Silica Exposure During Construction Activities: Statistical Modeling of Task-Based Measurements from the Literature.

Many construction activities can put workers at risk of breathing silica containing dusts, and there is an important body of literature documenting exposure levels using a task-based strategy. In this study, statistical modeling was used to analyze a data set containing 1466 task-based, personal res...

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Publicado en:Annals of Occupational Hygiene Vol. 57; no. 4; pp. 432 - 444
Autores principales: Sauvé, Jean-François, Beaudry, Charles, Bégin, Denis, Dion, Chantal, Gérin, Michel, Lavoué, Jérôme
Formato: equations & formulas research tables/charts Journal Article
Publicado: Oxford University Press / USA May2013
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2013
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      pub: Oxford University Press / USA
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        atl: Silica Exposure During Construction Activities: Statistical Modeling of Task-Based Measurements from the Literature.
      aug:
        au:
          Sauvé, Jean-François
          Beaudry, Charles
          Bégin, Denis
          Dion, Chantal
          Gérin, Michel
          Lavoué, Jérôme
        affil: Université de Montréal, Department of Environmental and Occupational Health , Montréal, Québec, Canada ;
      sug:
        subj:
          Silicates Adverse Effects
          Occupational Hazards Standards
          Task Performance and Analysis Methods
          Air Pollution Analysis
          Work Environment
          Construction Industry
          Models, Statistical
          Data Analysis, Statistical
          Descriptive Statistics
          Data Analysis Software
          Confidence Intervals
          Funding Source
          Human
      ab: Many construction activities can put workers at risk of breathing silica containing dusts, and there is an important body of literature documenting exposure levels using a task-based strategy. In this study, statistical modeling was used to analyze a data set containing 1466 task-based, personal respirable crystalline silica (RCS) measurements gathered from 46 sources to estimate exposure levels during construction tasks and the effects of determinants of exposure. Monte–Carlo simulation was used to recreate individual exposures from summary parameters, and the statistical modeling involved multimodel inference with Tobit models containing combinations of the following exposure variables: sampling year, sampling duration, construction sector, project type, workspace, ventilation, and controls. Exposure levels by task were predicted based on the median reported duration by activity, the year 1998, absence of source control methods, and an equal distribution of the other determinants of exposure. The model containing all the variables explained 60% of the variability and was identified as the best approximating model. Of the 27 tasks contained in the data set, abrasive blasting, masonry chipping, scabbling concrete, tuck pointing, and tunnel boring had estimated geometric means above 0.1mg m−3 based on the exposure scenario developed. Water-fed tools and local exhaust ventilation were associated with a reduction of 71 and 69% in exposure levels compared with no controls, respectively. The predictive model developed can be used to estimate RCS concentrations for many construction activities in a wide range of circumstances.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
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        Journal Article
      ougenre: Article
    language: English
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