Urinary Metals as a Marker of Exposure in Men and Women in the Welding and Electrical Trades: A Canadian Cohort Study
Bibliographic record
Abstract
OBJECTIVES: Men and women working in the welding trades undergo the same apprenticeship training but it is unknown whether, once in the trade, their exposures differ. Comparison of urinary metal concentrations, having adjusted for estimated airborne exposure, may provide an answer. METHODS: Men and women were recruited to a cohort study of workers in the welding and electrical trades (the Workers Health in Apprenticeship Trades-Metal working and Electrical [WHAT-ME study]). They completed a recruitment questionnaire and further questionnaires every 6 months for up to 5 years. At each follow-up, they gave details on employment and, if welding, answered trade-specific questionnaires. Urine samples were collected by mail. Welding exposure matrices were developed to estimate metal exposures from welding process, base metal, and consumables. Urinary metal concentrations, determined by ICP-MS, were compared by trade (welding or electrical). Within welding, the relation of urinary concentrations to estimated airborne exposure was examined, with adjustment for potential confounders including sex, use of respiratory protective equipment (RPE), and time spent outdoors. Natural logarithms were taken of exposure estimates and urinary concentrations, to reduce skew. All regression analyses included creatinine concentration. RESULTS: Urinary metal concentrations were analysed for 12 metals in 794 samples. Antimony, arsenic, lead, and mercury had a high proportion of samples with no metal detected and were not considered further. The urinary concentrations of aluminum, cadmium, chromium, cobalt, copper, manganese, nickel, and zinc were compared for welders (434 samples) and electrical workers (360). After adjustment for potential confounders, welders had higher urinary concentrations for aluminum (β = 0.13 95%CI 0.03-0.24) and chromium (β = 0.66 95%CI 0.55-0.77). Of 434 welder urines, 334 could be matched securely to detailed information about the most recent day welding. For these, an estimate of airborne exposure was made for aluminum, chromium, manganese, and nickel. Male welders were estimated to have higher airborne exposure to chromium and nickel than women welders. No difference was seen in the estimated exposures for aluminum or manganese (or total dust). Regression analyses of the relation of urinary metals to estimated exposure showed a good concordance for aluminum (β = 0.09 95%CI 0.04-0.15 (P < 0.001) and chromium (β = 0.11 95%CI 0.05-0.17 P < 0.001). The concordance for manganese and nickel was positive, but much weaker. Urinary concentrations of aluminum and nickel were somewhat lower with increasing time wearing RPE and, for chromium and nickel, with time working outdoors. Having adjusted for estimated exposure, creatinine and other confounders, male welders had lower urine concentrations of aluminum (β = -0.35 95%CI -0.51 to -0.19 P < 0.001) chromium (β = -0.38 95%CI -0.57 to -0.19 P < 0.001) and manganese (β = -0.36 95%CI -0.49 to -0.23 P < 0.001) than female welders. CONCLUSION: Welders had higher urinary concentrations of aluminum and chromium than electrical workers. Exposure estimates of aluminum and chromium for welders were a valid representation of the airborne exposures to these metals. Although male welders were estimated to have higher exposures of chrome and nickel than female welders, the higher urinary metal concentrations in women welders is of concern, particularly for women who may conceive while in the trade.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".