Technological advancements in exposure assessment, a necessary component of intervention, control, andcompliance, have recently increased the accuracy, reliability, and affordability of portable, direct-readingmonitors. These monitors can rapidly assess worker exposures to occupational hazards. By coupling theestimated exposure with a known location, an industrial hygienist has the ability to connect exposures tospecific sources. Contour plots of the hazard concentration over space, known as concentration maps, haverecently been used to assess the spatial variability of hazards. Concentration maps have the potential to bepowerful because they are easily comprehensible for managers, exposed employees, and occupational healthscientists to locate areas of concern. Reducing or eliminating exposures in these areas will improve workerhealth. While we believe there is great potential for direct-reading instruments to aid in the identification andmitigation of workplace exposure hazards, it can be dangerous to apply such a methodology withoutunderstanding the uncertainties associated with this new form of exposure assessment. To date, no statisticalframework has been applied to these maps. The goal of this project is to evaluate several statisticalapproaches for the analysis of workplace exposure data collected with direct-reading instruments.There are three specific aims for this project. First, we will employ a spatial statistical mapping method to buildreliable mapped exposure estimates and confidence intervals using a previously collected exposure dataset.Second, we will collect a comprehensive dataset of hazard concentration as a function of time and space fornoise level and aerosol concentration exposures. Third, we will generate a reference concentration map fromthe high temporal and spatial resolution dataset, against which we may evaluate simpler statistical models.

Agency
National Institute of Health (NIH)
Institute
National Institute for Occupational Safety and Health (NIOSH)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
3K01OH009886-04S1
Application #
8812293
Study Section
Safety and Occupational Health Study Section (SOH)
Program Officer
Dearwent, Steve
Project Start
2013-08-24
Project End
2014-08-31
Budget Start
2013-08-24
Budget End
2014-08-31
Support Year
Fiscal Year
2013
Total Cost
$19,547
Indirect Cost
$1,563
Name
Johns Hopkins University
Department
Type
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Koehler, Kirsten A; Peters, Thomas M (2013) Influence of analysis methods on interpretation of hazard maps. Ann Occup Hyg 57:558-70