Sickness absence trajectories following labour market participation patterns in Catalonia, 2012-2014
Bibliographic record
Abstract
Abstract Background Working life is characterized by transitions between different employment status which could affect future health status. Previous studies on sickness absence (SA) have focused on risk factors in the workplace; however, there is scarce evidence regarding labour market participation (LMP) patterns. The aim of this study is to examine the association between prior LMP patterns and the course of SA. Methods Cohort study based on a sample of 11,968 salaried workers affiliated with the Spanish Social Security system, living in Catalonia, who accumulated more than 15 days on SA at least in one quarter during 2012-2014, from three working life cohorts according to the working life stage in 2002: early (18-25 years), middle (26-35 years) and late (36-45 years). Sequence analysis was used to identify LMP patterns (2002-2011). Latent class growth analysis was applied to identify SA trajectories (2012-2014). Finally, crude and adjusted odds ratios (aOR) were estimated using multinomial logistic regression models. Results Overall, four SA trajectories were identified: low stable (83%-88% of the workers), decreasing (5%-9%), increasing (5%-11%) and high stable (7%-16%) accumulated days on SA, for men and women. Similarly, seven LMP patterns were obtained: stable employment (63%-81%), increasing employment (5%-22%), delayed employment (7%-8%), decreasing employment (4%-10%), varying employment (13%-14%), steeply decreasing employment (9%), and steeply labour market exit (8%). No significant associations were observed among LMP patterns and SA trajectories, except for young men, where an increasing employment pattern was significantly associated with a lower risk to increase days on SA over time (aOR: 0.21 [95% CI: 0.04-0.96]). Conclusions A prior 10 years of LMP pattern does not seem to show an effect on the course of SA. A closer working life to the SA course could be considered to assess this relationship. Funding: Grants FIS PI17/00220 and PI14/00057 Key messages A longitudinally approach is warranted to evaluate the relationship between working life and sickness absence. Extended prior working lives are not related to the course of future sickness absence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".