Neupane Subas, K C Prakash, Nosraty Lily, Kyrönlahti Saila, Nygård Clas-Håkan, Oakman Jodi
Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland.
Tampere University Hospital, Wellbeing Services County of Pirkanmaa, Tampere, Finland.
Eur J Public Health. 2025 Aug 1;35(4):665-671. doi: 10.1093/eurpub/ckaf104.
We studied the trajectories of sickness absences among industrial workers over 6 years and examined whether the membership of trajectories was associated with subsequent retirement type for 11 years. We used data from one of the largest Finnish food industry companies that responded to a questionnaire survey in 2003. Sickness absence days per year from 2003 to 2008 were obtained from the company's registers and linked to the register of Finnish Centre for Pension data (statutory and non-statutory) until the end of 2019. We analysed data from 633 individuals who had information on sickness absence and the type of retirement. Latent class growth modelling was used to identify trajectories of sickness absence days per year, and Cox-regression models were used to examine the association of trajectories with retirement type. The models were adjusted for baseline sociodemographic, work-related physical, and psychosocial factors. We identified three distinct trajectories of sickness absence during the 6-year period. Most respondents (51.2%) had low-fluctuating, one-third (33.9%) had moderate-stable, and 14.9% had a high-stable sickness absence trajectory throughout. The high-stable trajectory was associated with a higher risk of non-statutory retirement (hazard ratio 2.67, 95% confidence interval 1.69-4.23) when adjusted for sociodemographic, perceived health, and work-related variables. We found significant heterogeneity in the number of sick absence days per year among the private sector employees over a period of 6 years. An increase in the risk of non-statutory retirement among those with high-stable sickness absences signifies the importance of early intervention to support individuals experiencing recurring sickness absence whilst employed.
我们研究了产业工人6年期间的病假轨迹，并考察了这些轨迹类别与随后11年退休类型之间的关联。我们使用了芬兰最大的食品工业公司之一在2003年对问卷调查作出回应的数据。2003年至2008年每年的病假天数从公司记录中获取，并与芬兰养老金中心数据登记册（法定和非法定）相链接，直至2019年底。我们分析了633名有病假信息和退休类型信息的个体的数据。采用潜在类别增长模型来确定每年病假天数的轨迹，并使用Cox回归模型来考察轨迹与退休类型之间的关联。模型针对基线社会人口统计学、工作相关身体因素和心理社会因素进行了调整。我们在6年期间确定了三种不同的病假轨迹。大多数受访者（51.2%）的病假波动较小，三分之一（33.9%）的病假较为稳定，14.9%的人自始至终都有较高且稳定的病假轨迹。在对社会人口统计学、感知健康状况和工作相关变量进行调整后，高稳定轨迹与非法定退休的较高风险相关（风险比2.67，95%置信区间1.69 - 4.23）。我们发现，在6年期间，私营部门员工每年的病假天数存在显著异质性。高稳定病假员工非法定退休风险的增加表明，早期干预对于支持在职时反复请病假的个体具有重要意义。
