Ambient PM2.5 and ETS exposure: interactive health effects for asthmatic children

环境 PM2.5 和 ETS 暴露：对哮喘儿童健康的交互影响

• 批准号: 7851109
• 负责人: Matthew J Strand
• 金额: $ 7.8万
• 依托单位: NATIONAL JEWISH HEALTH
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-01 至 2011-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7851109
• 关键词: Accounting; Acute; Affect; Age; Air Pollutants; Air Pollution; Albuterol; Applications Grants; Asthma; Biological Markers; Caliber; Calibration; Child; Child health care; Colorado; Computer software; Confidence Intervals; Cotinine; Data; Data Analyses; Development; Environmental Tobacco Smoke; Exposure to; Funding; Hand; Health; Individual; Inflammation; Leukotriene E4; Measurement; Measures; Medical Research; Methodology; Methods; Modeling; Monitor; Outcome; Particulate Matter; Pharmaceutical Preparations; Publishing; Pulmonary Function Test/Forced Expiratory Volume 1; Research; Respiratory physiology; Risk; Sampling; Schools; Source; Statistical Methods; Statistical Models; Sum; Techniques; Time; Tobacco; Tobacco smoke; Work; computer program; follower of religion Jewish; method development; pollutant; pollutant interaction; programs; public health relevance; response

DESCRIPTION (provided by applicant): Statistical models that allow for estimation of health effects of air pollution are well developed when only one pollutant is considered. Similarly, co-pollutant models have often been examined, which typically consider two pollutant variables from ambient sources. In this proposed work, exposures to two air pollutants from differences sources (one ambient, one mainly non-ambient) will be modeled. Specifically, these pollutants are ambient particulate matter less than 2.5 microns in diameter (PM2.5), and environmental tobacco smoke (ETS). Individually, exposures to both pollutants have been shown to have negative impacts on health. However, interactive effects can only by examined by including these variables in the same model. Preliminary studies have suggested that for albuterol medication use, there is a significant negative interaction between the two pollutants, meaning that effect of two pollutants together is not as strong as the sum of the individual effects (i.e., the effect of exposure to only ambient PM2.5 plus the effect of exposure to ETS only). Before certain plausible explanations about why this occurs are developed, the model needs to be refined and results verified. In particular, the models need to more properly account for the longitudinal (repeated measures) component of the data, with verification by repeating analysis for each of three years of collected data. Since direct measures of pollutant exposures are difficult or impossible to obtain, other surrogate measures such as cotinine or fixed outdoor monitor concentrations need to be utilized. Using these, plus more unbiased measures of exposures from selected samples, regression calibration can be applied to yield estimates that are in similar and meaningful units of measurement. Regression calibration with two variables, including interaction, has only been recently proposed, and thus carrying out the actual analysis will require development of relevant computer programs to carry out the analysis. This program construction and data analysis will be the scope of the first aim. The remaining aims involve nonparametric regression with two variables for data that involve repeated measures, and monotone smoothing of the resulting mean function. These will involve some methods development (for the monotone estimation), and development of computer programs to carry out both. Collectively, the models will allow for more precise estimation of health effects of ETS and ambient PM2.5 exposure. Although certain limitations exist, such as establishing definitive causal effects, these analyses should be a first step in understanding how outdoor air pollution affects health of children, when ETS is examined as an effect modifier (both short term and long term). PUBLIC HEALTH RELEVANCE: The interactive acute health effects of environmental tobacco smoke (ETS) and ambient fine particulate matter (PM2.5) exposure on health of children with asthma will be analyzed. The results will allow for a better understanding about how children with lower or higher ETS exposure react to PM2.5 from outdoor sources.

描述（由申请人提供）：当只考虑一种污染物时，允许估计空气污染对健康影响的统计模型已经很好地开发出来。类似地，共同污染物模型也经常被检验，它通常考虑来自环境源的两个污染物变量。在这项拟议的工作中，将模拟暴露于来自不同来源的两种空气污染物（一种是环境污染物，另一种主要是非环境污染物）。具体来说，这些污染物是直径小于2.5微米的环境颗粒物（PM2.5）和环境烟草烟雾（ETS）。单独接触这两种污染物已被证明对健康有负面影响。然而，交互效应只能通过在同一模型中包含这些变量来检验。初步研究表明，对于沙丁胺醇药物的使用，两种污染物之间存在显著的负相互作用，这意味着两种污染物的共同影响不如单个影响的总和那么强（即仅暴露于环境PM2.5的影响加上仅暴露于ETS的影响）。在对发生这种情况的原因作出合理解释之前，需要对模型进行改进，并对结果进行验证。特别是，模型需要更适当地考虑数据的纵向（重复测量）成分，并通过对每三年收集的数据进行重复分析进行验证。由于很难或不可能获得污染物暴露的直接测量，因此需要利用其他替代措施，如可替宁或固定的室外监测浓度。使用这些，再加上来自选定样本的更多无偏暴露测量，回归校准可以应用于相似和有意义的测量单位的产量估计。包括相互作用在内的两个变量的回归校准最近才被提出，因此进行实际分析将需要开发相关的计算机程序来进行分析。本程序的构建和数据分析将是本范围的首要目标。其余的目标涉及涉及重复测量的数据的两个变量的非参数回归，以及结果平均函数的单调平滑。这将涉及到一些方法的开发（用于单调估计），以及开发计算机程序来实现这两者。总的来说，这些模型将允许更精确地估计碳排放交易体系和环境PM2.5暴露对健康的影响。虽然存在某些限制，例如确定明确的因果关系，但当将排放交易体系作为影响调节因素（短期和长期）进行研究时，这些分析应是了解室外空气污染如何影响儿童健康的第一步。

项目成果

Regression calibration for models with two predictor variables measured with error and their interaction, using instrumental variables and longitudinal data.

• DOI: 10.1002/sim.5904
• 发表时间: 2014-02-10
• 期刊: STATISTICS IN MEDICINE
• 影响因子: 2
• 作者: Strand, Matthew;Sillau, Stefan;Grunwald, Gary K.;Rabinovitch, Nathan
• 通讯作者: Rabinovitch, Nathan