Long-term exposure to fine particle elemental components and mortality in Europe: Results from six European...

Evidence for the association between long-term exposure to ambient particulate matter components and mortality from natural causes is sparse and inconsistent. We evaluated this association in six large administrative cohorts in the framework of the Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) project. We analyzed data from country-wide administrative cohorts in Norway, Denmark, the Netherlands, Belgium, Switzerland and in Rome (Italy). Annual 2010 mean concentrations of copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn) in fine particulate matter (PM_2.5) were estimated using 100 × 100 m Europe-wide hybrid land use regression models assigned to the participants' residential addresses. We applied cohort-specific Cox proportional hazard models controlling for area- and individual-level covariates to evaluate associations with natural mortality. Two pollutant models adjusting for PM_2.5 total mass or nitrogen dioxide (NO₂) were also applied. We pooled cohort-specific estimates using a random effects meta-analysis. We included almost 27 million participants contributing more than 240 million person-years. All components except Zn were significantly associated with natural mortality [pooled Hazard Ratios (HRs) (95% CI): 1.037 (1.014, 1.060) per 5 ng/m³ Cu; 1.069 (1.031, 1.108) per 100 ng/m³ Fe; 1.039 (1.018, 1.062) per 50 ng/m³ K; 1.024 (1.006, 1.043) per 1 ng/m³ Ni; 1.036 (1.016, 1.057) per 200 ng/m³ S; 1.152 (1.048, 1.266) per 100 ng/m³ Si; 1.020 (1.006, 1.034) per 2 ng/m³ V]. Only K and Si were robust to PM_2.5 or NO₂ adjustment [pooled HRs (95% CI) per 50 ng/m³ in K: 1.025 (1.008, 1.044), 1.020 (0.999, 1.042) and per 100 ng/m³ in Si: 1.121 (1.039, 1.209), 1.068 (1.022, 1.117) adjusted for PM_2.5 and NO₂ correspondingly]. Our findings indicate an association of natural mortality with most components, which was reduced after adjustment for PM_2.5 and especially NO₂.