Society For Risk Analysis Annual Meeting 2017

Session Schedule & Abstracts


* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

T3-D
Cumulative Risk Assessment

Room: Salon D   1:30 pm–3:10 pm

Chair(s): Kristen Spicer   kspicer@murraystate.edu

Sponsored by Occupational Health and Safety and Dose Response Specialty Groups



T3-D.1  1:30 pm  Implications of applying cumulative risk assessments to the workplace. Fox MA, Spicer KE*, Susi P, Chosewood LC, Johns DO, Dotson GS; Johns Hopkins University, Murray State University, Avanti Industrial Hygiene, and The National Institute for Occupational Safety and Health   kspicer@murraystate.edu

Abstract: There are many changes influencing work, workplaces and workers in the US. Broad changes in the economy have caused shifts in the main types of work from manufacturing to services. Other industries, such as construction, remain important but demographics, tools, processes, materials and the way work is organized is changing and will likely continue to change. Work and workplace changes have tracked with a decline in unions and associated advocacy for improved safety and health conditions. Risk assessment has been the primary method to inform occupational and environmental health policy and management for many types of hazards. Although developed and applied typically to address one hazard at a time, risk assessment frameworks and methods have advanced toward cumulative risk assessment (CRA) recognizing that exposures to a single chemical or non-chemical stressor rarely occur in isolation in the ambient environment or the workplace. To date, CRA has been primarily applied to address exposures in the ambient and social environments to evaluate ecological or general population health. Little attention has been paid to the impacts of cumulative risks in occupational environments. We explore: 1) how CRA approaches may change the roles of workers and employers as they pursue improved health and safety; 2) barriers and benefits to adoption of the CRA approach among workers; and 3) the challenges and opportunities that might arise for employers with adoption of a CRA approach. Application of CRA should result in better understanding of complex exposures, health risks and related modifying factors, with the possibility of attributing risk across multiple domains. Addressing exposures in this comprehensive manner should lead to the development of more effective controls and improved safety and health risk management overall. A range of policy and practice options to address the barriers and challenges identified are presented.

T3-D.2  1:50 pm  A Prelude to a Cumulative Risk Assessment: Qualitative Analysis of Work-Related Asthma among Healthcare Workers. Johns DO*, Virji MA, Park JH, MacDonell MM, Cox-Ganser JM; Centers for Disease Control and Prevention and Argonne National Laboratory   djohns@cdc.gov

Abstract: Workers in the United States and throughout the world are exposed daily to combinations of chemical, biological, physical and psychosocial stressors specific to their occupation. Recently, there has been a formal effort by some within the occupational health community to expand the integration of components of cumulative risk assessment into the occupational domain, and to encourage the inclusion of occupational risk factors in community-based cumulative risk assessments. However, attempting to characterize, either quantitatively or qualitatively, the health effects resulting from complex interactions among chemical and nonchemical occupational and non-occupational stressors is, in many cases, simply impractical. Nonetheless, efforts to encourage the consideration of multiple key stressors in human health risk assessments in occupational settings will greatly inform the development of strategies to efficiently reduce exposures of greatest concern, and may establish the information needed to conduct formal quantitative cumulative risk assessments. Factors to be considered in prioritizing targeted stressors include the number of individuals exposed, known health outcomes resulting from these exposures, and the level of understanding of the mode of action of the stressors of interest. As an example of such an evaluation, an effect-based approach was utilized to identify two key and common stressors among healthcare workers associated with work-related asthma: work-related stress and occupational exposure to chemical disinfectants. This approach is described and highlights the benefit of undertaking less complex, targeted assessments to illustrate the concepts, toward ultimately having greater impact and serving to advance practical applications of cumulative risk assessment. Disclaimer: The views expressed are those of the authors and do not necessarily represent the views or policies of the National Institute for Occupational Safety and Health.

T3-D.3  2:10 pm  Exploring Categorical Occupational Exposure Limits with a Quantitative Framework to Group Nanoscale and Microscale Particles by Hazard Potency. Drew NM*, Kuempel ED, Pei Y, Yang F; National Institute for Occupational Safety and Health   vom8@cdc.gov

Abstract: The large and rapidly growing number of engineered nanomaterials (ENMs) presents a challenge to assessing the potential occupational health risks. An initial database of 25 rodent studies including 1,929 animals across various experimental designs and material types was constructed to identify materials that are similar with respect to their potency in eliciting neutrophilic pulmonary inflammation, a response relevant to workers. Doses were normalized across rodent species, strain, and sex as the estimated deposited particle mass dose per gram of lung. Doses associated with specific measures of pulmonary inflammation were estimated by modeling the continuous dose-response relationships using benchmark dose modeling. Hierarchical clustering was used to identify similar materials. The 18 nanoscale and microscale particles were classified into four potency groups, which varied by factors of approximately two to 100. Benchmark particles microscale TiO2 and crystalline silica were in the lowest and highest potency groups, respectively. Random forest methods were used to identify the important physicochemical predictors of pulmonary toxicity, and group assignments were correctly predicted for five of six new ENMs. Proof-of-concept was demonstrated for this framework, although more comprehensive data are needed for further development and validation for use in deriving categorical occupational exposure limits.

T3-D.4  2:30 pm  Why many field-based toxicity thresholds are unreliable: Statistical artifacts affecting causal inference. Kashuba RO*, Menzie CA, Buonagurio JE; Exponent   rkashuba@exponent.com

Abstract: Environmental biomonitoring involves sampling biological media or communities in the field. By design, these samples are composed of mixtures of taxa or chemicals. The individual taxa or chemicals which comprise these mixtures, however, are sampled disproportionately. Some taxa or chemicals may be present in a sample much more often than rarer mixture components. Because sample size affects the accuracy of summary statistics, disproportionate sampling across mixture components affects derivation of stressor thresholds from these samples. The smaller the sample size, the more uncertainty there is in inferences made from that sample, and the more likely it is to calculate an extreme (i.e., very high or very low) estimate of a summary parameter attempting to characterize the sub-population of that mixture component. This is due solely to random chance and the properties of statistical inference. When such monitoring datasets composed of mixtures are used to calculate distribution summary statistics for individual mixture components, the concern is that differences in sample sizes among components create statistical artifacts misinterpreted as meaningful and accurately quantified relationships between chemical stressor levels and biological community response. This may cause some taxa to appear tolerant or intolerant by chance, which affects assignment of toxic effects thresholds. We demonstrate the effect of disproportionate sample size among groups on threshold calculation via mathematical simulation in concert with examining several existing water and sediment quality criteria examples. This shows that statistical artifacts present in field samples can suggest unreliable relationships, pointing to a need for multiple, different lines of evidence in the development of causally reliable regulatory guidelines for environmental stressors.



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