Modelling asthma epidemics on the relationship between air pollution and asthma emergency visits in Barcelona, Spain

Abstract

We have investigated different methods of controlling for asthma epidemics in the time series regression of the relationship between air pollution and asthma emergency visits in Barcelona, Spain. The relationship between air pollution and asthma emergency room visits was modelled using autoregressive Poisson models. We examined the effect of using no control by epidemics, and modelling asthma epidemics with a single dummy variable, six dummy variables, and a dummy variable for each epidemic day. Air pollution coefficients increased when controlling asthma epidemics with six dummy variables instead of a single variable. They further increased when autocorrelation was allowed for. Standard errors were relatively unaffected when either the epidemics or the autocorrelation were included in the model. Black smoke, nitrogen dioxide and ozone were statistically significant associated to asthma emergency visits after using six dummy variables to control for asthma epidemics. We have shown that different models, including different confounding variables, give markedly different estimates of the effect of a pollutant on health. Care is needed in the interpretation of such models, and careful reporting so it is clear how the confounding variables have been modelled.