Farming and the risk of developing osteoarthritis in Alberta, Canada
Bibliographic record
Abstract
INTRODUCTION: Because farming is a physically demanding occupation, farmers may be susceptible to developing osteoarthritis (OA). The aim of this study was to determine the risk of developing OA in Canadian farm, non-farm rural and urban residents. METHODS: A retrospective cohort study of five Alberta health administrative databases examined the risk of developing OA among three groups: farm (n=143 431), non-farm rural (n=143 431) and urban (n=143 431) residents over the fiscal years 2000-2001 through 2020-2021. The algorithm for OA ascertainment defined cases based on criteria including one hospital admission, two physician visits within a 2-year interval, or two ambulatory care visits within 2 years. Incidence rates, lifetime risk, and mortality rates were calculated. Cox proportional hazard models compared the incidence of OA for the three groups over the 21 years. RESULTS: A total of 26 957 OA cases were identified among 1 706 256 person-years (PYs) in the farm cohort. The crude incidence rate of OA over a period of 21 years ranged from 19.1 (95% confidence interval (CI) 18.6-19.6) per 1000 PYs in 2001 to 10.0 (95% CI 9.6-10.5) per 1000 PYs in 2021. The overall incidence rate was higher in the farm group (15.8 (95%CI 15.6-16.0) per 1000 PYs) as compared to the non-farm rural (14.7 (95%CI 14.5-14.9) per 1000 PYs) and the urban groups (13.3 (95%CI 13.1-13.4) per 1000 PYs). After adjusting for age and sex, the farm (6%; 95%CI 4-8%), and non-farm rural (9%; 95%CI 7-12%) groups had higher incidence rates than the urban group. The unadjusted non-injury mortality rate for the farm group with OA was lower (13.2 (95%CI 12.9-13.5) per 1000 PYs) than both the urban (14.5; 95%CI 14.1-14.8) and rural (18.0; 95%CI 17.6-18.4) groups. After adjusting for mortality, the lifetime risk of developing OA was 27.7% for farm residents, 25.6% for the non-farm rural cohort, and 24.0% for the urban cohort. CONCLUSION: When accounting for age and sex, farm and non-farm rural residents have a higher risk of developing OA as compared to the urban population. The higher mortality-adjusted lifetime risk of developing OA among farm residents highlights the necessity of specific interventions aimed at reducing the impact of this condition in rural communities. Further research is required to identify specific occupational and lifestyle risk factors associated with OA among farmers and to develop effective strategies for prevention and management.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".