Principal Component Pursuit to Assess Exposure to Environmental Mixtures in Epidemiologic Studies

流行病学研究中评估环境混合物暴露的主成分追踪

基本信息

项目摘要

Project Summary Traditionally, environmental epidemiologic studies have focused on assessing risks related to a single pollutant at a time. This, however, does not reflect reality, since we are constantly exposed to multiple pollutants at once. It is very important, therefore, to be able to assess exposure to pollutant mixtures when conducting environmental epidemiologic methods. Doing so, however, is especially challenging, mainly due to the high dimension of the multi-pollutant exposure matrix (if the exposure of interest includes more than e.g. 5 or 10 chemicals) and because these pollutants are usually very highly correlated with each other. Although some methods are available to address these issues, they usually require strong assumptions and have severe limitations. With this study we propose to bypass most of these limitations by adapting and extending a novel and robust method to assess exposure to multiple pollutants, called Principal Component Pursuit (PCP). We will assess the performance of PCP synthetic datasets representing multiple potential scenarios and study designs, and compare our results to those obtained by existing methods. Subsequently, we will apply PCP to three important Public Health issues, i.e. to evaluate the associations between (i) in utero exposure to a mixture of PCBs and neurodevelopment, (ii) exposure to a metals mixture and cardiovascular health, and (iii) exposure to an air pollution mixture and emergency cardiovascular admissions. Finally, we will develop and share software so other researchers can freely use this novel, robust and flexible tool across a plethora of study designs and research questions. Our proposed work will be significant as it will provide epidemiologists with a novel and robust tool to assess exposure to environmental pollutant mixtures.
项目摘要 传统上,环境流行病学研究侧重于评估与单一污染物相关的风险 一次。然而,这并不反映现实,因为我们经常暴露在多种污染物中, 一次因此,在进行环境管理时,能够评估对污染物混合物的暴露是非常重要的。 环境流行病学方法。然而,这样做特别具有挑战性,主要是由于高 多污染物暴露矩阵的维度(如果感兴趣的暴露超过5或10 化学物质),因为这些污染物通常彼此高度相关。尽管一些 虽然有方法可以解决这些问题,但它们通常需要强有力的假设,并且具有严重的 局限性。通过这项研究,我们建议通过改编和扩展一部小说来绕过这些限制。 主要成分追踪法(Principal Component Pursuit,PCP)是一种评估多种污染物暴露的可靠方法。我们 将评估代表多种潜在情景的五氯苯酚合成数据集的性能, 设计,并将我们的结果与现有方法获得的结果进行比较。随后,我们将PCP应用于 三个重要的公共卫生问题,即评估(i)子宫内暴露于 多氯联苯混合物与神经发育,(ii)接触金属混合物与心血管健康,以及(iii) 暴露于空气污染混合物和紧急心血管入院。最后,我们将开发和 共享软件,以便其他研究人员可以自由地使用这个新颖,强大和灵活的工具, 研究设计和研究问题。我们提出的工作将是重要的,因为它将提供流行病学家 使用一种新颖而强大的工具来评估对环境污染物混合物的暴露。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods.
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Marianthi-Anna Kioumourtzoglou其他文献

Marianthi-Anna Kioumourtzoglou的其他文献

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{{ truncateString('Marianthi-Anna Kioumourtzoglou', 18)}}的其他基金

Air Pollution and Pregnancy Loss
空气污染与流产
  • 批准号:
    10404683
  • 财政年份:
    2020
  • 资助金额:
    $ 51.38万
  • 项目类别:
Air Pollution and Pregnancy Loss
空气污染与流产
  • 批准号:
    10229357
  • 财政年份:
    2020
  • 资助金额:
    $ 51.38万
  • 项目类别:
Air Pollution and Pregnancy Loss
空气污染与流产
  • 批准号:
    10631106
  • 财政年份:
    2020
  • 资助金额:
    $ 51.38万
  • 项目类别:
Air Pollution and Pregnancy Loss
空气污染与流产
  • 批准号:
    9885935
  • 财政年份:
    2020
  • 资助金额:
    $ 51.38万
  • 项目类别:

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