The Association Between Farming Activities and Respiratory Health in Rural School Age Children
Bibliographic record
Abstract
This study assessed the prevalence of asthma in Canadian children living on and off farms and the risk of asthma and respiratory symptoms of children exposed to certain farming activities. A cross-sectional survey was sent to parents of school children ages 6 to 13 living in an agricultural community in rural Saskatchewan. History of asthma and respiratory symptoms (cough, phlegm, or wheeze), location of home, and exposure to farming activities including haying, harvesting, moving, or playing with hay bales, feeding livestock, cleaning or playing in barns, cleaning pens, and emptying or filling grain bins were assessed. The response rate was 90.6% (n = 553). The prevalence of asthma and respiratory symptoms were 18.8% and 39.8%, respectively, and did not differ by home location (farm/nonfarm). In the adjusted multivariable models conducted with each farming activity separately, children who were exposed to emptying and filling of grain bins had a higher odds of asthma (odds [OR] = 2.18, 95% confidence interval [CI]: 1.03-4.62]. Reports of playing on or near hay bales (OR = 1.89, 95% CI:1.19-3.01), (OR = 2.08, 95% CI:1.07-4.06), and cleaning pens (OR = 2.70, 95% CI:1.05-6.97) were associated with increased respiratory symptoms. Certain farming activities associated with dust and animals appear to be risk factors for asthma and respiratory symptoms in this study population and should be avoided.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".