Background: Although the association between exposure to particulate matter (PM) mass and mortality is well established, there remains uncertainty about which chemical components of PM are most harmful to human health.
Methods: A hierarchical approach was used to determine how the association between daily PM2.5 mass and mortality was modified by PM2.5 composition in 25 US communities. First, the association between daily PM2.5 and mortality was determined for each community and season using Poisson regression. Second, we used meta-regression to examine how the pooled association was modified by community and season-specific particle composition.
Results: There was a 0.74% (95% confidence interval = 0.41%-1.07%) increase in nonaccidental deaths associated with a 10 microg/m3 increase in 2-day averaged PM2.5 mass concentration. This association was smaller in the west (0.51% [0.10%-0.92%]) than in the east (0.92% [0.23%-1.36%]), and was highest in spring (1.88% [0.23%-1.36%]). It was increased when PM2.5 mass contained a higher proportion of aluminum (interquartile range = 0.58%), arsenic (0.55%), sulfate (0.51%), silicon (0.41%), and nickel (0.37%). The combination of aluminum, sulfate, and nickel also modified the effect. These species proportions explained residual variability between the community-specific PM2.5 mass effect estimates.
Conclusions: This study shows that certain chemical species modify the association between PM2.5 and mortality and illustrates that mass alone is not a sufficient metric when evaluating health effects of PM exposure.