Evidence map›Paper›PMID 34453157›Full record

ArticleAnnals of work exposures and health2022

Construction and Calibration of an Exposure Matrix for the Welding Trades.

Jean-Michel Galarneau

Open access · greenAbstract read
In one paragraph

Article in Annals of work exposures and health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 37% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Respiratory Ill-Health and Welding Exposures: A Canadian Cohort Study.American journal of industrial medicine · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Jean-Michel GalarneauDivision of Preventive Medicine, University of Alberta, 8303-112 Street, Edmonton, Alberta T6G 2T4, Canada.ORCID 0000-0003-3784-8753
University of Alberta · CA

Funding

CIHR 130236
6 · The paper itself

Abstract

objectivesThis study aimed to construct, validate, and calibrate an exposure matrix that would be used to estimate personal airborne exposures to total dust, manganese, nickel, chromium, and aluminum for welders in the WHAT-ME cohort. The Workers' Health in Apprenticeship Trades: metal and electrical (WHAT-ME) study established a cohort of women and men welders to investigate pregnancy and other birth outcomes along with health issues related to welding. To construct the matrix, data were extracted and assembled from the literature and analyzed to produce exposure models. Final models derived in this first step were then compared with external data gathered under controlled conditions and later combined to form calibrated models.

methodsA systematic literature search was conducted to identify and extract all relevant data from published journal articles appearing in selected databases. Summary data were extracted that represented airborne personal exposures to total, inhalable and respirable dusts along with metal concentrations for manganese, nickel, chromium, and aluminum. Mathematical exposure models were derived and a validation of the models undertaken in the second part of this study. The most common welding combinations of welding process, base metal, and consumable (welding scenarios) for welders taking part in the WHAT-ME study were identified through detailed welding questionnaires completed by WHAT-ME participants. These were replicated under controlled conditions with a welder equipped with a personal air sampling pump to gather samples. A gravimetric analysis was performed to determine total dust exposures followed by a metals analysis using ICP-MS. Predictions were made for these welding scenarios replicated in the laboratory, using the exposure models derived in the literature and the predictions correlated against the results from the welding laboratory replications.

resultsThe systematic review yielded 92 published articles from which 737 summary statistics were extracted representing 4620 personal samples of total dust, 4762 of manganese, 4679 of nickel, 3972 of chromium, and 676 of aluminum. The highest total dust exposures were for flux-core arc welding (FCAW) while the highest manganese producing base metal was mild steel. For nickel, the highest emissions were from high alloyed steel using gas metal arc welding while chromium emissions were most abundant in manual metal arc welding on stainless steel. Aluminum exposures were highest in FCAW welding and on aluminum as a base metal. The replication of 21 scenarios covered more than 90% of the scenarios in the WHAT-ME study. Sixty-one laboratory welding sessions took place with a minimum of two replications per scenario. Spearman rank correlations between predicted exposures and mean measured exposures yielded a rho of 0.93 (P < 0.001) for total dust, 0.87 (P < 0.001) for manganese, 0.54 (P < 0.024) for nickel, 0.43 (P = 0.055) for chromium, and 0.29 (P = 0.210) for aluminum.

conclusionsThis study produced the first welding exposure matrix composed of process, base metal, and consumable. This model was able to predict exposures observed under controlled conditions and could be used by any researcher to estimate welding exposures in a wide range of occupational contexts.

Indexed as

Air Pollutants, OccupationalOccupational ExposureWeldingCalibrationEnvironmental MonitoringFemaleHumansMaleAir Pollutants, Occupationalexposure matrixwelding exposure matrix

Identifiers

PMID34453157
PMCPMC8855695
OpenAlexW3194904586

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.