Assessment of joint effects of pesticides and air pollution in pediatric asthma

农药和空气污染对小儿哮喘的联合影响评估

基本信息

  • 批准号:
    9057040
  • 负责人:
  • 金额:
    $ 15.37万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-04-20 至 2018-03-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): The research objective of this K22 Career Development Award (CDA) is to ascertain if agricultural pesticide exposure confounds or modifies the relation between ambient air pollution exposure and pulmonary function in children with asthma. The central hypothesis is that early-life exposure to agricultural pesticides in conjunction with exposure to high levels of ambient air pollution is associated significantly with decreased lung function. The respiratory effects of chronic exposure to agricultural pesticides in childhood remain unknown. As the State of California has required full reporting of agricultural pesticide use for over two decades, retrospective exposure assessment of community-level pesticide application can be conducted effectively for hypothesized critical windows for asthma etiology. In addition to pesticide exposure, the land use patterns and topography of the San Joaquin Valley, the state's major agricultural region, result in high levels of exposure to ambient air pollution (AAP). The Fresno Asthmatic Children's Environment Study (FACES) offers a well-characterized longitudinal cohort to investigate the simultaneous effects of pesticides and AAP on changes in lung function and development of asthma. The research approach will consist of three Specific Aims. (Aim 1): Implementation of three pesticide exposure assessment strategies (geographic-based exposure, collection of dust samples, and collection of urinary biomarkers) to estimate associations with current lung function in the FACES cohort. We hypothesize that the relation between lung function and pesticides will vary by exposure assessment method and by class of pesticide. We anticipate that these short-term exposure measures can be used to calibrate the long-term pesticide exposures estimates. (Aim 2): Comparison of two Bayesian statistical methods to understand the relation between agricultural pesticide exposure and lung function. This aim will consist of statistical simulations that will be conducted with pesticide exposure estimates informed by Aim 1 and retrospective air pollution data based on residential histories from the FACES cohort (n = 315). The relation between lung function, environmental exposures and demographic covariates (sex and race) will be analyzed using two recently developed statistical methods, nonparametric Bayes shrinkage and profile regression. The objective of this aim is to understand the statistical model performance of these Bayesian approaches for research of complex environmental mixtures and demographic factors. (3). Assessment of the independent and joint effects of pesticide exposure in combination with ambient air pollution on lung function. We will estimate the effect of early childhood (ages 0 - 1) exposure to community-level pesticide and ambient air pollutants on baseline lung function from the FACES cohort (n=315) in a model derived in Aim 2. We hypothesize that early childhood (0 - 1 year) exposure to three classes of agricultural pesticides will modify the relation between air pollution and FEV1 measured at study enrollment (ages 6 - 11). The CDA Candidate is a tenure-track Assistant Professor of Epidemiology in the Department of Environmental and Radiological Health Sciences at Colorado State University (CSU) with training in environmental and social epidemiology. Her short-term career goal is to expand her current research in asthma epidemiology and develop a research program to address multi-pollutant exposure analyses in vulnerable communities, with specific focus on agricultural pesticide exposures and ambient air pollution. Her long-term career goal is to understand the dynamic interaction of environmental pollutants, biogenic exposures, and host factors on asthma incidence in children. This CDA will support her didactic and experiential training in toxicology and Bayesian statistics. Her statisticl training for this grant application is necessitated by the inferential limitations of conventional statistical methods (e.g. generalized linear models) for multi-pollutant analyses (i.e. regarding assessment of toxic compounds given application of mixtures or combinations of pesticides) and multi-domain analyses (i.e. ascertainment of the independent contribution of pesticides among combinations of correlated factors, both anthropogenic and biogenic in nature.) These statistical approaches must be informed by an understanding of compound interaction on a toxicological level. Her biostatistics training will include data simulation and Bayesian approaches for epidemiologic studies; toxicology training will include course work, field work in exposure assessment, and laboratory work in environmental and biomarker sample analysis. Her department has expertise in environmental epidemiology, exposure assessment and toxicology; the campus offers comprehensive training in applied statistical approaches and methods. These experiences will inform the conduct of this CDA, as well as future work transdisciplinary research environmental health. This CDA supports the mission of the NIEHS via investigation of the health effects of low-level chronic exposures.
描述(由申请人提供):本 K22 职业发展奖 (CDA) 的研究目标是确定农业农药暴露是否会混淆或改变环境空气污染暴露与哮喘儿童肺功能之间的关系。中心假设是,生命早期接触农业农药以及暴露于高水平的环境空气污染与肺功能下降显着相关。儿童时期长期接触农业农药对呼吸系统的影响仍不清楚。由于加利福尼亚州二十多年来一直要求全面报告农业农药的使用情况,因此可以有效地对社区一级农药的使用情况进行回顾性暴露评估,以推测哮喘病因的关键窗口。除了农药暴露之外,该州主要农业区圣华金河谷的土地利用模式和地形也导致高水平的环境暴露 空气污染(AAP)。弗雷斯诺哮喘儿童环境研究 (FACES) 提供了一个特征明确的纵向队列,以研究农药和 AAP 对肺功能变化和哮喘发展的同时影响。研究方法将包括三个具体目标。 (目标 1):实施三种农药暴露评估策略(基于地理的暴露、灰尘样本的收集和尿液生物标志物的收集),以估计与 FACES 队列中当前肺功能的关联。我们假设肺功能和农药之间的关系会因暴露评估方法和农药类别而异。我们预计这些短期暴露测量可用于校准长期农药暴露估计。 (目标 2):比较两种贝叶斯统计方法,以了解农业农药暴露与肺功能之间的关系。该目标将包括统计模拟,根据目标 1 提供的农药暴露估计值和基于 FACES 队列 (n = 315) 居住历史的回顾性空气污染数据进行统计模拟。将使用两种最近开发的统计方法(非参数贝叶斯收缩和轮廓回归)来分析肺功能、环境暴露和人口统计协变量(性别和种族)之间的关系。该目的的目的是了解这些贝叶斯方法在复杂环境混合物和人口因素研究中的统计模型性能。 (3)。评估农药暴露与环境空气污染对肺功能的独立和联合影响。我们将估计幼儿期(0 - 1 岁)的影响 在目标 2 派生的模型中,暴露于社区级农药和环境空气污染物对来自 FACES 队列 (n=315) 的基线肺功能的影响。我们假设幼儿期(0 - 1 岁)接触三类农业农药会影响基线肺功能。修改空气之间的关系 污染和 FEV1 在研究登记时测量(6 - 11 岁)。 CDA 候选人是科罗拉多州立大学 (CSU) 环境与放射健康科学系流行病学终身教授,接受过环境和社会流行病学培训。她的短期职业目标是扩大目前在哮喘流行病学方面的研究,并制定一项研究计划来解决脆弱社区的多污染物暴露分析,特别关注农业农药暴露和环境空气污染。她的长期职业目标是了解环境污染物、生物暴露和宿主因素对儿童哮喘发病率的动态相互作用。该 CDA 将支持她在毒理学和贝叶斯统计方面的教学和体验培训。由于传统统计方法(例如广义线性模型)在多污染物分析(即在施用农药混合物或组合的情况下评估有毒化合物)和多领域分析(例如广义线性模型)的推理局限性,她为此拨款申请进行统计培训是必要的。即确定农药在相关因素(本质上是人为因素和生物因素)组合中的独立贡献。)这些统计方法必须基于对毒理学上化合物相互作用的理解。 等级。她的生物统计学培训将包括流行病学研究的数据模拟和贝叶斯方法;毒理学培训将包括课程作业、暴露评估的现场工作以及环境和生物标志物样本分析的实验室工作。她的部门拥有环境流行病学、暴露评估和毒理学方面的专业知识;该校园提供应用统计方法和方法的综合培训。这些经验将为 CDA 的开展以及未来的跨学科环境健康研究工作提供信息。该 CDA 通过调查低水平慢性暴露对健康的影响来支持 NIEHS 的使命。

项目成果

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Sheryl Magzamen其他文献

Sheryl Magzamen的其他文献

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{{ truncateString('Sheryl Magzamen', 18)}}的其他基金

Antimicrobial Resistant Bacteria: Exposures and Health of Cattle Workers
耐药细菌:养牛工人的接触和健康
  • 批准号:
    10437480
  • 财政年份:
    2020
  • 资助金额:
    $ 15.37万
  • 项目类别:
Antimicrobial Resistant Bacteria: Exposures and Health of Cattle Workers
耐药细菌:养牛工人的接触和健康
  • 批准号:
    10227645
  • 财政年份:
    2020
  • 资助金额:
    $ 15.37万
  • 项目类别:
Evaluation of California's 2020 chlorpyrifos cancellation on health and exposure in agricultural communities
加州2020年取消毒死蜱对农业社区健康和暴露的影响评估
  • 批准号:
    10260580
  • 财政年份:
    2020
  • 资助金额:
    $ 15.37万
  • 项目类别:
Antimicrobial Resistant Bacteria: Exposures and Health of Cattle Workers
耐药细菌:养牛工人的接触和健康
  • 批准号:
    10783823
  • 财政年份:
    2020
  • 资助金额:
    $ 15.37万
  • 项目类别:
Antimicrobial Resistant Bacteria: Exposures and Health of Cattle Workers
耐药细菌:养牛工人的接触和健康
  • 批准号:
    10030543
  • 财政年份:
    2020
  • 资助金额:
    $ 15.37万
  • 项目类别:
Design and Evaluation of Interventions to Improve Dairy Worker Respiratory Health
改善乳制品工人呼吸健康的干预措施的设计和评估
  • 批准号:
    8866787
  • 财政年份:
    2014
  • 资助金额:
    $ 15.37万
  • 项目类别:
Validation of the UPAS+: A filter-based air sampler coupled with a suite of real-time sensors
UPAS 的验证:基于过滤器的空气采样器与一套实时传感器相结合
  • 批准号:
    10312360
  • 财政年份:
    2014
  • 资助金额:
    $ 15.37万
  • 项目类别:

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