USE OF TRANSITION-PROBABILITIES TO ESTIMATE THE EFFECT OF SMOKING ON THE DURATION OF EPISODES OF RESPIRATORY SYMPTOMS IN DIARY DATA - THE SWISS STUDY ON AIR-POLLUTION AND LUNG-DISEASES IN ADULTS (SAPALDIA)

Incompletely documented symptom episodes pose methodological problems in the analysis of diary data. The aim of this study was to develop a method of estimating the average durations of symptomatic and nonsympt omatic episodes, respectively, coping with the problem of bias due to undocumented days and censored episodes that is found in most diary st udies. The authors derived their outcome variables from a Markov model using transition probabilities. To evaluate this method, the authors assessed the impact of active smoking on the duration of episodes of b ronchitis symptoms and the corresponding nonsymptomatic periods, respe ctively, using diary data (1992-1993) obtained from 801 participants i n the Swiss Study on Air Pollution and Lung Diseases in Adults. Covari ate-adjusted distribution curves for the mean durations of individual episodes were estimated by Cox regression. Median values for light smo kers (<10 cigarettes/day) were 60.0 symptom-free days (95% confidence interval (CI) 42.0-78.5) and 4.0 symptomatic days (95% CI 3.0-6.0), re spectively, compared with medians of only 21.0 days (95% CI 16.2-29.8) for periods without bronchitis symptoms and 6.0 days (95% CI 4.9-9.0) for episodes of bronchitis symptoms in heavy smokers (greater than or equal to 30 cigarettes/day). The authors suggest that the Markov meth od is a feasible approach to the assessment of long term effects of sm oking and environmental risk factors on the average duration of sympto matic and nonsymptomatic respiratory episodes.