Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England

摘要: Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations pollutants to be constructed for each geographical unit and time period. Averaging space is commonly carried out, but little known about how robust estimated effects are different aggregation functions. A second under researched question what likely have future. We conducted England between 2007 2011, investigating relationship respiratory hospital admissions pollutants: nitrogen dioxide (NO2); ozone (O3); particulate matter, latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM2.5), 10 (PM10); sulphur (SO2). Bayesian Poisson regression models accounting localised autocorrelation were used estimate relative risks (RRs) on disease risk, pollutant four using combinations spatial temporal averages maximums. The RRs then make projections numbers 2050s attributable pollution, based emission from number Representative Concentration Pathways (RCP). NO2 exhibited largest association out considered, increased 0.9 1.6% one standard deviation increase concentrations. In future projected lower present day rates 3 (RCPs): 2.6, 6.0, 8.5, which due reductions emissions exhibit consistent substantial present-day regardless concentration time. Thus as predicted remain above limits set by European Union Legislation until 2030s parts urban England, it will risk some