Technological advancements in exposure assessment, a necessary component of intervention, control, and compliance, have recently increased the accuracy, reliability, and affordability of portable, direct-reading monitors. These monitors can rapidly assess worker exposures to occupational hazards. By coupling the estimated exposure with a known location, an industrial hygienist has the ability to connect exposures to specific sources. Contour plots of the hazard concentration over space, known as concentration maps, have recently been used to assess the spatial variability of hazards. Concentration maps have the potential to be powerful because they are easily comprehensible for managers, exposed employees, and occupational health scientists to locate areas of concern. Reducing or eliminating exposures in these areas will improve worker health. While we believe there is great potential for direct-reading instruments to aid in the identification and mitigation of workplace exposure hazards, it can be dangerous to apply such a methodology without understanding the uncertainties associated with this new form of exposure assessment. To date, no statistical framework has been applied to these maps. The goal of this project is to evaluate several statistical approaches 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 build reliable 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 for noise level and aerosol concentration exposures. Third, we will generate a reference concentration map from the high temporal and spatial resolution dataset, against which we may evaluate simpler statistical models.
The primary purpose of exposure assessment is to identify and prevent workplace conditions likely to cause adverse health outcomes. Exposure assessment methods rely on the ability to make quantitative measurements of health hazards. Advancements in technology have allowed for direct-reading instruments to be used to assess temporal variability of hazards at lower costs than ever before. Recently, there has been an effort to use such instruments to map hazard concentrations indoors. However, statistical methods have not been applied to determine the uncertainty associated with such techniques. Adapting methods from the air pollution literature, the implementation of a statistical model to produce maps of hazard concentration and uncertainties will aid industrial hygiene practitioners in making informed decisions on protecting worker health.
|Lake, Kirk; Zhu, Jun; Wang, Haonan et al. (2015) Effects of data sparsity and spatiotemporal variability on hazard maps of workplace noise. J Occup Environ Hyg 12:256-65|
|Koehler, Kirsten A; Peters, Thomas M (2013) Influence of analysis methods on interpretation of hazard maps. Ann Occup Hyg 57:558-70|