Identifying Childhood Age Groups for Exposure Assessments and Monitoring

The purpose of this article is to describe a standard set of age groups for exposure assessors to consider when assessing childhood exposure and potential dose to environmental contaminants. In addition, this article presents examples to show how the age groups can be applied in children's exposure assessments. A consistent set of childhood age groups, supported by an underlying scientific rationale, will improve the accuracy and comparability of exposure and risk assessments for children. The effort was undertaken in part to aid the U.S. Environmental Protection Agency (EPA) in implementing such regulatory initiatives as the 1997 Presidential Executive Order 13,045, which required all federal agencies to ensure that their standards take into account special risks to children. The standard age groups include: birth to <1 month; 1 to <3 months; 3 to <6 months; 6 to <12 months; 1 to <2 years; 2 to <3 years; 3 to <6 years; 6 to <11 years; 11 to <16 years; and 16 to <21 years. These age groups reflect a consideration of developmental changes in various behavioral, anatomical, and physiological characteristics that impact exposure and potential dose. It is expected that the availability of a standard set of early-life age groups will inform future analyses of exposure factors data as well as guide new research and data collection efforts to fill knowledge gaps.     

Influenza Infection Risk and Predominate Exposure Route: Uncertainty Analysis

An effective nonpharmaceutical intervention for influenza interrupts an exposure route that contributes significantly to infection risk. Herein, we use uncertainty analysis (point‐interval method) and Monte Carlo simulation to explore the magnitude of infection risk and predominant route of exposure. We utilized a previously published mathematical model of a susceptible person attending a bed‐ridden infectious person. Infection risk is sensitive to the magnitude of virus emission and contact rates. The contribution of droplet spray exposure to infection risk increases with cough frequency, and decreases with virus concentration in cough particles. We consider two infectivity scenarios: greater infectivity of virus deposited in the upper respiratory tract than virus inhaled in respirable aerosols, based on human studies; and equal infectivity in the two locations, based on studies in guinea pigs. Given that virus have equal probability of infection throughout the respiratory tract, the mean overall infection risk is 9.8 × 10^?2 (95th percentile 0.78). However, when virus in the upper respiratory tract is less infectious than inhaled virus, the overall infection risk is several orders of magnitude lower. In this event, inhalation is a significant exposure route. Contact transmission is important in both infectivity scenarios. The presence of virus in only respirable particles increases the mean overall infection risk by 1–3 orders of magnitude, with inhalation contributing ≥ 99% of the infection risk. The analysis indicates that reduction of uncertainties in the concentration of virus in expiratory particles of different sizes, expiratory event frequency, and infectivity at different sites in the respiratory tract will clarify the predominate exposure routes for influenza.     

Generating Probabilistic Spatially-Explicit Individual and Population Exposure Estimates for Ecological Risk Assessments

Exposure to chemical contaminants in various media must be estimated when performing ecological risk assessments. Exposure estimates are often based on the 95th-percentile upper confidence limit on the mean concentration of all samples, calculated without regard to critical ecological and spatial information about the relative relationship of receptors, their habitats, and contaminants. This practice produces exposure estimates that are potentially unrepresentative of the ecology of the receptor. This article proposes a habitat area and quality-conditioned exposure estimator, E[HQ], that requires consideration of these relationships. It describes a spatially explicit ecological exposure model to facilitate calculation of E[HQ]. The model provides (1) a flexible platform for investigating the effect of changes in habitat area, habitat quality, foraging area, and population size on exposure estimates, and (2) a tool for calculating E[HQ] for use in actual risk assessments. The inner loop of a Visual Basic program randomly walks a receptor over a multicelled landscape--each cell of which contains values for cell area, habitat area, habitat quality, and concentration--accumulating an exposure estimate until the total area foraged is less than or equal to a given foraging area. An outer loop then steps through foraging areas of increasing size. This program is iterated by Monte Carlo software, with the number of iterations representing the population size. Results indicate that (1) any single estimator may over- or underestimate exposure, depending on foraging strategy and spatial relationships of habitat and contamination, and (2) changes in exposure estimates in response to changes in foraging and habitat area are not linear.     

Phthalate Exposure Through Food and Consumers' Risk Perception of Chemicals in Food

Phthalates have been detected in various types of retail foods. Consumers' exposure to phthalates is common. Consumers are concerned about chemicals in food. Our aim was to investigate the relationships between consumers' exposure to phthalates through food, consumers' interest in a natural and healthy diet, risk perception of food chemicals, and consumers' diet patterns. We collected data through a mail survey in the adult Swiss-German population ( N  = 1,200). We modeled exposure to di(2-ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP), benzyl butyl phthalate (BBP), and diethyl phthalate (DEP) based on a food frequency questionnaire and phthalate concentrations reported from food surveys. Using rating scales, we assessed risk perceptions of chemicals in food and interest in a natural and healthy diet. Higher risk perceptions and higher natural and healthy diet interest were associated with higher daily doses of DEHP, BBP, and DEP. No health risk from phthalates in food was identified for the vast majority of the population. Four consumers' diet clusters were discerned, with differences in phthalate exposure, risk perceptions, and interest in a natural and healthy diet. This study shows that even those consumers who express strong interest in natural food and low acceptance of food chemicals, and who try to make respective food choices, are exposed to contaminants such as phthalates.     

Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments

Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe—here represented by Sweden—and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments.     

Characterizing and Communicating Risk with Exposure Reconstruction and Bayesian Analysis: Historical Locomotive Maintenance/Repair Associated with Asbestos Woven Tape Pipe Lagging

Our reconstructed historical work scenarios incorporating a vintage 1950s locomotive can assist in better understanding the historical asbestos exposures associated with past maintenance and repairs and fill a literature data gap. Air sampling data collected during the exposure scenarios and analyzed by NIOSH 7400 (PCM) and 7402 (PCME) methodologies show personal breathing zone asbestiform fiber exposures were below the current OSHA exposure limits for the eight‐hour TWA permissible exposure limit (PEL) of 0.1 f/cc (range <0.007–0.064 PCME f/cc) and the 30‐minute short‐term excursion limit (EL) of 1.0 f/cc (range <0.045–0.32 PCME f/cc) and orders of magnitude below historic OSHA PEL and ACGIH TLVs. Bayesian decision analysis (BDA) results demonstrate that the 95th percentile point estimate falls into an AIHA exposure category 3 or 4 as compared to the current PEL and category 1 when compared to the historic PEL. BDA results demonstrate that bystander exposures would be classified as category 0. Our findings were also significantly below the published calcium magnesium insulations exposure range of 2.5 to 7.5 f/cc reported for historic work activities of pipefitters, mechanics, and boilermakers. Diesel‐electric locomotive pipe systems were typically insulated with a woven tape lagging that may have been chrysotile asbestos and handled, removed, and reinstalled during repair and maintenance activities. We reconstructed historical work scenarios containing asbestos woven tape pipe lagging that have not been characterized in the published literature. The historical work scenarios were conducted by a retired railroad pipefitter with 37 years of experience working with materials and locomotives.     

A Critical Look at Risk Assessments for Global Catastrophes

Recent articles by Busza et al. (BJSW) and Dar et al. (DDH) argue that astrophysical data can be used to establish small bounds on the risk of a "killer strangelet" catastrophe scenario in the RHIC and ALICE collider experiments. The case for the safety of the experiments set out by BJSW does not rely solely on these bounds, but on theoretical arguments, which BJSW find sufficiently compelling to firmly exclude any possibility of catastrophe. Nonetheless, DDH and other commentators (initially including BJSW) suggested that these empirical bounds alone do give sufficient reassurance. This seems unsupportable when the bounds are expressed in terms of expectation value-a good measure, according to standard risk analysis arguments. For example, DDH's main bound, p(catastrophe) < 2 x 10(-8), implies only that the expectation value of the number of deaths is bounded by 120; BJSW's most conservative bound implies the expectation value of the number of deaths is bounded by 60,000. This article reappraises the DDH and BJSW risk bounds by comparing risk policy in other areas. For example, it is noted that, even if highly risk-tolerant assumptions are made and no value is placed on the lives of future generations, a catastrophe risk no higher than approximately 10(-15) per year would be required for consistency with established policy for radiation hazard risk minimization. Allowing for risk aversion and for future lives, a respectable case can be made for requiring a bound many orders of magnitude smaller. In summary, the costs of small risks of catastrophe have been significantly underestimated by BJSW (initially), by DDH, and by other commentators. Future policy on catastrophe risks would be more rational, and more deserving of public trust, if acceptable risk bounds were generally agreed upon ahead of time and if serious research on whether those bounds could indeed be guaranteed was carried out well in advance of any hypothetically risky experiment, with the relevant debates involving experts with no stake in the experiments under consideration.     

Assessment of Population Exposure and Carcinogenic Risk Posed by Volatile Organic Compounds in Indoor Air

A number of air pollutants are being found in low concentrations in indoor and outdoor air. Several studies have measured these concentrations for a large number of compounds in hundreds of residences. The concentrations range over several orders of magnitude over time and space. The log-normal distributions that are found make it possible to assess the impact on the health of populations, especially for genotoxic effects for which a threshold concentration is not expected to exist. Spreadsheets can be constructed which incorporate the unit risk of a substance for cancer, the distribution of concentrations of the substance in the population, and the size of the population into an assessment of the expected excess cases of cancer that can be attributed to the population exposure to such a toxicant. This approach allows for the evaluation of population risk for different substances as found in different environments, and for the evaluation of the relative efficacy of different strategies for population risk reduction.     

Measures of Societal Risk and Their Potential Use in Civil Aviation

This article seeks to clarify the conceptual foundations of measures of societal risk, to investigate how such measures may be used validly in commonly encountered policy contexts, and to explore the application of these measures in the field of civil aviation. The article begins by examining standard measures of societal and individual risk (SR and IR), with attention given to ethical as well as analytical considerations. A comprehensive technical analysis of SR is provided, encompassing scalar risk measures, barrier functions, and a utility‐based formulation, and clarifications are offered with respect to the treatment of SR in recent publications. The policy context for SR measures is shown to be critically important, and an extension to a hierarchical setting is developed. The prospects for applying SR to civil aviation are then considered, and some technical and conceptual issues are identified. SR appears to be a useful analytical tool in this context, provided that careful attention is given to these issues.     

Principles of Good Practice for the Use of Monte Carlo Techniques in Human Health and Ecological Risk Assessments

We propose 14 principles of good practice to assist people in performing and reviewing probabilistic or Monte Carlo risk assessments, especially in the context of the federal and state statutes concerning chemicals in the environment. Monte Carlo risk assessments for hazardous waste sites that follow these principles will be easier to understand, will explicitly distinguish assumptions from data, and will consider and quantify effects that could otherwise lead to misinterpretation of the results. The proposed principles are neither mutually exclusive nor collectively exhaustive. We think and hope that these principles will evolve as new ideas arise and come into practice.     

One Agency's Use of Risk Assessment and Risk Communication1

Few organizations have the courage to evaluate their own use of risk assessment (identifying hazards and estimating their probability and magnitude) and risk communication (interacting with internal and external stakeholder groups about risks). The USDA Animal and Plant Health Inspection Service (APHIS) wants to enhance its overall risk analysis process for managing a wide range of risks to animals, plants, and human health. We gathered survey data for a baseline of APHIS professionals’ understanding and use of risk assessment and risk communication. APHIS professionals spend a surprisingly large share of their time communicating about risks. They perceive that risk estimates influence decisions, but that risk estimates should have more influence. Respondents reported little opposition to APHIS risk management decisions, and little use of channels such as USDA Extension Service for disseminating risk messages. Substantial variance across responses is explained mostly by differences in the roles of the 11 work units (now 10) within the agency. Location also contributes to the variance. Demographic variables seem less important.     

Chloroform Exposure and the Health Risk Associated with Multiple Uses of Chlorinated Tap Water

Recently, showers have been suspected to be an important source of indoor exposure to volatile organic compounds (VOC). The chloroform dose to an individual from showering was determined based on exhaled breath analysis. The postexposure chloroform breath concentration ranged from 6.0-21 micrograms/m3, while all corresponding background breath concentrations were less than 0.86 micrograms/m3. The internal dose from showering (inhalation plus dermal) was comparable to estimates of the dose from daily water ingestion. The risk associated with a single, 10-min shower was estimated to be 1.22 x 10(-4), while the estimated risk from daily ingestion of tap water ranged from 0.130 x 10(-4) to 1.80 x 10(-4) for 0.15 and 2.0 L, respectively. Since the estimates of chloroform risk from domestic water use for the three exposure routes--ingestion, inhalation, and dermal--are similar, all routes must be used to calculate the total risk when making policy decisions regarding the quality of the municipal water supply.     

A Methodology for Grouping Source Terms for Consequence Calculations in Probabilistic Risk Assessments

The individual plant analyses in the U.S. Nuclear Regulatory Commission's reassessment of the risk from commercial nuclear power plants (NUREG-1150) consist of four parts: systems analysis, accident-progression analysis, source-term analysis, and consequence analysis. Careful definition of the interfaces between these parts is necessary for both information flow and computational efficiency. This paper describes the procedure used to define the interface between the source-term analysis and the consequence analysis. This interface is accomplished by forming groups of source terms with similar properties and then performing one set of MACCS calculations for each group.     

Risk Assessment of Listeria monocytogenes: Impact of Individual Cell Variability on the Exposure Assessment Step

Recently, the lag phase research in predictive microbiology is focusing more on the individual cell variability, especially for pathogenic microorganisms that typically occur in very low contamination levels, like Listeria monocytogenes. In this study, the effect of this individual cell lag phase variability was introduced in an exposure assessment study for L. monocytogenes in a liver paté. A basic framework was designed to estimate the contamination level of paté at the time of consumption, taking into account the frequency of contamination and the initial contamination levels of paté at retail. Growth was calculated on paté units of 150 g, comparing an individual-based approach with a classical population-based approach. The two different protocols were compared using simulations. If only the individual cell lag variability was taken into account, important differences were observed in cell density at the time of consumption between the individual-based approach and the classical approach, especially at low inoculum levels, resulting in high variability when using the individual-based approach. Although, when all variable factors were taken into account, no significant differences were observed between the different approaches, allowing the conclusion that the individual cell lag phase variability was overruled by the global variability of the exposure assessment framework. Even in more extreme conditions like a low inoculum level or a low water activity, no differences were created in cell density at the time of consumption between the individual-based approach and the classical approach. This means that the individual cell lag phase variability of L. monocytogenes has important consequences when studying specific growth cases, especially when the applied inoculum levels are low, but when performing more general exposure assessment studies, the variability between the individual cell lag phases is too limited to have a major impact on the total exposure assessment.     

Risk/Benefit Assessments of Human Diseases: Optimum Dose for Intervention

A simple procedure is proposed in order to quantify the tradeoff between a loss suffered from an illness due to exposure to a microbial pathogen and a loss due to a toxic effect, perhaps a different illness, induced by a disinfectant employed to reduce the microbial exposure. Estimates of these two types of risk as a function of disinfectant dose and their associated relative losses provide information for the estimation of the optimum dose of disinfectant that minimizes the total expected loss. The estimates of the optimum dose and expected relative total loss were similar regardless of whether the beta-Poisson, log-logistic, or extreme value function was used to model the risk of illness due to exposure to a microbial pathogen. This is because the optimum dose of the disinfectant and resultant expected minimum loss depend upon the estimated slope (first derivative) of the models at low levels of risk, which appear to be similar for these three models at low levels of risk. Similarly, the choice among these three models does not appear critical for estimating the slope at low levels of risk for the toxic effect induced by the use of a disinfectant. For the proposed procedure to estimate the optimum disinfectant dose, it is not necessary to have absolute values for the losses due to microbial-induced or disinfectant-induced illness, but only relative losses are required. All aspects of the problem are amenable to sensitivity analyses. The issue of risk/benefit tradeoffs, more appropriately called risk/risk tradeoffs, does not appear to be an insurmountable problem.     

Heterogeneity: A Major Factor Influencing Microbial Exposure and Risk Assessment

Microbial risk assessment is dependent on several biological and environmental factors that affect both the exposure characteristics to the biological agents and the mechanisms of pathogenicity involved in the pathogen‐host relationship. Many exposure assessment studies still focus on the location parameters of the probability distribution representing the concentration of the pathogens and/or toxin. However, the mean or median by themselves are insufficient to evaluate the adverse effects that are associated with a given level of exposure. Therefore, the effects on the risk of disease of a number of factors, including the shape parameters characterizing the distribution patterns of the pathogen in their environment, were investigated. The statistical models, which were developed to provide a better understanding of the factors influencing the risk, highlight the role of heterogeneity and its consequences on the commonly used risk assessment paradigm. Indeed, the heterogeneity characterizing the spatial and temporal distribution of the pathogen and/or the toxin contained in the water or food consumed is shown to be a major factor that may influence the magnitude of the risk dramatically. In general, the risk diminishes with higher levels of heterogeneity. This scheme is totally inverted in the presence of a threshold in the dose‐response relationship, since heterogeneity will then have a tremendous impact, namely, by magnifying the risk when the mean concentration of pathogens is below the threshold. Moreover, the approach of this article may be useful for risk ranking analysis, regarding different exposure conditions, and may also lead to improved water and food quality guidelines.     

Bisphenol A: How the Most Relevant Exposure Sources Contribute to Total Consumer Exposure

Bisphenol A (BPA) is an endocrine disrupting chemical that is found in human urine throughout industrial societies around the globe. Consumer exposure pathways to BPA include packaged food, household dust, air, and dental fillings. To date, information on the relative contribution of the different pathways to total consumer exposure is lacking, but is key for managing substance‐associated risks. We investigated the relative contributions of the pathways known to be most relevant for nine different consumer groups. Our results suggest that the most important pathways for infants and children are the use of polycarbonate (PC) baby bottles and for adults and teenagers the consumption of canned food. Dental surgery can also considerably contribute over a short time directly after the surgery. For infants fed with PC baby bottles with mean dose rates of 0.8 μg/kg_bw/d the highest exposure dose rate was calculated. This dose rate is far below the tolerable daily intake of 50 μg/kg_bw/d. However, it is of the same order of magnitude as recently reported concentrations that caused low‐dose health effects in rodents. We find a pattern of falling exposure levels with rising age that is supported by urinary concentrations of BPA available for selected consumer groups. Similarly, the exposure levels we predict are confirmed by the levels reported in these studies.     

Rapid Benefit-Risk Assessments: No Escape from Expert Judgments in Risk Management

The "human health impacts assessment" described by Cox and Popken (this issue) is intended to be a benefit-risk tool that avoids pitfalls of using expert judgments for policy analysis or during strict application of the precautionary principle in risk management. The proposed benefit-risk calculation uses numerous assumptions and suppositions to calculate a ratio of quality-adjusted life years (QALYs) lost for the number of human illness days prevented by the use of a food-animal antimicrobial drug, to the number of human illness days caused by the use of the antimicrobial drug. Assumptions about data--e.g., expert judgments on the representativeness of parameter estimates--are commonly used in risk assessment and risk management, including Cox and Popken's method. Cox and Popken apply the technique to specific examples of enrofloxacin and macrolides antimicrobial drugs, sometimes used in broiler chickens for human food. Although enthusiastically portrayed as a straightforward calculation of QALYs lost for two decision alternatives, Cox and Popken were silent on the pivotal expert judgment subsumed in their method: quality weights for illnesses caused by antimicrobial-resistant and antimicrobial-sensitive microbes are tacitly assumed to be equal. Yet, the costs in terms of prolonged illness, additional medications, repeat medical visits, and dread of more serious sequelae are expected to differ substantially for antimicrobial-resistant versus antimicrobial-sensitive illnesses. Despite their enthusiasm to the contrary, the "human health impacts assessment" by Cox and Popken is not immune from expert judgments in risk management.     

Integrated Analysis: Combining Risk and Economic Assessments While Preserving the Separation of Powers

This article presents a process for an integrated policy analysis that combines risk assessment and benefit-cost analysis. This concept, which explicitly combines the two types of related analyses, seems to contradict the long-accepted risk analysis paradigm of separating risk assessment and risk management since benefit-cost analysis is generally considered to be a part of risk management. Yet that separation has become a problem because benefit-cost analysis uses risk assessment results as a starting point and considerable debate over the last several years focused on the incompatibility of the use of upper bounds or "safe" point estimates in many risk assessments with benefit-cost analysis. The problem with these risk assessments is that they ignore probabilistic information. As advanced probabilistic techniques for risk assessment emerge and economic analysts receive distributions of risks instead of point estimates, the artificial separation between risk analysts and the economic/decision analysts complicates the overall analysis. In addition, recent developments in countervailing risk theory suggest that combining the risk and benefit-cost analyses is required to fully understand the complexity of choices and tradeoffs faced by the decisionmaker. This article also argues that the separation of analysis and management is important, but that benefit-cost analysis has been wrongly classified into the risk management category and that the analytical effort associated with understanding the economic impacts of risk reduction actions need to be part of a broader risk assessment process.