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Record W4225248661 · doi:10.1093/annweh/wxac024

Pregnancy Outcome in Women Exposed to Metal Fume in Welding: A Canadian Cohort Study

2022· article· en· W4225248661 on OpenAlexafffundabout
Jean‐Michel Galarneau, Jeremy Beach, Nicola Cherry

Bibliographic record

VenueAnnals of Work Exposures and Health · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsUniversity of CalgaryUniversity of Alberta
FundersCanadian Institutes of Health ResearchWorkSafeBC
KeywordsPregnancyWeldingMedicineOccupational hygieneCohort studyCohortEnvironmental healthOccupational safety and healthEngineeringMechanical engineering

Abstract

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OBJECTIVES: Welding is a physically demanding job that entails exposure to metal fume and particles. There is little information on the effect of welding exposures on the outcome of a pregnancy conceived during a period when a woman was employed as a welder. METHODS: Women welders recruited to the Workers Health in Apprenticeship Trades-Metal and Electrical (WHAT-ME) study were followed-up every 6 months for up to 5 years (January 2011-August 2018), and every pregnancy recorded. At the first 6-month follow-up, a detailed questionnaire was completed for the most recent day in welding, and this information was collected again at each follow-up and also from questionnaires completed during pregnancy. The date of conception was estimated for each pregnancy and the job at that date identified. Exposures to ergonomic factors, work schedule and perceptions of noise, heat and cold were extracted for the job at conception. Exposures to metals (aluminum, chromium, manganese, and nickel) and particles in welding fume were estimated from previously validated exposure algorithms reflecting the welding process, base metal and consumables of the job at the conception date. The effects of exposures were estimated in multilevel multivariable models allowing for confounding. RESULTS: There were 242 pregnancies conceived by a welder working in her trade, 87 were before the first follow-up, 3 were after first follow-up but detailed information was not collected, 22 of those potentially included in the assessment group were in-trade but not welding leaving 122 pregnancies in 90 welders for analysis. Of these 91 resulted in a live birth and 31 in a fetal loss (27 miscarriages and 4 stillbirths). Mean birth weight for live births was 3365 g and gestation 39.4 weeks. Final models showed that risk of fetal loss increased with manipulating heavy objects [odds ratio (OR) = 5.13, 95% confidence interval (CI) 2.04-12.92], whole-body vibration (OR = 5.86, 95% CI 1.81-18.92), a higher rating for noise exposure intensity (OR = 1.52, 95% CI 1.24-1.85), and decreased with use of local exhaust ventilation (OR = 0.20, 95% CI 0.03-1.18). Gestation decreased with perceived heat intensity (β = -0.15, 95% CI -0.29 to -0.02) and number of previous pregnancies (β = -0.35, 95% CI -0.65 to -0.05). Birth weight was lower in those reporting whole-body vibration (β = -596 g, 95% CI -924 to -267) and increased with the welder's body mass index (β = 36 g, 95% CI 12-61). Estimates of exposure to metals and particles were unrelated to gestation or birth weight. In a bivariate analysis, allowing for the same welder reporting >1 pregnancy, estimated airborne aluminum exposure (and to a lesser degree exposure to nickel and particles) was related to greater risk of fetal loss (OR = 1.52, 95% CI 1.04-2.24) but neither aluminum nor the other estimated elements of welding fume added to the final model. CONCLUSIONS: In this group of women actively engaged in welding during the time surrounding conception, the outcome of pregnancy was strongly related to work exposures, particularly vibration (reported in grinding tasks), manipulation of heavy objects, and perceived intensity of noise and heat. The study was unable to show an independent effect of exposure to metal fume constituents.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.089
GPT teacher head0.343
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2022
Admission routes3
Has abstractyes

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