The Importance of Biological Realism in Dioxin Risk Assessment Models Michael

Mechanistic mathematical models of hepatocarcinogenesis in the female rat were constructed to investigate possible relationships among the Ah, estrogen, and EGF receptors in TCDD hepato-carcinogenicity. Each model generates dose-response curves for the expression of biomarker liver proteins CYP1A1, CYP1A2, and residual plasma membrane EGF receptor consequent to exposure to TCDD. The shapes of the response curves were strongly dependent on the assumed mechanisms of constitutive expression of these proteins. Assuming a constant level of the hepatic Ah receptor, a sigmoidal dose-response of hepatic CYP1A1 to total liver TCDD was computed. However, inclusion of induction of the Ah receptor by TCDD in a physiologically realistic dosimetric model produced a linear low-dose response of CYP1A1. This behavior was computed to arise from the net effect of sublinear response of CYP1A1 mRNA to the concentration of the Ah-TCDD complex and supralinear response of the protein concentration to the mRNA level, illustrating the importance of biological realism in dose-response modeling. The dosimetric model also computed effects of TCDD on the hepatic estradiol concentration and consequent effects on the binding capacity of the EGF receptor and suggests plausible mechanisms for tumor promotion by TCDD. Setting circulating estradiol levels in the model to values typical of the male rat indicated possible sources of the differences in the responses of the EGF receptor and in development of tumors in the two sexes.     

Connecticut's Dioxin Ambient Air Quality Standard

Connecticut is the first state in the country to have adopted an ambient air quality standard for dioxins at 1 pg/m³, 2,3,7,8-TCDD equivalents, as annual average. This paper describes the scientific basis and the methodology used by the State Department of Health Services (the risk assessment agency) in assisting the Department of Enviromental Protection (the risk management agency) to establish a health-based dioxin standard. This standard protects the public health from the aggregate effect of all sources of dioxin emissions in the vapor and particulate phases. The risk assessment methodology included: a limit on total daily dioxin exposure from all media and sources based on reproductive effects; a multimedia nonsource-specific exposure assessment; an apportionment by media of the health-based limit (including background dosing rate); an evaluation of inhalation bioavailability and cancer risk based on a calculation of a range of upperbound cancer risk estimates using different potency, bioavailability, and particle phase assumptions.     

Risk Assessment for Aflatoxin: An Evaluation Based on the Multistage Model

Lifetime cancer potency of alfatoxin was assessed based on the Yeh et al. study from China in which both aflatoxin exposure and hepatitis B prevalence were measured. This study provides the best available information for estimating the carcinogenic risk posed by aflatoxin to the U.S. population. Cancer potency of aflatoxin was estimated using a biologically motivated risk assessment model. The best estimate of aflatoxin potency was 9 (mg/kg/day)⁻¹ for individuals negative for hepatitis B and 230 (mg/kg/day)⁻¹ for individuals positive for hepatitis B.     

Comparative Risk Analysis of Dioxins in Fish and Fine Particles from Heavy-Duty Vehicles

Dioxins and airborne fine particles are both environmental health problems that have been the subject of active public debate. Knowledge on fine particles has increased substantially during the last 10 years, and even the current, lowered levels in the Europe and in the United States appear to be a major public health problem. On the other hand, dioxins are ubiquitous persistent contaminants, some being carcinogens at high doses, and therefore of great concern. Our aim was to (a) quantitatively analyze the two pollutant health risks and (b) study the changes in risk in view of the current and forthcoming EU legislations on pollutants. We performed a comparative risk assessment for both pollutants in the Helsinki metropolitan area (Finland) and estimated the health effects with several scenarios. For primary fine particles: a comparison between the present emission situation for heavy-duty vehicles and the new fine particle emission standards set by the EU. For dioxins: an EU directive that regulates commercial fishing of Baltic salmon and herring that exceed the dioxin concentration limit set for fish meat, and a derogation (= exemption) from the directive for these two species. Both of these two decisions are very topical issues and this study estimates the expected changes in health effects due to these regulations. It was found that the estimated fine particle risk clearly outweighed the estimated dioxin risk. A substantial improvement to public health could be achieved by initiating reductions in emission standards; about 30 avoided premature deaths annually in the study area. In addition, the benefits of fish consumption due to omega-3 exposure were notably higher than the potential dioxin cancer risk. Both regulations were instigated as ways of promoting public health.     

Transgenic Mice as Future Tools in Risk Assessment

Historically, mice have served a routine and useful purpose in the research, development, and testing of biologicals, chemicals, and drugs for efficacy, toxicity, and carcinogenic risk. The literature is replete with examples using mice to study organic compounds both in short-term tests involving tumor initiation and promotion and in long-term experiments dealing with fertility, reproduction, and teratology. During the past two decades, a virtual explosion of advances has occurred in modern biology that includes the discoveries of retroviruses, oncogenes, DNA restriction enzymes, nucleotide sequence analyses, and microinjection techniques. Fusion of these milestones in genetic, molecular, and cell biology with recent developments in mouse embryology has opened novel avenues and methods of experimentation as significant additions to the risk assessment armamentarium that currently uses both prokaryotes and eukaryotes. Some promising directions afforded by transgenic mice as powerful future tools in risk assessment will be summarized below.     

Quantitative Assessment of the Risk of Lung Cancer Associated with Occupational Exposure to Refractory Ceramic Fibers

We present the results of a quantitative assessment of the lung cancer risk associated with occupational exposure to refractory ceramic fibers (RCF). The primary sources of data for our risk assessment were two long-term oncogenicity studies in male Fischer rats conducted to assess the potential pathogenic effects associated with prolonged inhalation of RCF. An interesting feature of the data was the availability of the temporal profile of fiber burden in the lungs of experimental animals. Because of this information, we were able to conduct both exposure–response and dose–response analyses. Our risk assessment was conducted within the framework of a biologically based model for carcinogenesis, the two-stage clonal expansion model, which allows for the explicit incorporation of the concepts of initiation and promotion in the analyses. We found that a model positing that RCF was an initiator had the highest likelihood. We proposed an approach based on biological considerations for the extrapolation of risk to humans. This approach requires estimation of human lung burdens for specific exposure scenarios, which we did by using an extension of a model due to Yu. Our approach acknowledges that the risk associated with exposure to RCF depends on exposure to other lung carcinogens. We present estimates of risk in two populations: (1) a population of nonsmokers and (2) an occupational cohort of steelworkers not exposed to coke oven emissions, a mixed population that includes both smokers and nonsmokers.     

A Comparison of Methods for Estimating the Benchmark Dose Based on Overdispersed Data from Developmental Toxicity Studies

Developmental anomalies resulting from prenatal toxicity can be manifested in terms of both malformations among surviving offspring and prenatal death. Although these two endpoints have traditionally been analyzed separately in the assessment of risk, multivariate methods of risk characterization have recently been proposed. We examined this and other issues in developmental toxicity risk assessment by evaluating the accuracy and precision of estimates of the effective dose ( ED ₀₅) and the benchmark dose ( BMD ₀₅) using computer simulation. Our results indicated that different variance structures (Dirichlet-trinomial and generalized linear model) used to characterize overdispersion yielded comparable results when fitting joint dose response models based on generalized estimating equations. (The choice of variance structure in separate modeling was also not critical.) However, using the Rao-Scott transformation to eliminate overdispersion tended to produce estimates of the ED ₀₅ with reduced bias and mean squared error. Because joint modeling ensures that the ED ₀₅ for overall toxicity (based on both malformations and prenatal death) is always less than the ED ₀₅ for either malformations or prenatal death, joint modeling is preferred to separate modeling for risk assessment purposes.     

The Interplay of Science, Values, and Experiences Among Scientists Asked to Evaluate the Hazards of Dioxin, Radon, and Environmental Tobacco Smoke

To investigate the extent to which personal values and experiences among scientists might affect their assessment of risks from dioxin, radon, and environmental tobacco smoke (ETS), we conducted an experiment through a telephone survey of 1461 epidemiologists, toxicologists, physicians, and general scientists. Each participant was read a vignette designed to reflect the mainstream scientific thinking on one of the three substances. For half of the participants (group A) the substance was named. For the other half (group B), the substance was not named but was identified only as Substance X, Y, or Z. Knowing the name of the substance had little effect on the scientists' evaluation of dioxin, although those who knew the substance to be dioxin were more likely to rate the substance as a serious environmental health hazard (51% vs. 42%, p = 0.062). For radon, those who knew the substance by name were significantly more likely to consider it an environmental health hazard than were those who knew it as substance Z (91% vs. 78%, p less than 0.001). Participants who knew they were being asked about ETS rather than substance X were significantly more likely to consider the substance an environmental health hazard (88% vs. 66%, p less than 0.001), to consider the substance a serious environmental health hazard (70% vs. 33%, p less than 0.001), to believe that background exposure required public health intervention (85% vs. 41%, p less than 0.001), and to believe that above-background exposure required public health intervention (90% vs. 74%, p less than 0.001). These findings suggest that values and experiences may be influencing health risk assessments for these substances, and indicate the need for more study of this phenomenon.     

Estimation of Human Exposure from Fish Contaminated with Dioxins and Furans Emitted by a Resource-Recovery Facility

Ingestion of contaminated fish can be an important human exposure pathway for dioxins and furans emitted from waste incineration plants. A new method for calculating fish contamination resulting from dioxin and furan emissions has been developed to overcome some of the problems of those currently used. The method is based on evidence that the major determinant of fish dioxin and furan uptake is sediment concentrations. Only two steps are necessary to calculate fish tissue levels. Step 1: Calculation of the concentration of dioxins and furans in particulate matter entering the lake or pond, and hence, the resulting sediment concentration. Step 2: Calculation of fish concentrations utilizing fish-to-sediment ratios for the various dioxin and furan isomers.     

The Benefits of Probabilistic Exposure Assessment: Three Case Studies Involving Contaminated Air,Water, and Soil1

Probabilistic risk assessments are enjoying increasing popularity as a tool to characterize the health hazards associated with exposure to chemicals in the environment. Because probabilistic analyses provide much more information to the risk manager than standard “point” risk estimates, this approach has generally been heralded as one which could significantly improve the conduct of health risk assessments. The primary obstacles to replacing point estimates with probabilistic techniques include a general lack of familiarity with the approach and a lack of regulatory policy and guidance. This paper discusses some of the advantages and disadvantages of the point estimate vs. probabilistic approach. Three case studies are presented which contrast and compare the results of each. The first addresses the risks associated with household exposure to volatile chemicals in tapwater. The second evaluates airborne dioxin emissions which can enter the food-chain. The third illustrates how to derive health-based cleanup levels for dioxin in soil. It is shown that, based on the results of Monte Carlo analyses of probability density functions (PDFs), the point estimate approach required by most regulatory agencies will nearly always overpredict the risk for the 95^th percentile person by a factor of up to 5. When the assessment requires consideration of 10 or more exposure variables, the point estimate approach will often predict risks representative of the 99.9^th percentile person rather than the 50^th or 95^th percentile person. This paper recommends a number of data distributions for various exposure variables that we believe are now sufficiently well understood to be used with confidence in most exposure assessments. A list of exposure variables that may require additional research before adequate data distributions can be developed are also discussed.     

Risk assessment of outsourcing e-procurement services: integrating SWOT analysis with a modified ANP-based fuzzy inference system

With electronic procurement solutions becoming increasingly sophisticated, many firms opt to source these services from third-party providers, effectively transferring (outsourcing) significant responsibility to these services companies. This action, however, entails certain risks, which are oftentimes difficult to assess. To guide managerial practice and to advance academic inquiry in this domain, we identify e-procurement risk factors through a strengths, weaknesses, opportunities, threats analysis, grounded in transaction cost economics (TCE), and propose a risk assessment framework based on the opinions of a group of experts. The approach taken is that of a modified analytic network process methodology, combined with a fuzzy inference system, which is versatile enough to accept the expert opinions in different input formats (such as linguistic variables and ranges). The proposed framework has the capability to aggregate expert judgements’ to estimate risk likelihoods, risk severities and risk factor indices, and derive overall risk magnitudes. The multi-method approach was motivated and is illustrated by a real-life case study of an Indian manufacturing company currently in the process of contract renewal with its existing e-procurement service provider.     

Benchmark Dose Risk Assessment for Formaldehyde Using Airflow Modeling and a Single-Compartment, DNA-Protein Cross-Link Dosimetry Model to Estimate Human Equivalent Doses

Formaldehyde induced squamous-cell carcinomas in the nasal passages of F344 rats in two inhalation bioassays at exposure levels of 6 ppm and above. Increases in rates of cell proliferation were measured by T. M. Monticello and colleagues at exposure levels of 0.7 ppm and above in the same tissues from which tumors arose. A risk assessment for formaldehyde was conducted at the CIIT Centers for Health Research, in collaboration with investigators from Toxicological Excellence in Risk Assessment (TERA) and the U.S. Environmental Protection Agency (U.S. EPA) in 1999. Two methods for dose-response assessment were used: a full biologically based modeling approach and a statistically oriented analysis by benchmark dose (BMD) method. This article presents the later approach, the purpose of which is to combine BMD and pharmacokinetic modeling to estimate human cancer risks from formaldehyde exposure. BMD analysis was used to identify points of departure (exposure levels) for low-dose extrapolation in rats for both tumor and the cell proliferation endpoints. The benchmark concentrations for induced cell proliferation were lower than for tumors. These concentrations were extrapolated to humans using two mechanistic models. One model used computational fluid dynamics (CFD) alone to determine rates of delivery of inhaled formaldehyde to the nasal lining. The second model combined the CFD method with a pharmacokinetic model to predict tissue dose with formaldehyde-induced DNA-protein cross-links (DPX) as a dose metric. Both extrapolation methods gave similar results, and the predicted cancer risk in humans at low exposure levels was found to be similar to that from a risk assessment conducted by the U.S. EPA in 1991. Use of the mechanistically based extrapolation models lends greater certainty to these risk estimates than previous approaches and also identifies the uncertainty in the measured dose-response relationship for cell proliferation at low exposure levels, the dose-response relationship for DPX in monkeys, and the choice between linear and nonlinear methods of extrapolation as key remaining sources of uncertainty.     

Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological,Nutritional, and Chemical Components

A probabilistic and interdisciplinary risk–benefit assessment (RBA) model integrating microbiological, nutritional, and chemical components was developed for infant milk, with the objective of predicting the health impact of different scenarios of consumption. Infant feeding is a particular concern of interest in RBA as breast milk and powder infant formula have both been associated with risks and benefits related to chemicals, bacteria, and nutrients, hence the model considers these three facets. Cronobacter sakazakii, dioxin‐like polychlorinated biphenyls (dl‐PCB), and docosahexaenoic acid (DHA) were three risk/benefit factors selected as key issues in microbiology, chemistry, and nutrition, respectively. The present model was probabilistic with variability and uncertainty separated using a second‐order Monte Carlo simulation process. In this study, advantages and limitations of undertaking probabilistic and interdisciplinary RBA are discussed. In particular, the probabilistic technique was found to be powerful in dealing with missing data and to translate assumptions into quantitative inputs while taking uncertainty into account. In addition, separation of variability and uncertainty strengthened the interpretation of the model outputs by enabling better consideration and distinction of natural heterogeneity from lack of knowledge. Interdisciplinary RBA is necessary to give more structured conclusions and avoid contradictory messages to policymakers and also to consumers, leading to more decisive food recommendations. This assessment provides a conceptual development of the RBA methodology and is a robust basis on which to build upon.     

Aligning Chemical Assessment Tools Across the Hazard-Risk Continuum

With the growing number and diversity of hazard and risk assessment algorithms, models, databases, and frameworks for chemicals and their applications, risk assessors and managers are challenged to select the appropriate tool for a given need or decision. Some decisions require relatively simple tools to evaluate chemical hazards (e.g., toxicity), such as labeling for safe occupational handling and transport of chemicals. Others require assessment tools that provide relative comparisons among chemical properties, such as selecting the optimum chemical for a particular use among a group of candidates. Still other needs warrant full risk characterization, coupling both hazard and exposure considerations. Examples of these include new chemical evaluations for commercialization, evaluations of existing chemicals for novel uses, and assessments of the adequacy of risk management provisions. Even well-validated tools can be inappropriately applied, with consequences as severe as misguided chemical management, compromised credibility of the tool and its developers and users, and squandered resources. This article describes seven discrete categories of tools based on their information content, function, and the type of outputs produced. It proposes a systematic framework to assist users in selecting hazard and risk assessment tools for given applications. This analysis illustrates the importance of careful selection of assessment tools to achieve responsible chemical assessment communication and sound risk management.     

Recommended Reference Values for Risk Assessment of Oral Exposure to Copper

The U.S. Environmental Protection Agency's (EPA) Integrated Risk Information System (IRIS) database, the authoritative source of U.S. risk assessment toxicity factors, currently lacks an oral reference dose (RfD) for copper. In the absence of such a value, various health-based reference values for copper are available for use in risk assessment. We summarize the scientific bases and differences in assumptions among key reference values for ingested copper to guide selection of appropriate values for risk assessment. A comprehensive review of the scientific literature best supports the oral RfD of 0.04 mg/kg body weight/day derived by EPA from their Drinking Water Action Level. This value is based on acute gastrointestinal effects but is further supported by broader analysis of copper deficiency and toxicity.     

Estimation of a Benchmark Dose in the Presence or Absence of Hormesis Using Posterior Averaging

U.S. Environment Protection Agency benchmark doses for dichotomous cancer responses are often estimated using a multistage model based on a monotonic dose‐response assumption. To account for model uncertainty in the estimation process, several model averaging methods have been proposed for risk assessment. In this article, we extend the usual parameter space in the multistage model for monotonicity to allow for the possibility of a hormetic dose‐response relationship. Bayesian model averaging is used to estimate the benchmark dose and to provide posterior probabilities for monotonicity versus hormesis. Simulation studies show that the newly proposed method provides robust point and interval estimation of a benchmark dose in the presence or absence of hormesis. We also apply the method to two data sets on carcinogenic response of rats to 2,3,7,8‐tetrachlorodibenzo‐p‐dioxin.     

A Look at State‐Level Risk Assessment in the United States: Making Decisions in the Absence of Federal Risk Values

State environmental agencies in the United States are charged with making risk management decisions that protect public health and the environment while managing limited technical, financial, and human resources. Meanwhile, the federal risk assessment community that provides risk assessment guidance to state agencies is challenged by the rapid growth of the global chemical inventory. When chemical toxicity profiles are unavailable on the U.S. Environmental Protection Agency's Integrated Risk Information System or other federal resources, each state agency must act independently to identify and select appropriate chemical risk values for application in human health risk assessment. This practice can lead to broad interstate variation in the toxicity values selected for any one chemical. Within this context, this article describes the decision‐making process and resources used by the federal government and individual U.S. states. The risk management of trichloroethylene (TCE) in the United States is presented as a case study to demonstrate the need for a collaborative approach among U.S. states toward identification and selection of chemical risk values while awaiting federal risk values to be set. The regulatory experience with TCE is contrasted with collaborative risk science models, such as the European Union's efforts in risk assessment harmonization. Finally, we introduce State Environmental Agency Risk Collaboration for Harmonization, a free online interactive tool designed to help to create a collaborative network among state agencies to provide a vehicle for efficiently sharing information and resources, and for the advancement of harmonization in risk values used among U.S. states when federal guidance is unavailable.