Skin symptoms in bakery and auto body shop workers: associations with exposure and respiratory symptoms
Bibliographic record
Abstract
PURPOSE: Despite the importance of skin exposure, studies of skin symptoms in relation to exposure and respiratory symptoms are rare. The goals of this study were to describe exposure-response relationships for skin symptoms, and to investigate associations between skin and respiratory symptoms in bakery and auto body shop workers. METHODS: Data from previous studies of bakery and auto body shop workers were analyzed. Average exposure estimates for wheat allergen and isocyanates were used. Generalized linear models were constructed to describe the relationships between exposure and skin symptoms, as well as between skin and respiratory symptoms. RESULTS: Data from 723 bakery and 473 auto body shop workers were analyzed. In total, 5.3% of bakery and 6.1% of auto body shop workers were female; subjects' mean age was 39 and 38 years, respectively. Exposure-response relationships were observed in auto body shop workers for itchy or dry skin (PR 1.55, 95% CI 1.2-2.0) and work-related itchy skin (PR 1.97, 95% CI 1.2-3.3). A possible exposure-response relationship for work-related itchy skin in bakery workers did not reach statistical significance. In both groups, reporting skin symptoms was strongly and significantly associated with reporting respiratory symptoms, both work-related and non-work-related. CONCLUSIONS: Exposure-response relationships were observed for skin symptoms in auto body shop workers. The lack of significant exposure-response associations in bakery workers should be interpreted cautiously. Workers who reported skin symptoms were up to four times more likely to report respiratory symptoms. Improved awareness of both skin and respiratory outcomes in exposed workers is needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".