine their influence of on adverse birth outcomes such as low birth weight and premature birth. Part B of the R21 evaluates the feasibility of assembling a birth-cohort to provide saliva samples for the analysis of genetic and epigenetic susceptibility to the effects of air pollution. During the pre-Center funding, we will obtain additional spatially-refined exposure data from the prenatal periods of over 300, 000 birth in the San Joaquin Valley of California. We will implement novel statistical methods to evaluate possible longitudinal and joint of effects of pollutant mixtures on birth outcomes. In addition to the spatially-refined air pollution data, detailed traffic counts and density data, census and neighborhood-level characteristics, and for some demographic variables, simulated individual-level data will be used to control for confounding and identification of susceptible subgroups. It will evaluate the feasibility of a similar study design to examine numerous important children's health outcomes. Examples of outcomes include asthma, autism spectrum disorders, cancer, and metabolic disorders such as obesity. Genetic samples will be obtained from mothers/children identified in Part B of the R21 and stored for analysis during a full Center grant. Extensive investigation will be done to identify the proper set of genetic polymorphisms that may influence susceptibility to the effects of air pollution and those that are associated with preterm birth. Similar investigations will be done to identify genetic polymorphism associated with the risk of the other health outcomes listed. We have chosen a cost-efficient approach by making use of an exposure dataset of unparalleled richness with respect to specific pollutants (CRPAQS) and existing birth certificates files while at the same time developing a birth cohort and specimen bank for future research. Our study will also make use of modeling strategies developed for other funded studies conducted within the same region.

项目1的主要数据将来自由NIEHS资助的R21（R21 ES 014891-01A1，遗传学和空气污染暴露对出生结果的影响。不良出生结果，例如低出生体重和早产。 R21的B部分评估了组装出生体的可行性，以提供唾液样本，以分析遗传和表观遗传学对空气污染影响的敏感性。在中心前的资金期间，我们将从产前期间获得其他空间精制的暴露数据 300，000在加利福尼亚的圣华金山谷出生。我们将实施新颖的统计方法，以评估污染物混合物对出生结果的可能纵向和关节。除了空间精制的空气污染数据，详细的流量计数和密度数据，人口普查和邻居级别的特征以及对于某些人口统计学变量外，模拟的个体级数据还将用于控制易感亚组的混淆和识别。它将评估类似研究设计的可行性，以检查许多重要的儿童健康结果。结果的例子包括哮喘，自闭症谱系障碍，癌症和代谢性疾病，例如肥胖症。遗传样本将从R21 B部分中鉴定出的母亲/儿童中获得，并在全中心拨款期间存储进行分析。将进行广泛的研究，以确定可能影响空气污染影响的易感性以及与早产相关的遗传多态性的正确集合。将进行类似的研究，以确定与列出其他健康结果的风险相关的遗传多态性。我们选择了一种具有成本效益的方法，它利用了针对特定污染物（CRPAQ）和现有出生证书档案的无与伦比的丰富性数据集，同时又开发了出生同龄人和标本库以进行未来的研究。我们的研究还将利用为在同一地区内进行的其他资助研究制定的建模策略。