Use of the MEGA Exposure Database for the Validation of the Stoffenmanager Model.
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| Title: | Use of the MEGA Exposure Database for the Validation of the Stoffenmanager Model. |
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| Authors: | Koppisch, Dorothea1, Schinkel, Jody2, Gabriel, Stefan1, Fransman, Wouter2, Tielemans, Erik2 |
| Source: | Annals of Occupational Hygiene. Jun2012, Vol. 56 Issue 4, p426-439. 14p. |
| Subjects: | Databases, Dust, Machinery, Mathematical models, Research methodology, Powders, Research funding, Risk assessment, Statistics, Work, Environmental exposure |
| Abstract: | Objectives: This paper explores the usefulness of the exposure database MEGA for model validation and evaluates the capability of two Stoffenmanager model equations (i.e. handling of powders/granules and machining) to estimate workers exposure to inhalable dust. Methods: For the task groups, ‘handling of powders and granules’ (handling) and ‘machining of wood and stone’ (machining) measurements were selected from MEGA and grouped in scenarios depending on task, product, and control measures. The predictive capability of the model was tested by calculating the relative bias of the single measurements and the correlation between geometric means (GMs) for scenarios. The conservatism of the model was evaluated by checking if the percentage of measurement values above the 90th percentile estimate was ≤10%. Results: From 22 596 personal measurements on inhalable dust within MEGA, 390 could be selected for handling and 1133 for machining. The relative bias for the task groups was −25 and 68%, respectively, the percentage of measurements with a higher result than the estimated 90th percentile 11 and 7%. Correlations on a scenario level were good for both model equations as well for the GM (handling: rs = 0.90, n = 15 scenarios; machining: rs = 0.84, n = 22 scenarios) as for the 90th percentile (handling: rs = 0.79; machining: rs = 0.76). Conclusions: The MEGA database could be used for model validation, although the presented analyses have learned that improvements in the database are necessary for modelling purposes in the future. For a substantial amount of data, contextual information on exposure determinants in addition to basic core information is stored in this database. The relative low bias, the good correlation, and the level of conservatism of the tested model show that the Stoffenmanager can be regarded as a useful Tier 1 model for the Registration, Evaluation, Authorisation and Restriction of Chemicals legislation. [ABSTRACT FROM AUTHOR] |
| Copyright of Annals of Occupational Hygiene is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 74197150 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Use of the MEGA Exposure Database for the Validation of the Stoffenmanager Model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Koppisch%2C+Dorothea%22">Koppisch, Dorothea</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Schinkel%2C+Jody%22">Schinkel, Jody</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Gabriel%2C+Stefan%22">Gabriel, Stefan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Fransman%2C+Wouter%22">Fransman, Wouter</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Tielemans%2C+Erik%22">Tielemans, Erik</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Annals+of+Occupational+Hygiene%22">Annals of Occupational Hygiene</searchLink>. Jun2012, Vol. 56 Issue 4, p426-439. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Dust%22">Dust</searchLink><br /><searchLink fieldCode="DE" term="%22Machinery%22">Machinery</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Powders%22">Powders</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Work%22">Work</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+exposure%22">Environmental exposure</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Objectives: This paper explores the usefulness of the exposure database MEGA for model validation and evaluates the capability of two Stoffenmanager model equations (i.e. handling of powders/granules and machining) to estimate workers exposure to inhalable dust. Methods: For the task groups, ‘handling of powders and granules’ (handling) and ‘machining of wood and stone’ (machining) measurements were selected from MEGA and grouped in scenarios depending on task, product, and control measures. The predictive capability of the model was tested by calculating the relative bias of the single measurements and the correlation between geometric means (GMs) for scenarios. The conservatism of the model was evaluated by checking if the percentage of measurement values above the 90th percentile estimate was ≤10%. Results: From 22 596 personal measurements on inhalable dust within MEGA, 390 could be selected for handling and 1133 for machining. The relative bias for the task groups was −25 and 68%, respectively, the percentage of measurements with a higher result than the estimated 90th percentile 11 and 7%. Correlations on a scenario level were good for both model equations as well for the GM (handling: rs = 0.90, n = 15 scenarios; machining: rs = 0.84, n = 22 scenarios) as for the 90th percentile (handling: rs = 0.79; machining: rs = 0.76). Conclusions: The MEGA database could be used for model validation, although the presented analyses have learned that improvements in the database are necessary for modelling purposes in the future. For a substantial amount of data, contextual information on exposure determinants in addition to basic core information is stored in this database. The relative low bias, the good correlation, and the level of conservatism of the tested model show that the Stoffenmanager can be regarded as a useful Tier 1 model for the Registration, Evaluation, Authorisation and Restriction of Chemicals legislation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Annals of Occupational Hygiene is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/annhyg/mer097 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 426 Subjects: – SubjectFull: Databases Type: general – SubjectFull: Dust Type: general – SubjectFull: Machinery Type: general – SubjectFull: Mathematical models Type: general – SubjectFull: Research methodology Type: general – SubjectFull: Powders Type: general – SubjectFull: Research funding Type: general – SubjectFull: Risk assessment Type: general – SubjectFull: Statistics Type: general – SubjectFull: Work Type: general – SubjectFull: Environmental exposure Type: general Titles: – TitleFull: Use of the MEGA Exposure Database for the Validation of the Stoffenmanager Model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Koppisch, Dorothea – PersonEntity: Name: NameFull: Schinkel, Jody – PersonEntity: Name: NameFull: Gabriel, Stefan – PersonEntity: Name: NameFull: Fransman, Wouter – PersonEntity: Name: NameFull: Tielemans, Erik IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2012 Type: published Y: 2012 Identifiers: – Type: issn-print Value: 00034878 Numbering: – Type: volume Value: 56 – Type: issue Value: 4 Titles: – TitleFull: Annals of Occupational Hygiene Type: main |
| ResultId | 1 |
