Farm Exposure and Atopy in Men and Women: The Saskatchewan Rural Health Study
Bibliographic record
Abstract
Associations between farming exposures and atopy can vary by timing of exposure and sex. We examined associations between adult atopy, sex, and farm living in a rural Canadian population. In 2010, we conducted a baseline survey of 11,982 households located in four agricultural regions of Saskatchewan, Canada. Of the 7225 adults aged 18-75, 1658 underwent clinical assessments including skin testing. Of these, 1599 participants underwent skin prick testing to four common allergens. We defined atopy as >3 mm reaction to any of four allergens compared with saline control. Farming exposures were farm living in the first year of life and current farm living. All analyses were stratified by sex. The prevalence of atopy was 17.8% and was higher in men than women (P < .001). The most common allergy was to grasses (8.8%) followed by house dust mite (HDM) mixed (8.1%). Atopy was lower in those subjects with an early farm exposure (P = .08) and who were female (P = .03). After adjusting for education, age, and smoking status, both current and early farm exposures were associated with decreased sensitization to cat atopy in women that was stronger with current exposure (P < .05). Men had significantly decreased atopic sensitization to Alternaria with an early farm exposure and increased atopic sensitization to HDM with a current farm exposure. In this rural population, the protective effect of an early farm exposure for any atopy was weak overall. The impact of farming exposures on atopy was allergen dependent and varied by sex.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".