Urban Ambient Particle Metrics and Health: A Time-series Analysis

Background: Epidemiologic evidence suggests that exposure to ambient particulate matter is associated with adverse health effects. Little is known, however, about which components of the particulate mixture (size, number, source, toxicity) are most relevant to health. We investigated associations of a range of particle metrics with daily deaths and hospital admissions in London. Methods: Daily concentrations of particle mass (PM10, PM2.5, and PM10–2.5), measured using gravimetric, tapered-element-oscillating, and filter-dynamic-measurement-system samplers, as well as particle number concentration and particle composition (carbon, sulfate, nitrate and chloride), were collected from a background monitoring station in central London between 2000 and 2005. All-cause and cause-specific deaths and emergency admissions to hospital in London for the same period were also collected. A Poisson regression time-series model was used in the analysis. Results: The results were not consistent across the various outcomes and lags. Particle number concentration was associated with daily mortality and admissions, particularly for cardiovascular diseases lagged 1-day; increases in particle number concentration (10,166 n/cm3) were associated with 2.2% (95% confidence interval = 0.6% to 3.8%) and 0.6% (−0.4% to 1.7%) increases in cardiovascular deaths and admissions, respectively. Secondary pollutants, especially nonprimary PM2.5, nitrate and sulfate, were more important for respiratory outcomes. Conclusions: This study provides some evidence that specific components of the particle mixture for air pollutants may be relevant to specific diseases. Interpretation should be cautious, however, in particular because exposures were based upon data from a single centrally located monitoring site. There is a need for replication with more comprehensive exposure data, both in London and elsewhere.