The main hypothesis we will investigate is that long-term exposure to low concentrations of outdoor air pollution is related to adverse health effects. We will define ‘low’ using various cut-points defined by current EU, US and WHO limit values, air quality standards and guidelines, respectively. We will specifically test whether the concentration-response functions deviate significantly from linearity at low exposures. We will exploit selected well-characterized cohorts from the ESCAPE study and seven large European administrative cohorts to study health effects of low level air pollution.
The specific objectives are:
To estimate long-term average exposure to PM2.5, NO2, O3 and Black Carbon by developing new hybrid models that combine monitoring data, land use, satellite observations and dispersion models of the pooled ESCAPE cohort and seven large administrative cohorts
To investigate the shape of the relationship between long-term exposure to PM2.5, NO2, Black Carbon and O3 and three broad health effect categories: (a) natural and cause-specific mortality, (b) coronary and cerebrovascular events, and (c) lung cancer incidence – using a number of different methods to characterize the exposure response function (linear, non-linear, threshold)
To investigate variability of the exposure-response function across population and different exposure assessment methods; as well as the impact of different methods for exposure measurement error; the role of co-occurring pollutants, and the effect of indirect approaches for confounder control in administrative cohorts