Recent re-analyses of time series studies have highlighted a second important epidemiological and statistical issue known as confounding bias. Pollution relative rate estimates for mortality= morbidity could be confounded by observed and unobserved time-varying confounders (such as weather variables, season, and in°uenza epidemics) that vary in a similar manner as the air pol- lution and mortality=morbidity time series. To control for confounding bias, smooth functions of time and temperature variables are included into the semi-parametric Poisson regression model
