Does exposure misclassification bias estimates of acute cardiovascular effects of traffic related air pollution? (R-8197)

This project tackles the problem of exposure misclassification in environmental epidemiology. Especially for spatially heterogeneous pollutants, like pollution from traffic, health estimates are biased when exposure is represented by surrogate measures. We will use data from a panel study consisting of 122 participants who wore sensing devices (i.e. a black carbon air pollution monitor, GPS, physical activity monitors) for three periods of seven consecutive days throughout the year during a wide variety of activities. In the same participants, several subclinical markers were repeatedly measured (blood pressure, retinal microvasculature, heart rate variability). For each individual exposure will be determined using different metrics, each with a different level of complexity or granularity. The measures range from a fixed monitor for ambient concentrations, over spatiotemporal air pollution models combined with GPS tracks, to personal monitoring of air pollution, and calculation of inhaled dose. Exposure estimates are compared across methods, and then associated with the subclinical cardiovascular markers to quantify biases in epidemiological studies looking for short term effects of traffic-related air pollution.

Keywords:Black Carbon, Air pollution, Environmental Epidemiology, Exposure Misclassification, Time-activity patterns, Traffic

Disciplines:General biology, Plant biology