Abstract

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.

Highlights

  • Estimating exposure to air pollution in members of an epidemiological cohort study is central to assessing associations between air pollution exposure and adverse health effects in these influential studies

  • Is estimation of air pollution exposure technically and logistically challenging [1,2], investigators are faced with uncertainty regarding the impacts of exposure measurement error on study health effect estimates

  • While there is a focus on Beijing, and Beijing is used as an example, the considerations and options are generally applicable to any air pollution cohort study anywhere, especially when within-urban exposure contrasts are of interest

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Summary

Introduction

Estimating exposure to air pollution in members of an epidemiological cohort study is central to assessing associations between air pollution exposure and adverse health effects in these influential studies. Is estimation of air pollution exposure technically and logistically challenging [1,2], investigators are faced with uncertainty regarding the impacts of exposure measurement error on study health effect estimates. We approach the task of attempting to estimate exposure to specific air pollutants and air pollution sources for study cohort participants in Beijing, China. While there is a focus on Beijing, and Beijing is used as an example, the considerations and options are generally applicable to any air pollution cohort study anywhere, especially when within-urban exposure contrasts are of interest. It is hoped that by going through this process we will be able to determine, or at least provide some guidance about, a preferred approach or approaches that are applicable in the current context

Air Monitoring Considerations
Geographic Scale
Measurement Error
Spatial Misalignment and Incompatibility
Exposure Time Windows
Evaluation of Predictions
The Beijing Context
Geographic Scale of Cohort Data
Health Endpoints in Cohort Studies
Beijing Cohorts
Approaches for Estimating Exposure
Using Administrative Monitoring Network Data
Using Study-Dedicated Monitoring Data
Approaches Not Utilizing Measured Air Pollution Concentrations
Chemical Transport Models
Satellite Remote Sensing Measurements
Approaches That Integrate Two or More Approaches
Overall Assessment and Recommendations
Conclusions
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