Fertilizer Use and Self-Reported Respiratory and Dermal Symptoms Among Tree Planters
Bibliographic record
Abstract
In British Columbia, some tree planting operations require workers to fertilize planted seedlings with polymer-coated nitrogen, phosphorus, and potassium (NPK) fertilizers. This study examined respiratory and dermal health associated with fertilizer exposure among tree planters. We interviewed 223 tree planters using an adapted version of the American Thoracic Society questionnaire supplemented with questions on dermal health. Subjects were grouped by categories of increasing duration of exposure, with workers who had not worked with fertilizer as a reference group. The relationship between exposure and reported work-related symptoms was analyzed using logistic regression, adjusting for age, cumulative tobacco cigarettes smoked, marijuana smoking status, sex, and exposure to abrasive spruce needles. An elevated odds ratio was seen for work-related cough, phlegm, nasal symptoms, nosebleed, and skin rash in the highest exposure group (>37 days of fertilizer use in the past 2 years) but was significant only for phlegm (odds ratio = 3.59, 95% confidence interval = 1.10-11.70). Trends of increasing odds ratios with increasing exposure were seen for cough, phlegm, nasal symptoms, and skin rash. The results suggest a weak association between respiratory and dermal irritation and work with fertilizer. Results highlight the need for further exposure monitoring within the tree planting industry, and larger studies to investigate the relationship between work with fertilizer and respiratory and dermal health symptoms. [Supplementary materials are available for this article. Go to the publisher's online edition of the Journal of Occupational and Environmental Hygiene for the following free supplemental resource: a PDF file containing a respiratory and dermal health questionnaire.].
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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 | 0.000 | 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".