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

项目1的主要数据将来自NIEHS资助的R21 （R21 ES 014891-01A1，遗传和空气污染暴露对出生结果的影响）。R21的A部分使用精炼的空气污染和交通密度数据来检查它们对低出生体重和早产等不良出生结局的影响。R21的B部分评估了组建出生队列以提供唾液样本以分析空气污染影响的遗传和表观遗传易感性的可行性。在前期中心资助期间，我们将从加利福尼亚州圣华金河谷超过30万名新生儿的产前阶段获得额外的空间精细暴露数据。我们将采用新的统计方法来评估污染物混合物对出生结果的可能的纵向和联合影响。除了空间精细的空气污染数据，详细的交通计数和密度数据，人口普查和社区水平

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 ofthe 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 ofthe 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 ofthe 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.