In reply: Serial correlation and confounders in time-series air pollution studies

In reply: Jalaludin and colleagues query the potential effects that serial correlation and confounding by school holiday time periods may have had on our finding of an association between particulates derived from bushfire smoke and asthma presentations.1

As previously discussed by Schwartz, time series analyses are important to control for serial correlations, particularly those due to the effects of seasonality and weather fluctuations.2 Our study did not cover a number of seasons. It was conducted during one tropical dry season, a period characterised by remarkably stable day-to-day weather conditions.3 For this reason, we believe that the effects of any autocorrelation would have been negligible. It is of interest that the development of statistical methods for analysing time series of count data during the 1990s, and analysis of large studies of particulate pollution using these methods, did not have an important effect on the conclusions reached by earlier studies.4

There is evidence that hospital admissions for asthma fall during school holidays.5 Anecdotal reports of more regional fires suggest that, if anything, particulate concentrations over Darwin might increase at these times. A reanalysis of our data including school holiday periods as a potential confounding factor did not appreciably alter our results in either the continuous (revised incidence rate ratio [IRR],1.26; 95% CI, 1.12–1.41, compared with original IRR, 1.20; 95% CI, 1.09–1.34) or categorical analysis (see Table).