Occupation, Physical Workload Factors, and Disability Retirement as a Result of Hip Osteoarthritis in Finland, 2005–2013
Bibliographic record
Abstract
OBJECTIVE: To identify occupations with a high risk of disability retirement as a result of hip osteoarthritis (OA), and to examine the effect of physical workload factors on the occupational differences in disability retirement. METHODS: A total of 1,135,654 (49.4% women) Finns aged 30-60 years in gainful employment were followed from 2005 to 2013 for full disability retirement as a result of hip OA. Information on pensions, occupation, and education were obtained from national registers. Physical workload was assessed by a sex-specific job exposure matrix. We calculated age-adjusted incidence rates and examined the associations of occupation, education, and physical workload factors with disability retirement using a competing risk regression model. RESULTS: Age-adjusted incidence rate was 25 and 22 per 100,000 person-years in men and women, respectively. Both men and women working in lower-level nonmanual and manual occupations had an elevated age-adjusted risk of disability retirement as a result of hip OA. A very high risk of disability retirement was found among male construction workers, electricians, and plumbers (HR 12.7, 95% CI 8.4-19.7), and female professional drivers (HR 15.2, 95% CI 7.5-30.8) as compared with professionals. After adjustment for age and education, the observed occupational differences in disability retirement were largely explained by physical workload factors among men and to a smaller extent, among women. CONCLUSION: Our results suggest that education and physical workload factors appear to be the major reasons for excess disability retirement as a result of hip OA in manual occupations, particularly among men.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".