National Research Center for the Working Environment (NRCWE), Lersø Parkallé 105, DK-2100 Copenhagen Ø, Denmark.
Scand J Work Environ Health. 2012 Nov;38(6):516-26. doi: 10.5271/sjweh.3293. Epub 2012 Mar 22.
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.
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.
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.
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.
针对劳动力市场结果（如病假）的研究通常仅限于单一结果。本文通过分析纵向登记数据，探讨了使用多状态模型来研究从登记病假到工作、失业和残疾养老金之间的多次过渡的方法。
使用多状态模型分析四种状态（工作、病假、失业和残疾养老金）之间的过渡。前三种是可能的反复出现的状态。预测变量包括年龄组、性别、地理区域、慢性病、临时疾病、自营职业病假保险和怀孕。还研究了先前过渡的相对影响。
从病假到残疾养老金的过渡风险因年龄和地理区域而异。20-29 岁的人从工作过渡到病假和从病假过渡到失业的风险增加。自雇人士从工作过渡到病假的风险增加。患有慢性病的人病假的风险增加，但返回工作的可能性也增加。以前的病假会增加从工作过渡到病假、从病假过渡到失业、从工作过渡到失业以及从工作过渡到残疾养老金的风险。
多状态模型是分析登记数据以及病假、工作、失业和残疾养老金之间过渡的有效方法。这些方法可用于开发更好的病假、重返工作岗位、失业和残疾预测模型。
