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SRA 2013 Annual Meeting Abstracts M2-E.4 Wu, F*; Liu, Y; Michigan State University; fwu@msu.edu Aflatoxin and cyanide: Global burden of disease Aflatoxin is a toxin produced by certain Aspergillus fungi that infect food crops, particularly corn, peanuts, and tree nuts (pistachios, hazelnuts, almonds, walnuts, etc.). It is the most potent naturally occurring human liver carcinogen known, and is particularly a danger in the parts of the world where corn and peanuts are dietary staples. We present our estimates of the global burden of human liver cancer caused by aflatoxin, and discuss the potential role of aflatoxin exposure in causing childhood stunting. Finally, we give a brief discussion of cyanide in cassava, its adverse effects, and the populations most at risk worldwide. P.73 Wu, CH*; Huang, YF; Wu, KY; National Taiwan University; charlenehwu@gmail.com Assessing the Health Risks of Dimethylformamide in an Occupational Setting Dimethylformamide (DMF) is an organic compound able to induce adverse health effects in humans. It is used in the production of pharmaceutical products, adhesives, and synthetic leathers. Employees working in these industries are likely to be at risk, particularly through inhalation and dermal absorption. Exposure assessment of DMF was conducted on 106 employees from three synthetic leather plants in Taiwan. The employees’ urinary samples were collected and subsequently analyzed. N-methylformamide (NMF), a DMF metabolite, is the biomarker identified to measure the body burden of DMF exposure. Results demonstrated that NMF concentrations from the majority of urinary samples collected prior to a work shift were mostly undetectable. However, urinary concentrations of NMF were significantly higher post-shift compared to pre-shift. Of the 318 urinary samples collected, the NMF concentrations in 59 samples exceeded the American Conference of Industrial Hygienists’ (ACHIH) recommended Biological Exposure Index (BEI) of 15mg/L. To assess the health risks of DMF, the reference concentrations (RfC) were calculated using the Benchmark Dose software. The benchmark dose, based on existing animal data, is calculated at 3.98 ppm (11.94 mg/m3). Based on this BMDL10, the RfC for DMF in these synthetic leather plants is derived at 0.04 ppm (0.12 mg/m3). The hazard indices for all 106 employees (HI) were also calculated and found that 89.6% of the employees have a HI value greater than one. Our results demonstrate that the majority of employees exposed to DMF are subject to noncarcinogenic adverse health effects, even though the amount of DMF exposure does not exceed current permissible exposure limits (PELs) of 10ppm. Further investigation focusing on the exposure to multiple compounds in these occupational settings is warranted. A review of risk management protocol of DMF should be considered since compliance with current regulations is inadequate in safeguarding health. P.70 Wu, KY*; Chung, YC; Chen, CC; Hsiao, CH; National Taiwan University; kuenyuhwu@ntu.edu.tw Probabilistic Risk Assessment with the Bayesian Statistics Markov Chain Monte Carlo Simulation US EPA already adopted probabilistic risk assessment (PRA) for decision making. Previously, PRA was conducted by mainly using the Monte Carlo (MC) simulation, which frequently requires either empirical or probability distributions of parameters to simulate the distribution of lifetime daily dose. The simulation results will be valid if only the input parameters, data and assumptions are valid. In practice, risk assessors frequently suffered from insufficient data to fit distributions for some parameters, especially concentrations and intake rates, or even worse spotted data hinder completion of an assessment, such as a large proportion of residue data below detection limit. In order to reduce uncertainty due to insufficient data, the Bayesian statistics Markov chain Monte Carlo (MCMC) simulation was applied to perform PRA. The limited data available were used as prior information. Markov chain Monte Carlo simulation was performed with the WinBUG to achieve the posterior distributions of parameters and health risk. Four examples will be presented in this meeting; assessment of lifetime cancer risk for N-nitrosodimethylamine (NDMA) in drinking water (only one sample with detectable NDMA level out of 50 samples collected), assessment of lifetime cancer risk for aflatoxin B1 in food (only few data greater than regulations were available), assessment of health risk for medical staffs exposed to cisplatin by using urinary platinum as biomarker to reconstruct exposures, and assessment of lifetime cancer risk for acrylamide in high-temperature processed foods with high uncertainty in residue and intake rate data. With limited data available, the posterior distributions of parameters and health risk theoretically converge to corresponding representative distributions for the study population so that quality of risk assessment may be improved without additional investment of resources to collect data. P.119 Wu, CY*; Chang, CH; Chung, YC; Chen, CC; Wu, KY; National Taiwan University; b97310020@ntu.edu.tw Probabilistic Assessment of Lifetime Cancer Risk for Acrylamide through Daily Consumption of High-Temperature Processed Foods in Taiwan with Bayesian Statistics Markov Chain Monte Carlo Simulation Acrylamide (AA), a probable carcinogen, present in foods, especially in carbohydrate-rich food processed at high temperature. The potential health risk has been of great concerns due to daily AA intakes which could vary geographically due to various dietary habits and cooking process. In order to assess the lifetime cancer risk, a variety of high-temperature processed foods were collected from several counties in Taiwan. Totally, AA contents in 300 samples were analyzed with liquid chromatography tandem mass spectrometry. Questionnaires were used to collect intakes of these foods from 132 study subjects. With the limited data on the AA contents and food intake rates, Bayesian statistics Markov chain Monte Carlo simulation was to perform probabilistic assessment of lifetime cancer risk for AA through consumption of high-temperature foods in Taiwan to estimate the representative distribution of daily AA intake. In this study, mean intakes doses is 1.655 micro-gram / kg-day for the samples. Use the cancer slope factor (0.51 [mg/kg-day] -1) of EPA(2010), the mean cancer risk for Taiwan population is 8.4410-4. The risk in our study is higher than those of other studies. This could be attributed to food intake rates probably overestimated according to surveys from young population. However, it may be necessary for the young study subjects to reduce the consumption of fried foods. December 8-11, 2013 - Baltimore, MD
SRA 2013 Annual Meeting Abstracts W2-H.2 Xu, J; Song, C; Zhuang, J, J*; University at Buffalo, SUNY; jzhuang@buffalo.edu Robust Screening Policy--Balancing Congestion and Security in the Presence of Strategic Applicants with Private Information Concerns on security and congestion appear in security screening which is used to identify and deter potential threats (e.g., attackers, terrorists, smugglers, spies) among normal applicants wishing to enter an organization, location, or facility. Generally, in-depth screening reduces the risk of being attacked, but creates delays that may deter normal applicants and thus, decrease the welfare of the approver (authority, manager, screener). In this research, we develop a model to determine the optimal screening policy to maximize the reward from admitting normal applicants net of the penalty from admitting bad applicants. We use an M/M/n queueing system to capture the impact of security screening policies on system congestion and use game theory to model strategic behavior, in which potential applicants with private information can decide whether to apply based on the observed approver's screening policy and the submission behavior of other potential applicants. We provide analytical solutions for the optimal non-discriminatory screening policy and numerical illustrations for both the discriminatory and non-discriminatory policies. In addition, we discuss more complex scenarios including robust screening, imperfect screening, abandonment behavior, and complex server networks. T2-I.1 XU, J*; Lambert, J.H.; University of Virginia; jx5aj@virginia.edu Addressing Uncertainties of Avoided Crash Risk, Travel Time Savings, and Lifecycle Costs in Transportation Access Management Access management in transportation planning can save travel time, reduce crashes, and increase route capacities. The literature suggests a need for performance metrics and a decision-aiding framework to guide access management programs across large corridor networks and diverse time horizons. This research discusses a quantitative framework to support access management programs decision making, applying multicriteria analysis and cost-benefit analysis with data and parameter uncertainties. The metrics used to assess relative needs at existing access points include: crash intensity, crash exposure, travel time delay factor, access point density, traffic exposure, value of time, costs of typical access management activities, etc. Uncertain data and parameters that influence the estimates of potential benefits and costs are identified and treated via a numerical interval analysis. The framework is demonstrated at several geographic scales and locations including six thousand miles of highways of a geographic region and its several sub-regions. The results assist decision makers to find from various perspectives which route segments should be addressed sooner by collection of additional data, reserving right of way, closing access points, new alignments, development proffers, etc. The methods combing uncertainty analysis, multicriteria analysis, and cost-benefit analysis should be interest to engineers, policymakers, and stakeholders engaged in the strategic planning of access management and other multiscale systems, and are transferable to other topics involving cost-benefit analysis under uncertainty, evidence-based decision aids, strategic resource allocation, and others. T1-E.2 Yan, Z*; Zhao, Q; ORISE; yan.june@epa.gov Toxicity Review of Technical Grade Dinitrotoluene And Identification of its Critical Effects Technical grade dinitrotoluene (tgDNT) is a mixture of dinitrotoluene isomers. It is composed of 76% 2,4 DNT and 19% 2,6 DNT. The toxicological effects of tgDNT were reviewed and the critical effects were identified by evaluating available human occupational and animal studies mainly via inhalation and oral exposure routes. In occupational studies of workers from DNT manufacturing plants, tgDNT exposure (predominately via the inhalation route) associates with clinical symptoms, adverse reproductive effects, adverse effects on the cardiovascular system, and increased carcinogenic risk. However, these occupational studies are limited due to co-exposure to other known and/or unknown chemicals and lack of useful exposure information. Oral studies in F344 rats showed that tgDNT has a broad toxicity profile in both males and females including significantly increased reticulocytes and Heinz bodies, increased relative liver weight and kidney weight, spleen hemosiderin and extramedullary hematopoiesis, increased incidence of chronic interstitial nephritis, and hepatotoxicity characterized by increased incidences of hepatocyte necrosis, hyperbasophilic hepatocytes, and hepatocyte megalocytosis. The incidence of testicular degeneration in male rats is also significantly increased by tgDNT. In order to identify the most sensitive non-cancer effect(s), all toxicological endpoints from subchronic, chronic, and reproductive/developmental studies were evaluated and dose response data were modeled using EPA’s Benchmark Dose Software. A comparison of the points of departure for all potential critical effects suggests increased hepatocyte necrosis is the most sensitive effect and is thus considered the critical effect following subchronic and chronic oral exposure. In summary, tgDNT elicits a broad spectrum of non-cancer effects, among which hepatocyte necrosis was identified as the most sensitive effect. The views expressed in this abstract are those of the authors and do not necessarily reflect the views or policies of the U.S. EPA. T4-G.2 Yang, ZJ; Rickard, L.*; Seo, M.; Harrison, T.; University at Buffalo, SUNY College of Environmental Science and Forestry, University at Albany; zyang5@buffalo.edu The “I” in climate: The role of individual responsibility in systematic processing of climate change information Past research suggests that how we perceive risk can be related to how we attribute responsibility for risk events. In particular, Kahlor, Dunwoody, and Griffin (2002) found that individuals who successfully avoided becoming ill from a waterborne parasite were more likely to attribute the outcome to their own actions, while those who fell ill were more likely to attribute causation externally. With the exception of this study, a substantial gap in research lies in the lack of connection between attribution of responsibility, risk perception, and information processing. This study fills this gap by examining whether attribution of responsibility for alleviating a risk issue influences communication behaviors that are often predicted by elevated risk perceptions. In Spring 2013, 572 undergraduates at two large research universities were randomly assigned to read one of two newspaper articles that emphasized either individual responsibility (by highlighting personal actions) or societal responsibility (by highlighting government policy) for climate change mitigation. Results from this experiment indicate that subjects in the individual responsibility condition were significantly more likely to process the message in a systematic manner. In addition, respondents with more ecocentric environmental attitudes, more negative feelings toward the impacts of climate change, and more favorable attitudes toward climate change information in general were also more likely to process the message systematically; however, attribution of responsibility did not interact with risk perception to influence systematic processing. Interestingly, respondents who identified as Christian (including Protestants, Catholics, and other denominations) were also more likely to process climate change information systematically. These findings suggest that strategic communication about climate change can emphasize individual responsibility to attract more attention from the audience and to promote deeper thinking about the issue. December 8-11, 2013 - Baltimore, MD
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