Document Detail

Measurement error and model specification in determining how duration of tasks affects level of occupational exposure.
MedLine Citation:
PMID:  19188265     Owner:  NLM     Status:  MEDLINE    
Statistical modeling of determinants of exposure ascertained in large-scale surveys is an increasingly popular approach to both (i) identifying effective occupational exposure controls that arise in 'natural experiments' and (ii) predicting how altering some working conditions may impact exposure levels. This paper sheds light on two underappreciated methodological challenges of such studies. First, I examine the impact of measurement error in the observed determinant of exposure on an investigator's ability to correctly rank the determinants of exposure in terms of their exposure rate (one aspect of how important a give determinant is). Simultaneously, I consider the issue of whether empirical models fitted for the sake of statistical convenience actually reflect the physical reality that is being modeled and how this may affect the answer to the question about ranking determinants of exposure. These general issues are examined in the context of the 'time per task' determinant of exposure and true exposure model that states that exposure is equal to product of exposure rate and duration of a task. Simulation studies were conducted and their conclusions applied in re-examining the data on the impact of duration of some key task on exposure levels to flour dust among bakers. The simulation study demonstrated that bias due to measurement error in observed effects can be either positive or negative. The main conclusion is that the correct ranking of exposure rates can be obtained from both true and poorly specified exposure models, but can be severely distorted by errors in estimates of the duration of tasks performed.
Igor Burstyn
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Publication Detail:
Type:  Journal Article     Date:  2009-02-02
Journal Detail:
Title:  The Annals of occupational hygiene     Volume:  53     ISSN:  1475-3162     ISO Abbreviation:  Ann Occup Hyg     Publication Date:  2009 Apr 
Date Detail:
Created Date:  2009-03-30     Completed Date:  2009-05-14     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0203526     Medline TA:  Ann Occup Hyg     Country:  England    
Other Details:
Languages:  eng     Pagination:  265-70     Citation Subset:  IM    
Community and Occupational Medicine Program, Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
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MeSH Terms
Bias (Epidemiology)
Computer Simulation*
Environmental Monitoring / methods
Food Industry
Models, Statistical*
Occupational Exposure / statistics & numerical data*
Occupational Health
Risk Assessment / methods
Time Factors

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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