Modeling COPD with a Generalized Linear Mixed Effect Model : Results from the OLIN-study

Abstract: The purpose of this thesis is to analyze which factors are associated with physicians’ diagnosis of Chronic Obstructive Pulmonary Disease (COPD) where time is of primary interest. The data that is used in the analysis is from the OLIN studies. The OLIN studies are a longitudinal epidemiological research project that focuses on obstructive lung diseases. The study population contains two groups, one group with COPD according to a lung function test criteria at inclusion in the study and one reference group with matching gender and age. All subjects were invited to annual examinations of a basic program including structured interviews, health-related questionnaires, and lung function testing. The analysis is performed with a generalized linear mixed effect model that accounts for dependencies within-subject observation, which make the selected model idea lwhen analyzing longitudinal data with repeated measurements from the same subject. Results show that smoking and poor performance from the lung function tests increases the risk of getting the COPD diagnosis by a physician. The thesis also reaches the conclusion that time has different effect depending on which group the subject belongs to. For subject that had COPD according to the lung function test criteria at inclusion in the study, the risk of getting the diagnosis increases with time, and for subject that did not have COPD at inclusion in the study, the risk decreases with time.