Urinary Metals as a Marker of Exposure in Men and Women in the Welding and Electrical Trades: A Canadian Cohort Study
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».