There is a large body of literature supporting a link between air pollutant exposure and asthma morbidity; however, the extent and significance of this relationship varies considerably among pollutants, location, scale of analysis, and analytical methods. This study evaluated relationships among asthma hospitalisation, ambient air pollution levels, and weather conditions in Los Angeles (LA) County, California, an area of historically heavy air pollution. County-wide CO, NO2, O3, particulate matter <10 ím (PM10), particulate matter <2.5 ím (PM2.5), maximum temperature, and relative humidity measurements were collected for all months, 2001 to 2008. These variables were then related to monthly asthma hospitalisation rates using Bayesian regression models with temporal random effects. Model performance was evaluated using a goodness of fit criterion and predictive ability. Asthma hospitalisation rates in LA County decreased from 2001 to 2008. Traffic related pollutants (CO, NO2) were significantly, positively correlated with asthma hospitalisations. PM2.5 also had a positive, significant association with asthma hospitalisation. PM10, relative humidity, and maximum temperature produced mixed results; O3 was non-significant in all models. Including temporal random effects satisfied statistical model assumptions, improved model fit, and yielded increased predictive accuracy and precision versus their non-temporal counterparts. Generally, pollution levels and asthma hospitalisation decreased over the study period. In addition, the results indicate that after accounting for seasonality in the data, asthma hospitalisation rate had a significantly positive relationship with ambient CO, NO2, and PM2.5 concentrations.
Authors: Delamater, Paul L.; Finley, Andrew O.; Banerjee, Sudipto ;Full Source: Science of the Total Environment [online computer file] 2012, 425, 110-118 (Eng) ;