Sickness absence trajectories following labour market participation patterns: a cohort study in Catalonia (Spain), 2012–2014

Abstract

Background Previous studies have focused on the relationship between employment pathways and health-related outcomes based on cross-sectional or longitudinal approaches. However, little is known about the cumulative effects of employment status mobility on sickness absence (SA) over time. The aim of the present study was to examine the association between prior labour market participation (LMP) patterns and SA trajectories from a life-course perspective. Methods This cohort study was based on a sample of 11,968 salaried workers living in Catalonia and affiliated with the Spanish Social Security system, who accumulated more than 15 days on SA in at least one quarter during 2012–2014. Individuals were grouped into three different working life stages: early (18–25 years), middle (26–35 years), and late (36–45 years). To identify LMP patterns, we applied sequence analysis and cluster analysis (2002–2011), and we used latent class growth modelling to identify SA trajectories (2012–2014). Finally, we applied multinomial logistic regression models to assess the relationship between LMP patterns and SA trajectories. Results The analyses yielded six LMP patterns: stable employment (value range: 63–81%), increasing employment (5–22%), without long-term coverage (7–8%), decreasing employment (4–10%), fluctuant employment (13–14%), and steeply decreasing employment (7–9%). We also identified four SA trajectories: low stable (83–88%), decreasing (5–9%), increasing (5–11%), and high stable (7–16%). However, the only significant association we identified for LMP patterns and SA trajectories was among young men, for whom an increasing employment pattern was significantly associated with a lower risk for increased days on SA (adjusted odds ratio: 0.21; 95% confidence interval: 0.05–0.96). Conclusions SA trajectories are generally not related to prior 10-year LMP patterns at any stage of working life. To disentangle this relationship, future research might benefit from considering working life transitions with a quality-of-work approach framed with contextual factors closer to the SA course.

Identifying labour market pathways after a 30-day-long sickness absence –a three-year sequence analysis study in Finland

“…Sickness absentees’ background factors such as higher age and lower socioeconomic on RTW processes are well known to predict future sickness absences and disability and a lower likelihood for RTW [ 4 , 5 , 9 , 11 , 12 ]. However, less is known about the role of LTSA diagnosis for future multi-state paths.…”

“…Sequence analysis has proven to be a valuable method in capturing the different phases and transitions involved in the RTW process [ 4 , 5 , 9 – 12 ]. However, sequence analyses or other multi-state analyses have often concentrated on distinct diagnosis groups [ 4 , 10 , 13 ] or have had a limited standpoint to the states studied with focus on either labour market attachment [ 10 , 11 ] or disability benefits [ 4 ]. Sequence analyses with all-cause LTSA absentees, that include labour market states central to RTW (employment, unemployment, sickness absence, rehabilitation, and disability pension) on the one hand, but also include a comprehensive set of background characteristics on the other, are scarce.…”

“…In addition, the pathways after LTSA can depend on a wide range of personal demographic and socioeconomic characteristics, and baseline labour market position [ 4 , 5 , 9 , 11 , 12 ]. While the medical condition behind LTSA obviously can play a central role in the process, the role of LTSA diagnosis for future paths has not been widely accounted for in the multi-state models.…”

Trajectories of sustainable working life in nine Swedish residential regions: A longitudinal twin cohort study

“…Working life is usually characterized by changes in employment, living, and working conditions and potentially consequent changes between employment statuses. 13 Such changes might be independent or be a part of a cluster, since each change in working life may affect the likelihood of other changes, for example, unemployment or sickness absence might be linked with low future employability. 13 , 14 These changes can be directly or indirectly influenced by regional characteristics and consequently have an impact on sustainable working life.…”

Methodological considerations in establishing and maintaining longitudinal health workforce studies: Lessons learned from the WiSDOM cohort in South Africa

“…Health workforce cohort studies are well established in high-income countries [ 23 , 25 , 28 , 33 , 39 , 41 , 43 ]. Notwithstanding an encouraging increase in the use of longitudinal study designs in health workforce research in LMICs [ 21 , 27 , 30 , 32 , 34 , 44 ], prospective cohort studies remain uncommon, especially in sub-Saharan Africa where they are most needed.…”