265 Incidence of self reported asthma or wheeze among women in welding and electrical trades in the WHAT-ME study in Canada
Bibliographic record
Abstract
Objectives The WHAT-ME study (Women’s Health in Apprenticeship Trades-Metalworkers and Electricians) was established because of concerns about risk to the fetus of women welding during pregnancy. Prospective data on work-related health outcomes are also collected. The potential of the study is investigated using ‘new-onset asthma or wheeze’ as an example. Methods Women in registered apprenticeships since 2005 in welding, boiler-making, steam fitting/pipefitting (‘welders’) or electrical trades are invited to join the study. They complete questionnaires on health and exposure at baseline and subsequently every six months. Exposure data are based on the last day at work at each contact, and include information on hazards encountered for each task performed. For the analyses presented here a woman was considered currently working within her trade if working as a welder or electrician at the time of the interview or in the preceding month. Results To date 496 women have signed up, and recruitment is underway across Canada. The results here are from 385 early recruits (mean age 31.6 years) with completed baseline questionnaires: 220 women, analysed here, have also completed the first (6 month) follow-up questionnaire. At baseline more welders (28%) than electricians (18%) were current smokers (p < 0.01). Amongst those working since baseline, and who did not initially report asthma/wheeze, 13/95 welders and 3/65 electricians reported asthma/wheeze at 6 months. In a logistic regression analysis, adjusting for smoking, months working in their trade since baseline, and current employment in the trade, welders had an odds ratio of 3.23 (95%CI 0.85–12.18) for new-onset asthma or wheeze. Conclusions Female welders appear at higher risk than female electricians of reporting new-onset asthma or wheeze. The continuing recruitment and follow-up of the cohort will provide increasing power for this analysis and information on tasks within trade will help identify recommendations for prevention.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".