Why People Believe They Were Exposed to Biological or Chemical Warfare: A Survey of Gulf War Veterans

The study sought to understand better how people come to believe they have been exposed to biological and chemical warfare. We conducted telephone interviews with 1,009 American veterans (65% response rate) deployed and not deployed to the Gulf War, a conflict during which there were credible threats that such warfare could be used. Only 6% of non-Gulf War veterans reported exposure to biological or chemical warfare, but most of Gulf War veterans reported exposure (64%). The majority of these were unsure whether the exposure was chemical or biological in nature. The most commonly reported exposure indicators were receiving an alert from the military and having physical symptoms. Veterans who were certain of the type of exposure (biological or chemical) were more likely to recall having been told by the military and to recall physical symptoms. Future communications with soldiers and the general public about biological and chemical warfare may need to emphasize the uncertain nature of such risk information. Evaluations of exposure diagnostic technologies should take into account the problem of people initially believing, but not later discounting, false positive results.     

Peak Exposures in Epidemiologic Studies and Cancer Risks: Considerations for Regulatory Risk Assessment

We review approaches for characterizing “peak” exposures in epidemiologic studies and methods for incorporating peak exposure metrics in dose–response assessments that contribute to risk assessment. The focus was on potential etiologic relations between environmental chemical exposures and cancer risks. We searched the epidemiologic literature on environmental chemicals classified as carcinogens in which cancer risks were described in relation to “peak” exposures. These articles were evaluated to identify some of the challenges associated with defining and describing cancer risks in relation to peak exposures. We found that definitions of peak exposure varied considerably across studies. Of nine chemical agents included in our review of peak exposure, six had epidemiologic data used by the U.S. Environmental Protection Agency (US EPA) in dose–response assessments to derive inhalation unit risk values. These were benzene, formaldehyde, styrene, trichloroethylene, acrylonitrile, and ethylene oxide. All derived unit risks relied on cumulative exposure for dose–response estimation and none, to our knowledge, considered peak exposure metrics. This is not surprising, given the historical linear no‐threshold default model (generally based on cumulative exposure) used in regulatory risk assessments. With newly proposed US EPA rule language, fuller consideration of alternative exposure and dose–response metrics will be supported. “Peak” exposure has not been consistently defined and rarely has been evaluated in epidemiologic studies of cancer risks. We recommend developing uniform definitions of “peak” exposure to facilitate fuller evaluation of dose response for environmental chemicals and cancer risks, especially where mechanistic understanding indicates that the dose response is unlikely linear and that short‐term high‐intensity exposures increase risk.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

A Bayesian Model and Stochastic Exposure (Dose) Estimation for Relative Exposure Risk Comparison Involving Asbestos‐Containing Dropped Ceiling Panel Installation and Maintenance Tasks

Assessing exposures to hazards in order to characterize risk is at the core of occupational hygiene. Our study examined dropped ceiling systems commonly used in schools and commercial buildings and lay‐in ceiling panels that may have contained asbestos prior to the mid to late 1970s. However, most ceiling panels and tiles do not contain asbestos. Since asbestos risk relates to dose, we estimated the distribution of eight‐hour TWA concentrations and one‐year exposures (a one‐year dose equivalent) to asbestos fibers (asbestos f/cc‐years) for five groups of workers who may encounter dropped ceilings: specialists, generalists, maintenance workers, nonprofessional do‐it‐yourself (DIY) persons, and other tradespersons who are bystanders to ceiling work. Concentration data (asbestos f/cc) were obtained through two exposure assessment studies in the field and one chamber study. Bayesian and stochastic models were applied to estimate distributions of eight‐hour TWAs and annual exposures (dose). The eight‐hour TWAs for all work categories were below current and historic occupational exposure limits (OELs). Exposures to asbestos fibers from dropped ceiling work would be categorized as “highly controlled” for maintenance workers and “well controlled” for remaining work categories, according to the American Industrial Hygiene Association exposure control rating system. Annual exposures (dose) were found to be greatest for specialists, followed by maintenance workers, generalists, bystanders, and DIY. On a comparative basis, modeled dose and thus risk from dropped ceilings for all work categories were orders of magnitude lower than published exposures for other sources of banned friable asbestos‐containing building material commonly encountered in construction trades.     

A combat support hospital in the Gulf War

The war in the Persian Gulf was an incredible undertaking from almost any viewpoint. The distances involved, the political alliances forged, the numbers of men and women participating, and the amount of equipment moved have not been seen since the Second World War. The medical effort to ensure that all combatants received appropriate health care was equally massive.     

Assessment of Interindividual and Geographic Variability in Human Exposure to Fine Particulate Matter in Environmental Tobacco Smoke

Environmental tobacco smoke (ETS) is a major contributor to indoor human exposures to fine particulate matter of 2.5 μm or smaller (PM_2.5). The Stochastic Human Exposure and Dose Simulation for Particulate Matter (SHEDS‐PM) Model developed by the U.S. Environmental Protection Agency estimates distributions of outdoor and indoor PM_2.5 exposure for a specified population based on ambient concentrations and indoor emissions sources. A critical assessment was conducted of the methodology and data used in SHEDS‐PM for estimation of indoor exposure to ETS. For the residential microenvironment, SHEDS uses a mass‐balance approach, which is comparable to best practices. The default inputs in SHEDS‐PM were reviewed and more recent and extensive data sources were identified. Sensitivity analysis was used to determine which inputs should be prioritized for updating. Data regarding the proportion of smokers and “other smokers” and cigarette emission rate were found to be important. SHEDS‐PM does not currently account for in‐vehicle ETS exposure; however, in‐vehicle ETS‐related PM_2.5 levels can exceed those in residential microenvironments by a factor of 10 or more. Therefore, a mass‐balance‐based methodology for estimating in‐vehicle ETS PM_2.5 concentration is evaluated. Recommendations are made regarding updating of input data and algorithms related to ETS exposure in the SHEDS‐PM model. Interindividual variability for ETS exposure was quantified. Geographic variability in ETS exposure was quantified based on the varying prevalence of smokers in five selected locations in the United States.     

The Obama Administration's Regulatory Review Initiative: A 21st Century Federal Regulatory Initiative?

On January 18, 2011, President Obama signed Executive Order 13563, Improving Regulation and Regulatory Review, which instructs federal regulators to do the following: coordinate their agencies activities to simplify and harmonize rules that may be overlapping, inconsistent, or redundant; determine whether the present and future benefits of a proposed regulation justify its potential costs (including taking into account both quantitative and qualitative factors); increase participation of industry, experts, and the public (“stakeholders”) in the formal rule‐making process; encourage the use of warnings, default rules, disclosure requirements, and provisions of information to the public as an alternative to traditional “command‐and‐control” rule‐making restricting consumer choice; and mandate a government‐wide review of all existing administrative rules to remove outdated regulations. Executive Order 13563 includes a qualitative “values” provision to be considered in the required cost–benefit analysis, which can potentially counteract the alleged regulatory reform rationale of President Obama. Furthermore, in Executive Order 13563, President Obama established a deadline of May 18, 2011, for all executive branch agencies to submit their plans to streamline their rulemaking operations and repeal those “overlapping, inconsistent, or redundant” rules. These two issues, along with complementary regulatory review proposals being discussed in the U.S. Congress, are evaluated in this essay.     

Some Limitations of Qualitative Risk Rating Systems

Qualitative systems for rating animal antimicrobial risks using ordered categorical labels such as “high,”“medium,” and “low” can potentially simplify risk assessment input requirements used to inform risk management decisions. But do they improve decisions? This article compares the results of qualitative and quantitative risk assessment systems and establishes some theoretical limitations on the extent to which they are compatible. In general, qualitative risk rating systems satisfying conditions found in real‐world rating systems and guidance documents and proposed as reasonable make two types of errors: (1) Reversed rankings, i.e., assigning higher qualitative risk ratings to situations that have lower quantitative risks; and (2) Uninformative ratings, e.g., frequently assigning the most severe qualitative risk label (such as “high”) to situations with arbitrarily small quantitative risks and assigning the same ratings to risks that differ by many orders of magnitude. Therefore, despite their appealing consensus‐building properties, flexibility, and appearance of thoughtful process in input requirements, qualitative rating systems as currently proposed often do not provide sufficient information to discriminate accurately between quantitatively small and quantitatively large risks. The value of information (VOI) that they provide for improving risk management decisions can be zero if most risks are small but a few are large, since qualitative ratings may then be unable to confidently distinguish the large risks from the small. These limitations suggest that it is important to continue to develop and apply practical quantitative risk assessment methods, since qualitative ones are often unreliable.     

Psychosocial effects of war experiences among displaced children in southern Darfur

This study focused on assessing the psychosocial effects of the long standing, high intensity, and guerrilla-style of warfare among displaced children in Southern Darfur. The goal was to better understand the etiology, prognosis, and treatment implications for traumatic reactions, depression, and grief symptoms in this population. Three hundred thirty-one children aged 6-17 from three IDP Camps were selected using a quota sampling approach and were administered a Demographic Questionnaire, Child Post Traumatic Stress Reaction Index, Child Depression Inventory, and the Expanded Grief Inventory. Forty-three percent were girls and 57% were boys. The mean age of the children was 12 years. Results found that children were exposed to a very large number of war experiences with no significant differences between genders for types of exposure, including rape, but with older children (13-17 years) facing a larger number of exposures than younger children (6-12 years). Out of the 16 possible war experiences, the mean number was 8.94 (SD = 3.27). Seventy-five percent of the children met the DSM-IV criteria for PTSD, and 38% exhibited clinical symptoms of depression. The percentage of children endorsing significant levels of grief symptoms was 20%. Increased exposure to war experiences led to higher levels of: (1) traumatic reactions; (2) depression; and (3) grief symptoms. Of the 16 war experiences, abduction, hiding to protect oneself, being raped, and being forced to kill or hurt family members were most predictive of traumatic reactions. Being raped, seeing others raped, the death of a parent/s, being forced to fight, and having to hide to protect oneself were the strongest predictors of depressive symptoms. War experiences such as abduction, death of one's parent/s, being forced to fight, and having to hide to protect oneself were the most associated with the child's experience of grief. In addition to Total Grief, Traumatic Grief, Existential Grief, and Continuing Bonds were measured in these children. Although trauma, depression, and grief often exist as co-morbid disorders, the mechanisms and pathways of these is less understood. In this study we used Structural Equation Modeling to better understand the complex interaction and trajectories of these three symptoms evolving from war exposure and loss. This study is the first of its kind to assess the psychosocial effects of war experiences among children currently living in war zone areas within Sudan. It identifies some of the most prevalent war-related atrocities and their varying impact on the children's psychological well-being and overall adjustment. Implications for planning mental health interventions are discussed.     

How soy labeling influences preference and taste

Using a “Phantom Ingredient” taste test, this article demonstrates how the use of soy labels and health claims on a package negatively biased taste perceptions and attitudes toward a food erroneously thought to contain soy. Consumers who ate products which mentioned soy on the package described the taste more grainy, less flavorful, and as having a strong aftertaste compared to those who ate the product but saw no soy label. Yet, while putting “soy” on a package negatively influenced taste-conscious consumers, when combined with a health claim, it improved attitudes among consumers who are health-conscious, natural food lovers, or dieters. Our results and discussion provide better direction for researchers who work with ingredient labeling as well as for marketers who work with soybean products.     

Assessment of Health Risk from Historical Use of Cosmetic Talcum Powder

This study's objective is to assess the risk of asbestos‐related disease being contracted by past users of cosmetic talcum powder.  To our knowledge, no risk assessment studies using exposure data from historical exposures or chamber simulations have been published. We conducted activity‐based sampling with cosmetic talcum powder samples from five opened and previously used containers that are believed to have been first manufactured and sold in the 1960s and 1970s.  These samples had been subject to conflicting claims of asbestos content; samples with the highest claimed asbestos content were tested.  The tests were conducted in simulated‐bathroom controlled chambers with volunteers who were talc users.  Air sampling filters were prepared by direct preparation techniques and analyzed by phase contrast microscopy (PCM), transmission electron microscopy (TEM) with energy‐dispersive x‐ray (EDX) spectra, and selective area diffraction (SAED).  TEM analysis for asbestos resulted in no confirmed asbestos fibers and only a single fiber classified as “ambiguous.”  Hypothetical treatment of this fiber as if it were asbestos yields a risk of 9.6 × 10^?7 (under one in one million) for a lifetime user of this cosmetic talcum powder.  The exposure levels associated with these results range from zero to levels far below those identified in the epidemiology literature as posing a risk for asbestos‐related disease, and substantially below published historical environmental background levels.  The approaches used for this study have potential application to exposure evaluations of other talc or asbestos‐containing materials and consumer products.     

Designing Graphs that Promote Both Risk Understanding and Behavior Change

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk‐avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm (“foreground+background”) versus only those affected (“foreground‐only”), and the presence versus absence of simple numerical labels above bars. Foreground‐only displays were associated with larger risk perceptions and risk‐avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground‐only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground‐only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk‐avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk‐avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground‐only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.     

A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population‐Based Epidemiology and Experimental Animal Tests

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real‐life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound‐by‐compound strategy (1.6%).     

When Is a Risk Assessment Deficient According to an Uncertainty‐Based Risk Perspective?

The Petroleum Safety Authority Norway (PSA‐N) has recently adopted a new definition of risk: “the consequences of an activity with the associated uncertainty.” The PSA‐N has also been using “deficient risk assessment” for some time as a basis for assigning nonconformities in audit reports. This creates an opportunity to study the link between risk perspective and risk assessment quality in a regulatory context, and, in the present article, we take a hard look at the term “deficient risk assessment” both normatively and empirically. First, we perform a conceptual analysis of how a risk assessment can be deficient in light of a particular risk perspective consistent with the new PSA‐N risk definition. Then, we examine the usages of the term “deficient” in relation to risk assessments in PSA‐N audit reports and classify these into a set of categories obtained from the conceptual analysis. At an overall level, we were able to identify on what aspects of the risk assessment the PSA‐N is focusing and where deficiencies are being identified in regulatory practice. A key observation is that there is a diversity in how the agency officials approach the risk assessments in audits. Hence, we argue that improving the conceptual clarity of what the authorities characterize as “deficient” in relation to the uncertainty‐based risk perspective may contribute to the development of supervisory practices and, eventually, potentially strengthen the learning outcome of the audit reports.     

Integrated Uncertainty Analysis for Ambient Pollutant Health Risk Assessment: A Case Study of Ozone Mortality Risk

The U.S. Environmental Protection Agency (EPA) uses health risk assessment to help inform its decisions in setting national ambient air quality standards (NAAQS). EPA's standard approach is to make epidemiologically‐based risk estimates based on a single statistical model selected from the scientific literature, called the “core” model. The uncertainty presented for “core” risk estimates reflects only the statistical uncertainty associated with that one model's concentration‐response function parameter estimate(s). However, epidemiologically‐based risk estimates are also subject to “model uncertainty,” which is a lack of knowledge about which of many plausible model specifications and data sets best reflects the true relationship between health and ambient pollutant concentrations. In 2002, a National Academies of Sciences (NAS) committee recommended that model uncertainty be integrated into EPA's standard risk analysis approach. This article discusses how model uncertainty can be taken into account with an integrated uncertainty analysis (IUA) of health risk estimates. It provides an illustrative numerical example based on risk of premature death from respiratory mortality due to long‐term exposures to ambient ozone, which is a health risk considered in the 2015 ozone NAAQS decision. This example demonstrates that use of IUA to quantitatively incorporate key model uncertainties into risk estimates produces a substantially altered understanding of the potential public health gain of a NAAQS policy decision, and that IUA can also produce more helpful insights to guide that decision, such as evidence of decreasing incremental health gains from progressive tightening of a NAAQS.     

Methodology for Determining the Appropriateness of a Linear Dose‐Response Function

Microbial food safety risk assessment models can often at times be simplified by eliminating the need to integrate a complex dose‐response relationship across a distribution of exposure doses. This is possible if exposure pathways lead to pathogens at exposure that consistently have a small probability of causing illness. In this situation, the probability of illness will follow an approximately linear function of dose. Consequently, the predicted probability of illness per serving across all exposures is linear with respect to the expected value of dose. The majority of dose‐response functions are approximately linear when the dose is low. Nevertheless, what constitutes “low” is dependent on the parameters of the dose‐response function for a particular pathogen. In this study, a method is proposed to determine an upper bound of the exposure distribution for which the use of a linear dose‐response function is acceptable. If this upper bound is substantially larger than the expected value of exposure doses, then a linear approximation for probability of illness is reasonable. If conditions are appropriate for using the linear dose‐response approximation, for example, the expected value for exposure doses is two to three logs₁₀ smaller than the upper bound of the linear portion of the dose‐response function, then predicting the risk‐reducing effectiveness of a proposed policy is trivial. Simple examples illustrate how this approximation can be used to inform policy decisions and improve an analyst's understanding of risk.     

Compliance Versus Risk in Assessing Occupational Exposures

Assessments of occupational exposures to chemicals are generally based upon the practice of compliance testing in which the probability of compliance is related to the exceedance [γ, the likelihood that any measurement would exceed an occupational exposure limit (OEL)] and the number of measurements obtained. On the other hand, workers’ chronic health risks generally depend upon cumulative lifetime exposures which are not directly related to the probability of compliance. In this paper we define the probability of “overexposure” (θ) as the likelihood that individual risk (a function of cumulative exposure) exceeds the risk inherent in the OEL (a function of the OEL and duration of exposure). We regard θ as a relevant measure of individual risk for chemicals, such as carcinogens, which produce chronic effects after long-term exposures but not necessarily for acutely-toxic substances which can produce effects relatively quickly. We apply a random-effects model to data from 179 groups of workers, exposed to a variety of chemical agents, and obtain parameter estimates for the group mean exposure and the within- and between-worker components of variance. These estimates are then combined with OELs to generate estimates of γ and θ. We show that compliance testing can significantly underestimate the health risk when sample sizes are small. That is, there can be large probabilities of compliance with typical sample sizes, despite the fact that large proportions of the working population have individual risks greater than the risk inherent in the OEL. We demonstrate further that, because the relationship between θ and γ depends upon the within- and between-worker components of variance, it cannot be assumed a priori that exceedance is a conservative surrogate for overexposure. Thus, we conclude that assessment practices which focus upon either compliance or exceedance are problematic and recommend that employers evaluate exposures relative to the probabilities of overexposure.     

PROPERTY RIGHTS AND THE EFFICIENCY OF BARGAINING

We show that efficient bargaining is impossible for a wide class of economic settings and property rights. These settings are characterized by (i) the existence of “adverse efficient opt‐out types”, whose participation does not change the efficient allocation and who, when they opt out, are the worst type other agents can face, and (ii) non‐existence of the “marginal core”, and its multivaluedness with a positive probability. We also examine the optimal allocation of property rights within a given class that satisfies (i), such as simple property rights, liability rules, and dual‐chooser rules. We characterize property rights that minimize the expected subsidy required to implement efficiency. With two agents, simple property rights that are optimal in this way maximize the expected surplus at the status quo allocation, but this no longer holds with more agents. We also study “second‐best” budget‐balanced bargaining under a liability rule. The optimal “second‐best” liability rule may differ from, but is often close to, the expectation of the victim's harm, which would be optimal if there were no bargaining. However, liability rules that are close to a simple property right result in a lower expected surplus than the simple property right they are near.     

重大供给冲击对石油市场的影响分析

收集历史上石油市场的重大供给冲击事件,包括委内瑞拉大罢工、伊拉克战争、卡特琳娜飓风、土耳其攻打库尔德、墨西哥湾漏油事件和利比亚战争,选取Brent、WTI现货和期货以及迪拜和阿曼现货等国际主要石油市场数据,建立GARCH模型,分析供给冲击对市场波动性的影响,进一步采用异方差修正的事件分析法考察这些事件对全球主要石油市场收益率的短期影响。研究结果表明,大部分事件会导致事件窗内的方差变大,除伊拉克战争和墨西哥湾漏油事件外,其他事件的事件窗内的累计超额收益显著为正,同一事件下所有市场事件窗内累计超额收益走势一致,重大事件发生的地理区位对邻近市场的收益率的影响更大。对实证结果进行经济解释,针对不同的石油市场参与者给出相应的政策建议。