Respiratory and allergic outcomes among 5-year-old children exposed to pesticides
Bibliographic record
Abstract
Background Little is known about the effects of pesticides on children’s respiratory and allergic outcomes. We evaluated associations of prenatal and current pesticide exposures with respiratory and allergic outcomes in children from the Infants’ Environmental Health Study in Costa Rica. Methods Among 5-year-old children (n=303), we measured prenatal and current specific gravity-corrected urinary metabolite concentrations of insecticides (chlorpyrifos, pyrethroids), fungicides (mancozeb, pyrimethanil, thiabendazole) and 2,4-D. We collected information from caregivers on respiratory (ever doctor-diagnosed asthma and lower respiratory tract infections (LRTI), wheeze and cough during last 12 months) and allergic (nasal allergies, itchy rash, ever eczema) outcomes. We fitted separate multivariable logistic regression models for high (≥75th percentile (P75)) vs low ( Results Children’s respiratory outcomes were common (39% cough, 20% wheeze, 12% asthma, 5% LRTI). High current pyrethroid metabolite concentrations (∑pyrethroids) were associated with wheeze (OR=2.37, 95% CI 1.28 to 4.34), itchy rash (OR=2.74, 95% CI 1.33 to 5.60), doctor-diagnosed asthma and LRTI. High current ethylene thiourea (ETU) (specific metabolite of mancozeb) was somewhat associated with LRTI (OR=2.09, 95% CI 0.68 to 6.02). We obtained similar results when modelling ∑pyrethroids and ETU as continuous variables. We saw inconsistent or null associations for other pesticide exposures and health outcomes. Conclusions Current pyrethroid exposure may affect children’s respiratory and allergic health at 5 years of age. Current mancozeb exposure might contribute to LRTI. These findings are important as pyrethroids are broadly used in home environments and agriculture and mancozeb in agriculture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".