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).

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State: Public
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It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.
Serval ID
serval:BIB_9428
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
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).
Journal
American Journal of Epidemiology
Author(s)
Kaiser R., Schindler C., Künzli N., Ackermann-Liebrich U., Heeb D., Medici T.C., Zellweger J.P.
ISSN
0002-9262 (Print)
ISSN-L
0002-9262
Publication state
Published
Issued date
1998
Volume
148
Number
6
Pages
600-608
Language
english
Notes
Publication types: Journal Article ; Multicenter Study ; Research Support, Non-U.S. Gov't Publication Status: ppublish
licence nationale
Abstract
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 nonsymptomatic episodes, respectively, coping with the problem of bias due to undocumented days and censored episodes that is found in most diary studies. 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 bronchitis symptoms and the corresponding nonsymptomatic periods, respectively, using diary data (1992-1993) obtained from 801 participants in the Swiss Study on Air Pollution and Lung Diseases in Adults. Covariate-adjusted distribution curves for the mean durations of individual episodes were estimated by Cox regression. Median values for light smokers (<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), respectively, 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 (> or =30 cigarettes/day). The authors suggest that the Markov method is a feasible approach to the assessment of long term effects of smoking and environmental risk factors on the average duration of symptomatic and nonsymptomatic respiratory episodes.
Keywords
Adult, Air Pollution/adverse effects, Cross-Sectional Studies, Female, Humans, Male, Markov Chains, Middle Aged, Proportional Hazards Models, Respiratory Tract Diseases/epidemiology, Respiratory Tract Diseases/etiology, Smoking/adverse effects, Type="Geographic">Switzerland/epidemiology
Pubmed
Web of science
Open Access
Yes
Create date
19/11/2007 13:48
Last modification date
25/09/2019 7:10
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