Statistical Services and Methods Development Resource

项目总结 对儿童环境健康的研究表明，环境暴露的后果 在发育的关键时期，可表现为人类一生中的疾病或功能障碍。 儿童是因各种因素而增加的不良健康风险的最脆弱的亚群之一 包括暴露于环境污染物、营养不良和压力，因为它们的主要器官 这些系统从受孕到青春期都在发展。这些因素是多方面的，而且 复杂--不是简单的、与单一健康后果有关的单一暴露。统计方法与研究 用于分析在这种环境下产生的复杂、高维数据的设计仍然相对较新 需要先进的统计技术知识。统计服务与方法的发展 资源(SSMDR)将多学科的专业知识(统计学、流行病学、生物信息学)整合在 单一教员可与更广泛的儿童环境健康研究合作 通过数据中心建立社区。SSMDC的目标主要有四个类别：服务、 儿童环境健康研究联盟的合作研究，方法 与儿童健康接触有关的生物统计技术的发展和教育/培训 分析资源(CHEAR)数据中心。我们的具体目标是：1)为 向与数据中心合作的调查人员提供统计、流行病学和生物信息学服务；2) 支持儿童环境健康研究联盟之间的合作研究；3)开展 新的和创新的生物统计和生物信息学方法在相关领域的发展 数据中心；以及4)为儿童环境健康研究人员提供统计培训，创建 可公开使用的统计软件，用于分析CHEAR数据并开发可公开使用的软件 用于通过与儿童环境有关的网络研讨会进行教学的培训/范例数据集 健康。这些目标的实现将推动CHEAR数据中心和更大范围的目标 CHEAR网络，以最大限度地了解环境暴露对 通过提供严谨和创新的生物统计/生物信息学方法来分析儿童健康 儿童环境健康数据。

PROJECT SUMMARY Research in children's environmental health demonstrates that consequence of environmental exposures during critical periods in development can manifest as disease or dysfunction across the human life span. Children are one of the most vulnerable subpopulations for increased adverse health risks from factors including exposures to environmental contaminants, poor nutrition, and stress because their major organ systems are developing from conception through adolescence. These factors are multi-dimensional and complex – not simple, single exposures related to a single health outcome. Statistical methods and study designs for analyzing the complex, high-dimensional data that arise in such settings are still relatively new and require knowledge of advanced statistical techniques. The Statistical Services and Methods Development Resource (SSMDR) consolidates multi-disciplinary expertise (statistics, epidemiology, bioinformatics) in a single faculty made available for collaboration with the broader children's environmental health research community through the Data Center. The aims of the SSMDC are in four primary categories: service, collaborative research across the Children's Environmental Health Research consortium, methods development, and education/training on biostatistical techniques relevant to the Children's Health Exposure Analysis Resource (CHEAR) Data Center. Our specific aims are: 1) provide an integrated approach for statistical, epidemiological, and bioinformatics service to investigators collaborating with the Data Center; 2) support collaborative research across the Children's Environmental Health Research consortium; 3) conduct novel and innovative biostatistical and bioinformatic methods development in relevant areas to the CHEAR and the Data Center; and 4) provide statistical training for children's environmental health researchers by creating publicly available statistical software for analysis of the CHEAR data and developing publicly utilizable training/example datasets to be used for didactic learning through webinars related to children's environmental health. The achievement of these aims will advance the goals of the CHEAR Data Center and the larger CHEAR Network to maximize our understanding of the potential impact of environmental exposures on children's health by providing rigorous and innovative biostatistical/bioinformatics methods for analyzing children's environmental health data.