Airborne Particulate Matter and Adverse Health Events: Robust Estimation of Timescale Effects

Numerous epidemiological studies based on time-series analysis have shown associations between morbidity/mortality caused by respiratory and cardiovascular adverse events and chronic exposure to airborne particles (Bell et al. 2004), but a considerable uncertainty remains to be seen. This begs the question of whether these associations represent premature morbidity within only a few days among those people already near to acute health events. Statistical aspects of such a displacement effect (or harvesting) have been discussed by several authors (Dominici et al. 2003 and references therein); a reasonable underlying hypothesis is that mortality/morbidity displacement is associated with shorter timescales, while longer time scales are supposed to be resistant to displacement. If associations reflect only harvesting, the effect of air pollution on morbidity can be considered as having a limited impact from a public-health point of view. In this paper we discuss a new approach to assess the effect of short term changes in air pollution on acute health effects. Our method is based on a Singular Spectrum Analysis (SSA) decomposition of airborne particulate matter time series into a set of exposure variable, each one representing a different timescale. An advantage of our approach is that timescales need not to be set prior to their estimation.