Bioaccessibility of Fukushima‐Accident‐Derived Cs in Soils and the Contribution of Soil Ingestion to Radiation Doses in Children

Ingestion of contaminated soil is one potential internal exposure pathway in areas contaminated by the Fukushima Daiichi Nuclear Power Plant accident. Doses from this pathway can be overestimated if the availability of radioactive nuclides in soils for the gastrointestinal tract is not considered. The concept of bioaccessibility has been adopted to evaluate this availability based on in vitro tests. This study evaluated the bioaccessibility of radioactive cesium from soils via the physiologically‐based extraction test (PBET) and the extractability of those via an extraction test with 1 mol/L of hydrochloric acid (HCl). The bioaccessibility obtained in the PBET was 5.3% ± 1%, and the extractability in the tests with HCl was 16% ± 3%. The bioaccessibility was strongly correlated with the extractability. This result indicates the possibility that the extractability in HCl can be used as a good predictor of the bioaccessibility with PBET. In addition, we assessed the doses to children from the ingestion of soil via hand‐to‐mouth activity based on our PBET results using a probabilistic approach considering the spatial distribution of radioactive cesium in Date City in Fukushima Prefecture and the interindividual differences in the surveyed amounts of soil ingestion in Japan. The results of this assessment indicate that even if children were to routinely ingest a large amount of soil with relatively high contamination, the radiation doses from this pathway are negligible compared with doses from external exposure owing to deposited radionuclides in Fukushima Prefecture.     

Assessment of Instructions on Protection Against Food Contaminated with Radiocesium in Japan in 2011

The Japan Ministry of Health, Labour and Welfare (MHLW) has published instructions for radiological protection against food after the Fukushima Daiichi nuclear power plant accident in 2011. Following the instructions, the export and consumption of food items identified as being contaminated were restricted for a certain period. We assessed the validity of the imposed restriction periods for two representative vegetables (spinach and cabbage) grown in Fukushima Prefecture from two perspectives: effectiveness for reducing dietary dose and economic efficiency. To assess effectiveness, we estimated the restriction period required to maintain consumers’ dose below the guidance dose levels. To assess economic efficiency, we estimated the restriction period that maximizes the net benefit to taxpayers. All estimated restriction periods were shorter than the actual restriction periods imposed on spinach and cabbage from Fukushima in 2011, which indicates that the food restriction effectively maintained consumers’ dietary dose below the guidance dose level, but in an economically inefficient manner. We also evaluated the response of the restriction period to the sample size for each weekly food safety test and the instructions for when to remove the restriction. Stringent MHLW instructions seemed to sufficiently reduce consumers’ health risk even when the sample size for the weekly food safety test was small, but tended to increase the economic cost to taxpayers.     

Return Migration and Decontamination After the 2011 Fukushima Nuclear Power Plant Disaster

Return migration is key to community recovery from many disasters. Japanese governments have conducted radiation decontamination efforts in the Exclusion Zone designated after the 2011 Fukushima nuclear disaster in order to encourage this outcome. Little is known, however, about the factors that influence post-disaster migrants to return, and, if people are relatively unresponsive to decontamination, then the costs of promoting recovery may exceed the benefits. We exploit a unique survey of Fukushima evacuees to determine the factors that influence their decision to return after a disaster. Location-specific capital characteristics, such as housing tenure and the extent of property damage, are estimated to be strong factors. The radiation dose rate of the home location is found to be a statistically significant factor for intent to return, but its effect is small. We also found that households with various other characteristics were noncommittal about the return option and likely to defer their decisions, which implies that “return” and “not-return” are asymmetric. Our simulation analysis found that the number of returnees encouraged by this decontamination was 12,882, less than 8% of the total evacuees, while the decontamination cost per returnee was 3.36 million USD. This result implies that the government could have improved the well-being of evacuees at a lower cost by policies other than decontamination.     

Media Exposure to Terrorism and Perception of Immigrants as a Threat: The Role of Emotional Intelligence and Psychophysiological Self-Regulation

To better understand how media exposure to terrorism-related images can lead to perceiving immigrants as more threatening, in the present study we manipulated participants’ exposure to media coverage of terrorist attacks and investigated how this may influence people's perception of Arab immigrants. Considering the important role of regulatory abilities when facing stressful events like terrorist attacks, we measured individual differences in both trait emotional intelligence and resting heart rate variability (HRV). Results showed that participants perceived Arab immigrants as more threatening in the media exposure condition than in the control condition. Importantly, there were moderating effects of both trait emotional intelligence and HRV. People with lower trait emotional intelligence or lower HRV at rest felt more threatened in the media exposure condition compared to the control condition, whereas this effect was not observed among participants with higher trait emotional intelligence or higher resting HRV. The present study highlights some of the complexities related to how media exposure to terrorism-related images influences people's reactions to, and evaluations of, an outgroup that is related to the perpetrators of the attacks.     

Triaging overflow: A case study of the ‘Gateway Assessment’ in the UK Citizens Advice Service

This article explores the impact upon the work of the UK Citizens Advice Service of the ‘Gateway Assessment’ system, a ‘triage device’ rolled out across Citizens Advice Bureaux in England and Wales from 2007 onwards designed to deal with an overflow of client needs.The paper addresses the history of ‘triage’ as a method for dealing with an excess of problematic bodies, before describing how a demonstrable need for systems to organise an overflow of advice needs within Citizens Advice Bureaux led to the emergence of triage as a ‘technique of government’ that would re-shape the advice process. Yet, as an attempt to regulate ‘from above’ the front-line of the Citizens Advice service, it met forms of resistance as existing practices of advice work and local situations fell into conflict with the inflexibility of the Gateway Assessment Process. The paper describes how implementation of the Gateway Assessment involved acts of compliance and acts of resistance, followed by a jostling between actors and a reshaping of the spaces of regulation, resulting in the ‘Gateway Plus’ model in which triage can slip into advice where necessary. We argue that this process displayed a conflict between a framing of overflow as an excess of countable bodies and one of problem-bearing subjects, the latter being derived from the relational and voluntary practice of advice.     

Model Averaging Using the Kullback Information Criterion in Estimating Effective Doses for Microbial Infection and Illness

Since the National Food Safety Initiative of 1997, risk assessment has been an important issue in food safety areas. Microbial risk assessment is a systematic process for describing and quantifying a potential to cause adverse health effects associated with exposure to microorganisms. Various dose-response models for estimating microbial risks have been investigated. We have considered four two-parameter models and four three-parameter models in order to evaluate variability among the models for microbial risk assessment using infectivity and illness data from studies with human volunteers exposed to a variety of microbial pathogens. Model variability is measured in terms of estimated ED01s and ED10s, with the view that these effective dose levels correspond to the lower and upper limits of the 1% to 10% risk range generally recommended for establishing benchmark doses in risk assessment. Parameters of the statistical models are estimated using the maximum likelihood method. In this article a weighted average of effective dose estimates from eight two- and three-parameter dose-response models, with weights determined by the Kullback information criterion, is proposed to address model uncertainties in microbial risk assessment. The proposed procedures for incorporating model uncertainties and making inferences are illustrated with human infection/illness dose-response data sets.     

Defining Susceptibility for Microbial Risk Assessment: Results of a Workshop

An interdisciplinary workshop was convened by the George Washington University in June 2001 to discuss how to incorporate new knowledge about susceptibility to microbial pathogens into risk assessment and management strategies. Experts from government, academic, and private sector organizations discussed definitions, methods, data needs, and issues related to susceptibility in microbial risk assessment. The participants agreed that modeling approaches need to account for the highly specific nature of host-pathogen relationships, and the wide variability of infectivity, immunity, disease transmission, and outcome rates within microbial species and strains. Concerns were raised about distinguishing between exposure and dose more clearly, interpreting experimental and outbreak data correctly, and using thresholds and possibly linearity at low doses. Recommendations were made to advance microbial risk assessment by defining specific terms and concepts more precisely, designing explicit conceptual frameworks to guide development of more complex models and data collection, addressing susceptibility in all steps of the model, measuring components of immunity to characterize susceptibility, reexamining underlying assumptions, applying default methods appropriately, obtaining more mechanistic data to improve default methods, and developing more biologically relevant and continuous risk estimators. The interrelated impacts of selecting specific subpopulations and health outcomes, and of increasing model complexity and data demands, were considered in the contexts of public policy goals and resources required. The participants stated that zero risk is unattainable, so targeted and effective risk reduction and communication strategies are essential not only to raise pubic awareness about water quality but also to protect the most susceptible members of the population.     

Determination of Less-Than-Lifetime Exposures to Point Source Emissions

This paper presents a method of estimating long-term exposures to point source emissions. The method consists of a Monte Carlo exposure model (PSEM or Point Source Exposure Model) that combines data on population mobility and mortality with information on daily activity patterns. The approach behind the model can be applied to a wide variety of exposure scenarios. In this paper, PSEM is used to characterize the range and distribution of lifetime equivalent doses received by inhalation of air contaminated by the emissions of a point source. The output of the model provides quantitative information on the dose, age, and gender of highly exposed individuals. The model is then used in an example risk assessment. Finally, future uses of the model's approach are discussed.     

Role of Citizens in Environmental Conservation: The Case of the Yokosuka City; A Statistical Analysis

With the recent environmental issues such as global warming and illegal dumping of waste, people are getting more concerned with the impacts of household activities on the environment. Environmental conservation activities conducted voluntarily by citizens may reduce these impacts. Citizens can be encouraged by the assessment of their activities for further undertakings. In this article, as necessary tools for such assessment, new statistics measuring the size of citizens’ activities in the environmental conservation are presented along with the outline of environmental governance in Japan. In concluding, several strategies for effective involvement of citizens in the environmental governance are suggested.     

On the risk of mortality to primates exposed to anthrax spores.

Current events have heightened the importance of understanding the risks from inhalation exposure to small numbers of spores of Bacillus anthracis. Previously reported data sets have not been fully assessed using current understanding of microbial dose response. This article presents an assessment of the reported primate dose-response data. At low doses, the risk to large populations of low doses of inhaled spores (e.g., < 100) is not insignificant.     

Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.     

A Trichloroethylene Risk Assessment Using a Monte Carlo Analysis of Parameter Uncertainty in Conjunction with Physiologically-Based Pharmacokinetic Modeling

A Monte Carlo simulation is incorporated into a risk assessment for trichloroethylene (TCE) using physiologically-based pharmacokinetic (PBPK) modeling coupled with the linearized multistage model to derive human carcinogenic risk extrapolations. The Monte Carlo technique incorporates physiological parameter variability to produce a statistically derived range of risk estimates which quantifies specific uncertainties associated with PBPK risk assessment approaches. Both inhalation and ingestion exposure routes are addressed. Simulated exposure scenarios were consistent with those used by the Environmental Protection Agency (EPA) in their TCE risk assessment. Mean values of physiological parameters were gathered from the literature for both mice (carcinogenic bioassay subjects) and for humans. Realistic physiological value distributions were assumed using existing data on variability. Mouse cancer bioassay data were correlated to total TCE metabolized and area-under-the-curve (blood concentration) trichloroacetic acid (TCA) as determined by a mouse PBPK model. These internal dose metrics were used in a linearized multistage model analysis to determine dose metric values corresponding to 10^-6 lifetime excess cancer risk. Using a human PBPK model, these metabolized doses were then extrapolated to equivalent human exposures (inhalation and ingestion). The Monte Carlo iterations with varying mouse and human physiological parameters produced a range of human exposure concentrations producing a 10^-6 risk.     

Comparative Probabilistic Assessment of Occupational Pesticide Exposures Based on Regulatory Assessments

Implementation of probabilistic analyses in exposure assessment can provide valuable insight into the risks of those at the extremes of population distributions, including more vulnerable or sensitive subgroups. Incorporation of these analyses into current regulatory methods for occupational pesticide exposure is enabled by the exposure data sets and associated data currently used in the risk assessment approach of the Environmental Protection Agency (EPA). Monte Carlo simulations were performed on exposure measurements from the Agricultural Handler Exposure Database and the Pesticide Handler Exposure Database along with data from the Exposure Factors Handbook and other sources to calculate exposure rates for three different neurotoxic compounds (azinphos methyl, acetamiprid, emamectin benzoate) across four pesticide‐handling scenarios. Probabilistic estimates of doses were compared with the no observable effect levels used in the EPA occupational risk assessments. Some percentage of workers were predicted to exceed the level of concern for all three compounds: 54% for azinphos methyl, 5% for acetamiprid, and 20% for emamectin benzoate. This finding has implications for pesticide risk assessment and offers an alternative procedure that may be more protective of those at the extremes of exposure than the current approach.     

A Bayesian Semiparametric Model for Radiation Dose‐Response Estimation

In evaluating the risk of exposure to health hazards, characterizing the dose‐response relationship and estimating acceptable exposure levels are the primary goals. In analyses of health risks associated with exposure to ionizing radiation, while there is a clear agreement that moderate to high radiation doses cause harmful effects in humans, little has been known about the possible biological effects at low doses, for example, below 0.1 Gy, which is the dose range relevant to most radiation exposures of concern today. A conventional approach to radiation dose‐response estimation based on simple parametric forms, such as the linear nonthreshold model, can be misleading in evaluating the risk and, in particular, its uncertainty at low doses. As an alternative approach, we consider a Bayesian semiparametric model that has a connected piece‐wise‐linear dose‐response function with prior distributions having an autoregressive structure among the random slope coefficients defined over closely spaced dose categories. With a simulation study and application to analysis of cancer incidence data among Japanese atomic bomb survivors, we show that this approach can produce smooth and flexible dose‐response estimation while reasonably handling the risk uncertainty at low doses and elsewhere. With relatively few assumptions and modeling options to be made by the analyst, the method can be particularly useful in assessing risks associated with low‐dose radiation exposures.     

Cancer Risk Estimation of Genotoxic Chemicals Based on Target Dose and a Multiplicative Model

A mechanistic model and associated procedures are proposed for cancer risk assessment of genotoxic chemicals. As previously shown for ionizing radiation, a linear multiplicative model was found to be compatible with published experimental data for ethylene oxide, acrylamide, and butadiene. The validity of this model was anticipated in view of the multiplicative interaction of mutation with inherited and acquired growth-promoting conditions. Concurrent analysis led to rejection of an additive model (i.e. the model commonly applied for cancer risk assessment). A reanalysis of data for radiogenic cancer in mouse, dog and man shows that the relative risk coefficient is approximately the same (0.4 to 0.5 percent per rad) for tumours induced in the three species.Doses in vivo, defined as the time-integrated concentrations of ultimate mutagens, expressed in millimol × kg^–1 × h (mMh) are, like radiation doses given in Gy or rad, proportional to frequencies of potentially mutagenic events. The radiation dose equivalents of chemical doses are, calculated by multiplying chemical doses (in mMh) with the relative genotoxic potencies (in rad × mMh^–1) determined in vitro. In this way the relative cancer incidence increments in rats and mice exposed to ethylene oxide were shown to be about 0.4 percent per rad-equivalent, in agreement with the data for radiogenic cancer.Our analyses suggest that values of the relative risk coefficients for genotoxic chemicals are independent of species and that relative cancer risks determined in animal tests apply also to humans. If reliable animal test data are not available, cancer risks may be estimated by the relative potency. In both cases exposure dose/target dose relationships, the latter via macromolecule adducts, should be determined.     

Environmental Exposure of the Adult French Population to Permethrin

This work aims to assess the exposure to permethrin of the adult French population from available contamination measurements of outdoor air, indoor air, and settled dust. Priority is given to the assessment of chronic exposure, given the potential of permethrin to induce cancers and/or endocrine disorders. A statistical method was devised to calculate exposure to permethrin by different pathways (inhalation, indirect dust ingestion, and dermal contact). This method considers anthropometric parameters, the population's space–time budget, and recent methods for calculating dermal exposure. Considering the media of interest, our results pointed to house dust as the main environmental source of permethrin exposure, followed by indoor and outdoor air. Dermal contact and indirect dust ingestion may be more important exposure pathways than inhalation. A sensitivity analysis indicated that exposure estimates were mainly affected by variability within contamination data. This study is the first step in aggregated exposure and risk assessment due to pyrethroid exposure. Outdoor air, indoor air, and settled dust may constitute significant exposure sources, in addition to diet, which could be important. The next step entails assessing internal doses and estimating the proportion of each exposure source and pathway relative to internal exposure.     

Using the Biological Two-Stage Model to Assess Risk from Short-Term Exposures

Two assumptions used in risk assessment are investigated: (1) the assumption of fraction of lifetime dose rate assumes that the risk from a fractional lifetime exposure at a given dose rate is equal to the risk from full lifetime exposure at that same fraction of the given dose rate; (2) the assumption of fraction of lifetime risk assumes that the risk from a fractional lifetime exposure at a given dose rate is equal to that same fraction of the risk from full lifetime exposure at the same dose rate. These two assumptions are equivalent when risk is a linear function of dose. Thus both can be thought of as generalizations of the assumption that cancer risk is proportional to the total accumulated lifetime dose (or average daily dose), which is often made to assess the risk from short-term exposures. In this paper, the age-specific cumulative hazard functions are derived using the two-stage model developed by Moolgavkar, Venzon, and Knudson for situations when the exposure occurs during a single period or a single instant. The two assumptions described above are examined for three types of carcinogens, initiator, completer, and promoter, in the context of the model. For initiator and completer, these two assumptions are equivalent in the low-dose region; for a promoter, using the fraction of lifetime risk assumption is generally more conservative than that of the fraction of lifetime dose rate assumption. Tables are constructed to show that the use of either the fraction of lifetime dose rate assumption or the fraction lifetime risk assumption can both underestimate and overestimate the true risk for the three types of carcinogens.     

Variability in PAH-DNA Adduct Measurements in Peripheral Mononuclear Cells: Implications for Quantitative Cancer Risk Assessment

Biomarkers such as DNA adducts have significant potential to improve quantitative risk assessment by characterizing individual differences in metabolism of genotoxins and DNA repair and accounting for some of the factors that could affect interindividual variation in cancer risk. Inherent uncertainty in laboratory measurements and within-person variability of DNA adduct levels over time are putatively unrelated to cancer risk and should be subtracted from observed variation to better estimate interindividual variability of response to carcinogen exposure. A total of 41 volunteers, both smokers and nonsmokers, were asked to provide a peripheral blood sample every 3 weeks for several months in order to specifically assess intraindividual variability of polycyclic aromatic hydrocarbon (PAH)-DNA adduct levels. The intraindividual variance in PAH-DNA adduct levels, together with measurement uncertainty (laboratory variability and unaccounted for differences in exposure), constituted roughly 30% of the overall variance. An estimated 70% of the total variance was contributed by interindividual variability and is probably representative of the true biologic variability of response to carcinogenic exposure in lymphocytes. The estimated interindividual variability in DNA damage after subtracting intraindividual variability and measurement uncertainty was 24-fold. Inter-individual variance was higher (52-fold) in persons who constitutively lack the Glutathione S-Transferase M1 (GSTM1) gene which is important in the detoxification pathway of PAH. Risk assessment models that do not consider the variability of susceptibility to DNA damage following carcinogen exposure may underestimate risks to the general population, especially for those people who are most vulnerable.     

Benchmark Dose Analysis via Nonparametric Regression Modeling

Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose‐response modeling. It is a well‐known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low‐dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal‐response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap‐based confidence limits for the BMD. We explore the confidence limits’ small‐sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty.