Work-related factors of knee osteoarthritis in Korean farmers: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Several studies have reported a high prevalence of osteoarthritis (OA) of the knee among agricultural workers. We investigated work-related factors that increase the risk of knee OA among Korean farmers. METHODS: Data were extracted from the Jeonnam Center for Farmer's Safety and Health survey, conducted between 2013 and 2015. The sample included 489 farmers (man 240, woman 249). We defined knee OA as radiographic knee OA (≥ Kellgren-Lawrence grade 2) with symptoms (≥ Western Ontario and McMaster Universities Osteoarthritis, Korean version score 29.5). We considered covariates such as cumulative squatting working time (CSWT), cumulative heavy lifting working time (CLWT), body mass index (BMI), and history of knee injury. Odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were calculated for knee OA and adjusted for relevant covariates. RESULTS: The results of multivariate logistic regression analysis indicated that knee OA was correlated by factors such as sex, age, BMI, history of knee injury, CSWT, and CLWT. Particularly, CSWT > 20,000 hours (OR: 2.83; 95% CI: 1.35-5.92; reference < 10,000 hours) and CLWT > 5,000 hours (OR: 2.62; 95% CI: 1.14-6.06; reference < 2,000 hours) were associated with an increased risk of knee OA after adjustment for covariates. CONCLUSIONS: Squatting posture and heavy lifting associated with farm work might increase the risk of knee OA among Korean farmers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".