Dataset Information

Estimation of particulate mass and manganese exposure levels among welders.

ABSTRACT:

Background

Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations reported in the published literature.

Methods

Articles that described welding particulate and Mn exposures during field welding activities were identified through a comprehensive literature search. Summary measures of exposure and related determinants such as year of sampling, welding process performed, type of ventilation used, degree of enclosure, base metal, and location of sampling filter were extracted from each article. The natural log of the reported arithmetic mean exposure level was used as the dependent variable in model building, while the independent variables included the exposure determinants. Cross-validation was performed to aid in model selection and to evaluate the generalizability of the models.

Results

A total of 33 particulate and 27 Mn means were included in the regression analysis. The final model explained 76% of the variability in the mean exposures and included welding process and degree of enclosure as predictors. There was very little change in the explained variability and root mean squared error between the final model and its cross-validation model indicating the final model is robust given the available data.

Conclusions

This model may be improved with more detailed exposure determinants; however, the relatively large amount of variance explained by the final model along with the positive generalizability results of the cross-validation increases the confidence that the estimates derived from this model can be used for estimating welder exposures in absence of individual measurement data.

SUBMITTER: Hobson A

PROVIDER: S-EPMC3020674 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Publications

Estimation of particulate mass and manganese exposure levels among welders.

Hobson Angela A Seixas Noah N Sterling David D Racette Brad A BA

The Annals of occupational hygiene 20100924 1

<h4>Background</h4>Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations ...[more]

PMID: 20870928

Similar Datasets

Project description:Manganese (Mn) is an essential trace metal. It is also a component of welding fume. Chronic inhalation of manganese from welding fume has been associated with decreased neurological function. Currently, there is not a universally recognized biomarker for Mn exposure; however, hair and toenails have shown promise. In a cohort of 45 male welders and 35 age-matched factory control subjects, we assessed the sensitivity and specificity of toenail Mn to distinguish occupationally exposed subjects from unexposed controls. Further we examined the exposure time window that best correlates with the proposed biomarker, and investigated if non-occupational exposure factors impacted toenail Mn concentrations. Toenail clippings were analyzed for Mn using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Exposure to respirable Mn-containing particles (<4 µm) was estimated using an exposure model that combines personal air monitoring, work history information, and dietary intake to estimate an individual's exposure to Mn from inhalation of welding fume. We assessed the group differences in toenail concentrations using a Student's t-test between welders and control subjects and performed a receiver operating characteristic (ROC) curve analysis to identify a threshold in toenail concentration that has the highest sensitivity and specificity in distinguishing welders from control subjects. Additionally, we performed mixed-model regressions to investigate the association between different exposure windows and toenail Mn concentrations. We observed that toenail Mn concentrations were significantly elevated among welders compared to control subjects (6.87 ± 2.56 versus 2.70 ± 1.70 µg g-1; P < 0.001). Our results show that using a toenail Mn concentration of 4.14 µg g-1 as cutoff allows for discriminating between controls and welders with 91% specificity and 94% sensitivity [area under curve (AUC) = 0.98]. Additionally, we found that a threshold of 4.66 µg g-1 toenail Mn concentration enables a 90% sensitive and 90% specific discrimination (AUC = 0.96) between subjects with average exposure above or below the American Conference of Governmental Industrial Hygienist (ACGIH) Threshold Limit Value (TLV) of 0.02 mg m-3 during the exposure window of 7-12 months prior to the nail being clipped. Investigating which exposure window was best reflected by toenail Mn reproduced the result from another study of toenail Mn being significantly (P < 0.001) associated with exposure 7-12 months prior to the nail being clipped. Lastly, we found that dietary intake, body mass index, age, smoking status, and ethnicity had no significant effect on toenail Mn concentrations. Our results suggest that toenail Mn is a sensitive, specific, and easy-to-acquire biomarker of Mn exposure, which is feasible to be used in an industrial welder population.

Project description:Increased manganese (Mn) exposure is known to cause cognitive, psychiatric and motor deficits. Mn exposure occurs in different occupational settings, where the airborne Mn level and the size of respirable particulates may vary considerably. Recently the importance of the role of the cerebral cortex in Mn toxicity has been highlighted, especially in Mn-induced neuropsychological effects. In this study we used magnetic resonance imaging (MRI) to evaluate brain Mn accumulation using T1 signal intensity indices and to examine changes in brain iron content using T2* contrast, as well as magnetic resonance spectroscopy (MRS) to measure exposure-induced metabolite changes non-invasively in cortical and deep brain regions in Mn-exposed welders, Mn-exposed smelter workers and control factory workers with no measurable exposure to Mn. MRS data as well as T1 signal intensity indices and T2* values were acquired from the frontal cortex, posterior cingulate cortex, hippocampus, and thalamus. Smelters were exposed to higher air Mn levels and had a longer duration of exposure, which was reflected in higher Mn levels in erythrocytes and urine than in welders. Nonetheless, welders had more significant metabolic differences compared to controls than did the smelter workers, especially in the frontal cortex. T1 hyperintensities in the globus pallidus were observed in both Mn-exposed groups, but only welders showed significantly higher thalamic and hippocampal T1 hyperintensities, as well as significantly reduced T2* values in the frontal cortex. Our results indicate that (1) the cerebral cortex, in particular the frontal cortex, is clearly involved in Mn neurotoxic effects and (2) in spite of the lower air Mn levels and shorter duration of exposure, welders exhibit more extensive neuroimaging changes compared to controls than smelters, including measurable deposition of Mn in more brain areas. These results indicate that the type of exposure (particulate sizes, dust versus fume) and route of exposure play an important role in the extent of Mn-induced toxic effects on the brain.

Dataset Information

Estimation of particulate mass and manganese exposure levels among welders.

Background

Methods

Results

Conclusions

Publications

Estimation of particulate mass and manganese exposure levels among welders.

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