A spatial joint analysis of metal constituents of ambient particulate matter and mortality in England

Abstract

Background Few studies have investigated associations between metal components of particulate matter on mortality due to well-known issues of multicollinearity. Here, we analyze these exposures jointly to evaluate their associations with mortality on small area data.

Methods We fit a Bayesian Profile Regression (BPR) to account for the multicollinearity in the elemental components (iron, copper and zinc) of PM10 and PM2.5. The models are developed in relation to mortality from cardiovascular and respiratory disease and lung cancer incidence in 2008-11 at small area level, for a population of 13.6 million in the London-Oxford area of England.

Results From the BPR, we identified higher risks in the PM10 fraction cluster likely to represent the study area, excluding London, for cardiovascular mortality RR 1.07 (95%CI 1.02, 1.12) and for respiratory mortality RR 1.06 (95%CI 0.99, 1.31), compared to the study mean. For PM2.5 fraction, higher risks were seen for cardiovascular mortality RR 1.55 (CI 95% 1.38, 1.71) and respiratory mortality RR 1.51 (CI 95% 1.33, 1.72), likely to represent the 'highways' cluster. We did not find relevant associations for lung cancer incidence.

Conclusion Our analysis showed small but not fully consistent adverse associations between health outcomes and particulate metal exposures. The BPR approach identified subpopulations with unique exposure profiles and provided information about the geographical location of these to help interpret findings.