Importance of the Population Exposure Model in the Impact of PM and Daily Mortality
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Date
2009
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Abstract
Background and Objectives:
A usual critique of ecological studies is the poor characterization of the population exposure to air pollution. In this work, the impact of population exposure modeling to particulate matter (PM10 and PM2.5) on the risk estimates is analyzed for the inhabitants of Santiago (Chile), for the years 1997 to 2005.
Methods:
All cause mortality risks were computed using a simple exposure model (average of several monitors) and a more detailed one, based on the results of an atmospheric photochemical model for four weeks, and extrapolated to the rest of the year.
Results:
Significant contributions to the risk estimates were found when the detailed exposure model was considered. The elderly showed the biggest increase on risk due to PM2.5 exposure, from 2.7% (CI 95%: 1.8–3.6) to 3% (1.9–4.1). For all ages, the increase was smaller, from 1% (0.4–1.7) to 1.2% (0.3–2.1). Even though the increases in risk were higher for the cold season, the incorporation of the proposed exposure wasn’t statistically significant.
Conclusion:
Health risks found were consistent with the evidence of previous national and international studies. The relative risks estimations using the proposed model were greater than using the average of the monitors, as usual in ecological studies. Even though the difference between the two models was not statistically significant, the RR increase is important for policy applications. The model based on photochemical estimations is a contribution in the exposure assessment, but its influence has to be explored with more detail.