Risk Factors for Agricultural Injury: A CaseâControl Analysis of Iowa Farmers in the Agricultural Health Study
Bibliographic record
Abstract
The purpose of this case-control study nested in the Agricultural Health Study was to assess risk factors for agricultural injury among a large group of Iowa farmers. A questionnaire sent to 6,999 farmers identified 431 cases who had a farm work-related injury requiring medical advice/treatment in the previous year and 473 controls who had no injury in the previous year. We assessed several potential risk factors for injury. A multiple logistic regression analysis showed significant associations between farm work-related injury and weekly farming work hours (> or = 50 hours/week) (OR = 1.65; 95% CI = 1.23-2.21), the presence of large livestock (OR = 1.77; 95% CI = 1.24-2.51), education beyond high school (OR = 1.61; 95% CI = 1.21-2.12), regular medication use (OR = 1.44; 95% CI = 1.04-1.96), wearing a hearing aid (OR = 2.36; 95% CI = 1.07-5.20), and younger age. These results confirm the importance of risk factors identified in previous analytic studies and suggest directions for future research in preventive intervention strategies to reduce farm work-related injuries.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".