Hernando-Rodriguez JC, Serra L, Benavides FG, Ubalde-Lopez M. Sickness absence trajectories following labour market participation patterns: a cohort study in Catalonia (Spain), 2012-2014.
BMC Public Health 2020;
20:1306. [PMID:
32854670 PMCID:
PMC7453716 DOI:
10.1186/s12889-020-09396-9]
[Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 08/17/2020] [Indexed: 11/10/2022] Open
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.
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