OBJECTIVES: Studies of labor market outcomes like sickness absence are usually restricted to a single outcome. This paper investigates the use of multi-state models for studying multiple transitions between sick-listing, work, unemployment, and disability pension by analyzing longitudinal register data. Every person sick-listed in Denmark during 2004 was followed until the spring of 2008. METHODS: A multi-state model was used to analyze transitions between four states: work, sickness absence, unemployment, and disability pension. The first three are possible recurrent states. The predictor variables include age group, gender, geographical region, chronic disease, temporary disease, self-employment sickness absence insurance, and pregnancy. The relative effects of previous transitions were also studied. RESULTS: Risk of transition from sickness absence to disability pension differs with age and geographical region. Those aged 20-29 years have an increased risk of transitioning from work to sickness absence and from sickness absence to unemployment. The self-employed have increased risk of transitioning from work to sickness absence. Those with chronic disease have increased risk of sickness absence, but also a greater probability of returning to work. Previous sickness absence increases the risk of transitioning from work to sickness absence, from sickness absence to unemployment, from work to unemployment, and from work to disability pension. CONCLUSIONS: The multi-state model is an effective way of analyzing register data and the transitions between sickness absence, work, unemployment, and disability pension. These methods can be used to develop better predictive models of sickness absence, return to work, unemployment, and disability.
OBJECTIVES: Studies of labor market outcomes like sickness absence are usually restricted to a single outcome. This paper investigates the use of multi-state models for studying multiple transitions between sick-listing, work, unemployment, and disability pension by analyzing longitudinal register data. Every person sick-listed in Denmark during 2004 was followed until the spring of 2008. METHODS: A multi-state model was used to analyze transitions between four states: work, sickness absence, unemployment, and disability pension. The first three are possible recurrent states. The predictor variables include age group, gender, geographical region, chronic disease, temporary disease, self-employment sickness absence insurance, and pregnancy. The relative effects of previous transitions were also studied. RESULTS: Risk of transition from sickness absence to disability pension differs with age and geographical region. Those aged 20-29 years have an increased risk of transitioning from work to sickness absence and from sickness absence to unemployment. The self-employed have increased risk of transitioning from work to sickness absence. Those with chronic disease have increased risk of sickness absence, but also a greater probability of returning to work. Previous sickness absence increases the risk of transitioning from work to sickness absence, from sickness absence to unemployment, from work to unemployment, and from work to disability pension. CONCLUSIONS: The multi-state model is an effective way of analyzing register data and the transitions between sickness absence, work, unemployment, and disability pension. These methods can be used to develop better predictive models of sickness absence, return to work, unemployment, and disability.