Spatial and Temporal Modeling of PM2.5 and Infant Morbidity

描述(由申请人提供)：环境PM2.5暴露与婴儿毛细支气管炎和中耳炎风险之间的潜在关联是一个重大的公共卫生问题。越来越多的毒理学和流行病学证据表明，暴露在环境中的PM2.5会加剧疾病进程，这支持了这种担忧。婴儿毛细支气管炎和中耳炎可能会对受影响的婴儿产生严重的长期后果，与医疗保健相关的成本很高。然而，现有的研究很少，而且有重要的局限性。这项研究将解决许多这些弱点，并为了解环境PM2.5暴露与婴儿毛细支气管炎和中耳炎之间的关系做出重大贡献。第一个目标是通过用卫星遥感数据补充地面监测数据，改进PM2.5暴露评估。高级统计建模将用于预测婴儿地理编码地址的PM2.5浓度，而不是将婴儿邮政编码质心与最近监测仪的数据联系起来。与现有研究相比，这将减少接触的错误分类。第二个目标是将PM2.5暴露与马萨诸塞州大型纵向出生队列的数据结合起来，这些数据与医院数据和马萨诸塞州出生缺陷登记处有关。由于有40,000多例住院和门诊婴儿毛细支气管炎病例和125,000例住院和门诊中耳炎病例，分析将有足够的能力检测微小影响，并检查脆弱的亚群，包括早产或既有呼吸或心脏疾病和/或先天性异常的婴儿。链接的Pell数据集允许对短期暴露进行病例交叉分析，并使用同胞对照分析长期暴露，以最大限度地减少混淆偏差。将传统流行病学研究设计与创新方法相结合，将减少经常与基于登记的分析相关的混淆偏差。为了检验剩余混杂的可能性，第三个目标将使用广义相加模型来检验在包括环境PM2.5暴露并对已知风险因素进行调整后的剩余风险的时空模式。拟议研究的结果将提供有关婴儿毛细支气管炎和中耳炎的新信息，这两种结果都有很强的环境因素，而且在脆弱的婴儿人群中的流行率越来越高。对于像周围环境PM2.5这样广泛的暴露，即使是很小的关联也可能对公共健康产生重大影响。

DESCRIPTION (provided by applicant): The potential association between ambient PM2.5 exposure and the risk of infant bronchiolitis and otitis media is a significant public health concern. This concern is supported by growing toxicologic and epidemiologic evidence that ambient PM2.5 exposure increases potentiation of the disease process. Infant bronchiolitis and otitis media may have serious long-term consequences for the affected infants and the healthcare related costs are substantial. However, available studies are sparse and have important limitations. This study will address many of these weaknesses and make significant contributions to understanding the relationship between ambient PM2.5 exposure and infant bronchiolitis and otitis media. The first aim is to improve PM2.5 exposure assessment compared to earlier studies by supplementing data from ground monitors with remote sensing data from satellites. Instead of linking infant ZIP code centroids to data from the closest monitor, advanced statistical modeling will be used to predict the PM2.5 concentration at the infants' geocoded addresses. This will reduce exposure misclassification compared to existing studies. The second aim is to integrate the PM2.5 exposure with data from a large longitudinal Massachusetts (MA) birth cohort linked to hospital data and the MA Birth Defects Registry. With more than 40,000 cases of inpatient and outpatient infant bronchiolitis and 125,000 cases of inpatient and outpatient otitis media, analyses will have sufficient power to detect small effects as well as examine vulnerable subpopulations including infants born premature or with pre- existing respiratory or cardiac conditions and/or congenital anomalies. The linked PELL dataset allows for case-crossover analyses for short-term exposures and analyses of long-term exposures using sibling controls to minimize confounding bias. The combination of traditional epidemiologic study designs with innovative methods will reduce confounding bias often associated with registry-based analyses. To examine the possibility of residual confounding, the third aim will use generalized additive models to examine the space- time pattern of residual risk after including ambient PM2.5 exposure and adjusting for known risk factors. The results of the proposed study will provide new information on infant bronchiolitis and otitis media, two outcomes for which there is a strong indication of an environmental component and for which there is increasing prevalence in the vulnerable infant population. For an exposure as widespread as ambient PM2.5, even small associations can have a significant public health impact.