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Development of a quantitative North and Central European job exposure matrix for wood dust.

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Title: Development of a quantitative North and Central European job exposure matrix for wood dust.
Authors: Basinas, Ioannis1,2,3 ioannis.basinas@manchester.ac.uk, Liukkonen, Tuula4, Sigsgaard, Torben3, Andersen, Nils T3, Vestergaard, Jesper M5, Galea, Karen S2, Tongeren, Martie van1, Wiggans, Ruth1, Savary, Barbara6, Eduard, Wijnand7, Kolstad, Henrik A5, Vested, Anne3,5, Kromhout, Hans8, Schlünssen, Vivi3
Source: Annals of Work Exposures & Health. Jul2023, Vol. 67 Issue 6, p758-771. 14p.
Subjects: Dust, Construction materials, Occupational exposure, Regression analysis, Population geography, Descriptive statistics, Research funding
Geographic Terms: Netherlands, United Kingdom, France, Denmark, Finland, Norway
Abstract: Wood dust is an established carcinogen also linked to several non malignant respiratory disorders. A major limitation in research on wood dust and its health effects is the lack of (historical) quantitative estimates of occupational exposure for use in general population-based case-control or cohort studies. The present study aimed to develop a multinational quantitative Job Exposure Matrix (JEM) for wood dust exposure using exposure data from several Northern and Central European countries. For this, an occupational exposure database containing 12653 personal wood dust measurements collected between 1978 and 2007 in Denmark, Finland, France, The Netherlands, Norway, and the United Kingdom (UK) was established. Measurement data were adjusted for differences in inhalable dust sampling efficiency resulting from the use of different dust samplers and analysed using linear mixed effect regression with job codes (ISCO-88) and country treated as random effects. Fixed effects were the year of measurement, the expert assessment of exposure intensity (no, low, and high exposure) for every ISCO-88 job code from an existing wood dust JEM and sampling duration. The results of the models suggest that wood dust exposure has declined annually by approximately 8%. Substantial differences in exposure levels between countries were observed with the highest levels in the United Kingdom and the lowest in Denmark and Norway, albeit with similar job rankings across countries. The jobs with the highest predicted exposure are floor layers and tile setters, wood-products machine operators, and building construction labourers with geometric mean levels for the year 1997 between 1.7 and 1.9 mg/m3. The predicted exposure estimates by the model are compared with the results of wood dust measurement data reported in the literature. The model predicted estimates for full-shift exposures were used to develop a time-dependent quantitative JEM for exposure to wood dust that can be used to estimate exposure for participants of general population studies in Northern European countries on the health effects from occupational exposure to wood dust. [ABSTRACT FROM AUTHOR]
Copyright of Annals of Work Exposures & Health 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.)
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  Data: Development of a quantitative North and Central European job exposure matrix for wood dust.
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  Data: <searchLink fieldCode="AR" term="%22Basinas%2C+Ioannis%22">Basinas, Ioannis</searchLink><relatesTo>1,2,3</relatesTo><i> ioannis.basinas@manchester.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Liukkonen%2C+Tuula%22">Liukkonen, Tuula</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Sigsgaard%2C+Torben%22">Sigsgaard, Torben</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Andersen%2C+Nils+T%22">Andersen, Nils T</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Vestergaard%2C+Jesper+M%22">Vestergaard, Jesper M</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Galea%2C+Karen+S%22">Galea, Karen S</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Tongeren%2C+Martie+van%22">Tongeren, Martie van</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wiggans%2C+Ruth%22">Wiggans, Ruth</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Savary%2C+Barbara%22">Savary, Barbara</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Eduard%2C+Wijnand%22">Eduard, Wijnand</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Kolstad%2C+Henrik+A%22">Kolstad, Henrik A</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Vested%2C+Anne%22">Vested, Anne</searchLink><relatesTo>3,5</relatesTo><br /><searchLink fieldCode="AR" term="%22Kromhout%2C+Hans%22">Kromhout, Hans</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Schlünssen%2C+Vivi%22">Schlünssen, Vivi</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Annals+of+Work+Exposures+%26+Health%22">Annals of Work Exposures & Health</searchLink>. Jul2023, Vol. 67 Issue 6, p758-771. 14p.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Dust%22">Dust</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+materials%22">Construction materials</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+exposure%22">Occupational exposure</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Population+geography%22">Population geography</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Netherlands%22">Netherlands</searchLink><br /><searchLink fieldCode="DE" term="%22United+Kingdom%22">United Kingdom</searchLink><br /><searchLink fieldCode="DE" term="%22France%22">France</searchLink><br /><searchLink fieldCode="DE" term="%22Denmark%22">Denmark</searchLink><br /><searchLink fieldCode="DE" term="%22Finland%22">Finland</searchLink><br /><searchLink fieldCode="DE" term="%22Norway%22">Norway</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Wood dust is an established carcinogen also linked to several non malignant respiratory disorders. A major limitation in research on wood dust and its health effects is the lack of (historical) quantitative estimates of occupational exposure for use in general population-based case-control or cohort studies. The present study aimed to develop a multinational quantitative Job Exposure Matrix (JEM) for wood dust exposure using exposure data from several Northern and Central European countries. For this, an occupational exposure database containing 12653 personal wood dust measurements collected between 1978 and 2007 in Denmark, Finland, France, The Netherlands, Norway, and the United Kingdom (UK) was established. Measurement data were adjusted for differences in inhalable dust sampling efficiency resulting from the use of different dust samplers and analysed using linear mixed effect regression with job codes (ISCO-88) and country treated as random effects. Fixed effects were the year of measurement, the expert assessment of exposure intensity (no, low, and high exposure) for every ISCO-88 job code from an existing wood dust JEM and sampling duration. The results of the models suggest that wood dust exposure has declined annually by approximately 8%. Substantial differences in exposure levels between countries were observed with the highest levels in the United Kingdom and the lowest in Denmark and Norway, albeit with similar job rankings across countries. The jobs with the highest predicted exposure are floor layers and tile setters, wood-products machine operators, and building construction labourers with geometric mean levels for the year 1997 between 1.7 and 1.9 mg/m3. The predicted exposure estimates by the model are compared with the results of wood dust measurement data reported in the literature. The model predicted estimates for full-shift exposures were used to develop a time-dependent quantitative JEM for exposure to wood dust that can be used to estimate exposure for participants of general population studies in Northern European countries on the health effects from occupational exposure to wood dust. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Annals of Work Exposures & Health 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:
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    Identifiers:
      – Type: doi
        Value: 10.1093/annweh/wxad021
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 758
    Subjects:
      – SubjectFull: Dust
        Type: general
      – SubjectFull: Construction materials
        Type: general
      – SubjectFull: Occupational exposure
        Type: general
      – SubjectFull: Regression analysis
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      – SubjectFull: Population geography
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Research funding
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      – SubjectFull: Netherlands
        Type: general
      – SubjectFull: United Kingdom
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      – SubjectFull: France
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      – SubjectFull: Denmark
        Type: general
      – SubjectFull: Finland
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      – SubjectFull: Norway
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      – TitleFull: Development of a quantitative North and Central European job exposure matrix for wood dust.
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              Text: Jul2023
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