Comparative evaluation of Spatio-Temporal Exposure Assessment Methods for estimating the health effects of air pollution (STEAM)

背景：流行病学研究已将长期和短期接触室外空气污染与死亡和发病风险增加联系起来。队列研究通过利用年空气污染浓度的空间异质性来评估长期接触对健康的影响，而时间序列研究利用污染浓度的时间变异性来评估急性影响。这些不同研究设计所报告的不良健康影响的重叠程度对健康影响评估和政策制定具有重要意义，迄今为止，在美国以外尚未进行过调查。在过去，这两种研究设计都受到监测污染数据可用性的限制，但分散和土地利用回归模型的发展改进了队列研究中的暴露评估，并使调查更广泛的污染物成为可能。将这些模型加以扩展，以提供按空间分列的污染物浓度每日估计数，将能够综合评估长期和短期接触各种污染物所产生的健康影响，并适用于监测很少或没有监测的地点。目的:1。开发、验证和比较伦敦在精细空间（邮编水平）和时间（每日）尺度上的分散、土地利用回归和基于卫星数据的污染模型。2. 评估这些方法及其组合在估计长期和短期接触空气污染物对健康的影响方面的表现。3. 使用最佳综合暴露方法来估计长期和短期暴露对选定健康结果的影响的相对重要性。为了实现这些目标，该项目将利用MRC-PHE环境与健康中心开发的专业知识，并需要借鉴国际领先组织（美国和希腊）在建模、模拟研究和时间序列分析方面的专业知识。方法：将为颗粒和气体污染物开发模型，并使用伦敦空气质量网络测量的浓度进行验证。它们对监测较少或没有监测的地点的适用性将使用可获得的暴露信息中依次较小的部分进行评估。一项已知“真实”影响的广泛模拟研究将调查使用每种暴露方法对健康影响估计的影响（精度和偏差）。为了验证概念，同时估计对各种健康结果的长期和短期影响，将对选定的端点进行分析，包括全科医生咨询、住院人数和死亡率数据。创新方面:1。精细时间和空间分辨率下空气污染建模方法的应用2。整合不同的暴露评估方法，优化其性能。3 .利用模拟方法同时评估模型在评估长期和短期暴露于微粒和气体污染物的影响方面的性能。在现有大型卫生数据集中同时估计长期和短期接触空气污染对健康的影响，以便比较它们的相对重要性。政策含义:1。关于每种暴露模式的优缺点的信息将为监测系统的最佳范围和密度以及当地模式的其他输入提供信息。同时估计短期和长期接触的影响将为短期紧急行动和长期污染管理干预之间的平衡提供依据。3 .为欧洲和世界上监测不那么密集的地区的建模发展提供信息。在欧洲和世界卫生结果数据库有限的地区，向卫生研究通报短期影响与长期影响的相对重要性

Background: Epidemiological studies have linked long- and short-term outdoor air pollution exposures to increased risks of death and morbidity. Cohort studies evaluate the health effects of long-term exposure by exploiting spatial heterogeneity in annual air pollution concentrations whereas time-series studies evaluate acute effects exploiting temporal variability in pollution concentrations. The extent to which the adverse health effects reported by these different study designs overlap has important implications for health impact assessment and policy development and to date this has not been investigated outside the US. In the past, both study designs have been limited by the availability of monitored pollution data but the development of dispersion and land use regression models have improved exposure assessment in cohort studies and enabled the investigation of a broader range of pollutants. The extension of these models to provide spatially resolved daily estimates of pollutant concentrations will enable an integrated assessment of health effects arising from both long- and short-term exposures to a wide range of pollutants and with applicability to locations with sparse or no monitoring.Objectives: 1.To develop, validate and compare dispersion, land use regression and satellite data based pollution models for London at both fine spatial (postcode level) and temporal (daily) scales. 2. To assess the performance of these methods and their combinations in estimating the health effects of long and short-term exposures to air pollutants. 3. To use the optimum integrated exposure method to estimate the relative importance of the effects of long-and short-term exposure for selected health outcomes. To achieve these objectives the project will use the expertise developed within the MRC-PHE Centre for Environment and Health and will need to draw upon the expertise of pioneering international groups (in the U.S. & Greece) in modelling, simulation studies and time series analyses.Methods: Models will be developed for particulate and gaseous pollutants and validated using measured concentrations from the London Air Quality Network. Their applicability to locations with sparse or no monitoring will be assessed using sequentially smaller parts of the available exposure information. An extensive simulation study, in which the "true" effect is known, will investigate the implications of using each exposure method on the health effect estimation (precision and bias).To enable proof of concept for the simultaneous estimation of long- and short-term effects on various health outcomes, the analysis of selected endpoints including GP consultations, hospital admissions and mortality data will be applied.Innovation aspects:1. Application of air pollution modelling approaches at a fine time and spatial resolution2. Integration of the different exposure assessment methods for optimizing their performance.3. Use of simulation methods to evaluate simultaneously the performance of models in assessing the effects of long- and short-term exposure to particulate and gaseous pollutants.4. Simultaneous estimation of health effects of long- and short-term exposure to air pollution in existing large health data sets to enable a comparison of their relative importance.Policy implications:1. Information on the advantages and disadvantages of each exposure model will inform the optimum extent and density of monitoring systems and other inputs to local models.2. The simultaneous estimation of the effects of short and long-term exposures will provide a rationale for the balance between emergency short-term action and long-term pollution management interventions.3. Informing the development of modelling in areas of Europe and the World where monitoring is not so dense.4. Informing health studies about the comparative importance of short vs long-term effects in areas of Europe and the World where health outcome data bases are limited