The effect of joint pain and arthritis on the Montana ranching and farming community
Bibliographic record
Abstract
Abstract Background: Arthritis and joint pain have shown high prevalence rates in agricultural workers and is of concern because many agricultural operations are sustained by a small number of workers. The disability of even one worker may therefore contribute to economic hardship. This study investigated joint health in Montana agricultural workers and its economic effects on ranches and farms. Methods: The aims of this study were to determine associations between years working in agriculture and joint health, and between joint health and the economic health of a ranch or farm. A total of 299 ranchers and farmers in nine Montana counties completed a survey that included an assessment of the economic health of the ranch or farm, work capacity, and the need to rely on others to complete one’s work. Focus groups were then held with ranchers in two Montana counties, discussing similar topics. Results: 87.6% of survey respondents reported joint pain, 47.8% a diagnosis of arthritis, and 22.4% osteoarthritis (OA). Using proportional odds regression analysis, a 10-point increase in the Western Ontario and McMaster University arthritis index (WOMAC) score was significantly associated with lower work capacity (OR 2.00; 95% CI [1.58, 2.55], p<0.01), worse financial condition (OR 1.23; 95% CI [1.01,1.48], p=0.04), and increased reliance on others (OR 1.82; 95% CI [1.32, 2.55], p<0.01). A diagnosis of arthritis was associated with moving to a worse category of work capacity (OR 4.66; 95% CI [2.71, 8.01], p<0.01) and increased odds of relying on others (OR 3.23; 95% CI [1.56, 6.66], p<0.01), compared to those without arthritis. A diagnosis of OA was significantly associated with decreased work capacity (OR 3.47; 95% CI [1.97, 6.11], p<0.01). Adjusting for age and BMI, we found no association between years spent working in agriculture and joint health. Focus group themes included decreased productivity with increased joint symptoms and a tendency for ranchers to avoid interaction with the health care system. Conclusions: This mixed-methods study demonstrated an association between poor joint health and economic risk on Montana ranches and farms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".