Abstract No:
1720
Abstract Type:
Professional Poster
Authors:
M Virji1
Institutions:
1NIOSH, N/A
Presenter:
M. Abbas Virji
NIOSH
Description:
Peak exposures from workplace hazards can overwhelm the body's normal defense mechanisms and induce adverse health effects; however, there is a lack of a framework for evaluating such excursions based on real-time exposure data. This presentation will address several aspects of peak exposures including definitions, exposure limits, toxicological and exposure factors influencing peaks, and calculating a variety of peak exposure metrics from real-time data.
Situation / Problem:
Peak exposures (high-intensity exposures over short-duration) can overwhelm the body's normal defense mechanisms and induce adverse health effects, which may be more severe or different from the effects of chronic or average exposures. However, epidemiologic and exposure literature lack consensus on how to define peaks because relevant peak metrics depend upon exposure patterns, kinetics of the exposure substance, health outcomes of interest, and disease mechanisms. Consequently, peak exposure metrics are often overlooked in epidemiologic studies, defaulting to average or cumulative exposure metrics instead. Use of less relevant metrics can lead to exposure misclassification or systematic error and missed associations. In industrial hygiene, peaks are considered in terms of compliance with ceiling or short-term exposure limits (STEL); however, criteria for evaluating such excursions based on real-time exposure data is lacking. Real-time data are often presented graphically highlighting periods of excursions associated with job tasks, but quantitative analysis is not performed. A framework for summarizing exposure time-series data can help define standardized peak metrics, ensuring a consistent approach to data analysis and developing effective sampling strategies.
Methods:
In this work, a toxicologic approach is used to define a biologically relevant peak including drawing a baseline, choosing an averaging period, identifying the time interval between peaks, and selecting a peak height. An array of exposure metrics can be generated once a peak is defined such as (1) number of peaks, (2) peak duration, (3) peak concentration (maximum or average), (4) ratio of maximum to average peak exposure, (5) time between peaks (average, minimum, maximum), and (6) cumulative peak exposure, together reflecting different aspects of peaks such as its variability or intensity or "peakiness". Analyzing the exposure time-series in the frequency domain (as opposed to the time domain typically used in time-series analysis) can reveal patterns of peak occurrences which is important in evaluating biological recovery time. If work processes and tasks are observed during monitoring, advanced regression methods that account for non-stationary autocorrelation and other data structures can be used to directly understand the impact of those factors on exposure. For comparison to STEL, rolling average and the 95th percentile over a relevant time interval can be plotted to display compliance with any short-term limits. Although biological recovery time between peak exposures can be a factor in subsequent toxicologic effects, the number of peaks and interval between peaks that is permissible within a work shift is often ignored. The utility of these six peak exposure metrics will be exemplified in a dataset of real-time carbon monoxide measurements collected during coffee manufacturing.
Results / Conclusions:
There is little consensus in scientific literature in defining peak characteristics such as intensity, duration, interval between peaks, frequency, and aggregation of peaks. Approaches to characterize and define peak exposures based on the disease mechanism, kinetics of the exposure substance, and exposure characteristics may generate biologically relevant metrics. This work identified factors that influence peak exposures and their definition, and the creation of peak metrics. Important messages from this work include: 1) peak exposure are important for both acute and chronic effects, 2) a framework for defining peak exposure will help in devising sampling strategies, 3) incorporating toxicology is key to developing a biologically relevant definition of peaks and a sampling strategy, 4) a single definition of peak exposure is likely not useful – consistency is achieved by systematically applying all the factors that affect dose and peaks, 5) artificial intelligence and machine learning methods can help identify patterns in exposure. Peak metrics grounded in toxicology and exposure characteristics will improve our understanding of exposure-response relationships and the development of effective intervention strategies.
Core Competencies:
Exposure Assessment
Secondary Core Competencies:
Biostatistics and Epidemiology
Toxicology / Human Disease
Choose at least one (1), and up to five, (5) keywords from the following list. These selections will optimize your presentation's search results for attendees.
Exposure Assessment
Occupational epidemiology
Real-time detection services and direct reading instruments
Based on the selected primary competency area of your proposal, select one group below that would be best suited to serve as a subject matter expert for peer review:
(Select one)
Exposure Assessment Strategies Committee
Based on the information that will be presented during your proposed session, please indicate the targeted audience practice level: (select one)
Professional: Professional is a job title given to persons who have obtained a baccalaureate or graduate degree in IH/OH, public health, safety, environmental sciences, biology, chemistry, physics, or engineering or who have a degree in another area that meets the standards set forth in the next section, Knowledge and Skill Sets of IH/OH Practice Levels, and has had 4 or more years of practice. One significant way of demonstrating professional competence is to achieve certification by a 3rd party whose certification scheme is recognized by the International Occupational Hygiene Association (IOHA) such as the Board of Global EHS Credentialing (BGC).
Was this session organized by an AIHA Technical Committee, Special Interest Group, Working Group, Advisory Group or other AIHA project Team?
No
Are worker exposure data and/or results of worker exposure data analysis presented?
Yes
If yes, i.e., If worker exposure data and/or results of worker exposure data analysis are to be presented please describe the statistical methods and tools (e.g. IHSTAT, Expostats, IHSTAT_Bayes, IHDA-AIHA, or other statistical tool, please specify) used for analysis of the data.
"R - Bayesian exposure time series analysis R/SAS - Analysis of time series in frequency domain Python/Excel - identification of peaks from time series data"
How will this help advance the science of IH/OH?
This presentation will address several aspects of peak exposures including definitions, exposure limits, toxicological and exposure factors influencing peaks, and calculating a variety of peak exposure metrics from real-time data.
What level would you consider your presentation content geared towards?
Advanced: Specific topic within a subject in great detail. May cover current issues, involve complex calculations, analysis and synthesis, or evaluations/assessments of real-life scenarios Participant must have ten (10) or more years of experience in industrial hygiene or OEHS. Prerequisites required: working knowledge of the specific topic before the course.
Have you presented this information before?
No
I have read and agree to these guidelines.
Yes