Bootstrap Estimation of Benchmark Doses and Confidence Limits with Clustered Quantal Data

The benchmark dose (BMD) is an exposure level that would induce a small risk increase (BMR level) above the background. The BMD approach to deriving a reference dose for risk assessment of noncancer effects is advantageous in that the estimate of BMD is not restricted to experimental doses and utilizes most available dose-response information. To quantify statistical uncertainty of a BMD estimate, we often calculate and report its lower confidence limit (i.e., BMDL), and may even consider it as a more conservative alternative to BMD itself. Computation of BMDL may involve normal confidence limits to BMD in conjunction with the delta method. Therefore, factors, such as small sample size and nonlinearity in model parameters, can affect the performance of the delta method BMDL, and alternative methods are useful. In this article, we propose a bootstrap method to estimate BMDL utilizing a scheme that consists of a resampling of residuals after model fitting and a one-step formula for parameter estimation. We illustrate the method with clustered binary data from developmental toxicity experiments. Our analysis shows that with moderately elevated dose-response data, the distribution of BMD estimator tends to be left-skewed and bootstrap BMDL s are smaller than the delta method BMDL s on average, hence quantifying risk more conservatively. Statistically, the bootstrap BMDL quantifies the uncertainty of the true BMD more honestly than the delta method BMDL as its coverage probability is closer to the nominal level than that of delta method BMDL. We find that BMD and BMDL estimates are generally insensitive to model choices provided that the models fit the data comparably well near the region of BMD. Our analysis also suggests that, in the presence of a significant and moderately strong dose-response relationship, the developmental toxicity experiments under the standard protocol support dose-response assessment at 5% BMR for BMD and 95% confidence level for BMDL.     

A Process for Incorporating Comparative Risk into Environmental Policymaking in Louisiana

The goal of Louisiana's 1990–1991 comparative risk project, also called the Louisiana Environmental Action Plan (LEAP), was to incorporate risk assessment into state environmental planning and policymaking. Scientists, government officials, and citizens were brought together to estimate the relative risk to human health, natural resources, and quality of life posed by 33 selected environmental issues. The issues were then ranked according to their relative estimated risks. It was hoped that this ranking of "comparative risks" would enable state policymakers to target the most important environmental problems and allocate scarce public resources more rationally and efficiently. As a result of the project, the governor issued an Executive Order forming a permanent Public Advisory Committee to continue this type of comparative risk assessment in Louisiana.     

Summary of the Workshop on Issues in Risk Assessment: Quantitative Methods for Developmental Toxicology

This report summarizes the proceedings of a conference on quantitative methods for assessing the risks of developmental toxicants. The conference was planned by a subcommittee of the National Research Council's Committee on Risk Assessment Methodology ⁴ in conjunction with staff from several federal agencies, including the U.S. Environmental Protection Agency, U.S. Food and Drug Administration, U.S. Consumer Products Safety Commission, and Health and Welfare Canada. Issues discussed at the workshop included computerized techniques for hazard identification, use of human and animal data for defining risks in a clinical setting, relationships between end points in developmental toxicity testing, reference dose calculations for developmental toxicology, analysis of quantitative dose-response data, mechanisms of developmental toxicity, physiologically based pharmacokinetic models, and structure-activity relationships. Although a formal consensus was not sought, many participants favored the evolution of quantitative techniques for developmental toxicology risk assessment, including the replacement of lowest observed adverse effect levels (LOAELs) and no observed adverse effect levels (NOAELs) with the benchmark dose methodology.     

Intuitive Toxicology: Expert and Lay Judgments of Chemical Risks

Human beings have always been intuitive toxicologists, relying on their senses of sight, taste, and smell to detect harmful or unsafe food, water, and air. As we have come to recognize that our senses are not adequate to assess the dangers inherent in exposure to a chemical substance, we have created the sciences of toxicology and risk assessment to perform this function. Yet despite this great effort to overcome the limitations of intuitive toxicology, it has become evident that even our best scientific methods still depend heavily on extrapolations and judgments in order to infer human health risks from animal data. Many observers have acknowledged the inherent subjectivity in the assessment of chemical risks and have indicated a need to examine the subjective or intuitive elements of expert and lay risk judgments. We have begun such an examination by surveying members of the Society of Toxicology and the lay public about basic toxicological concepts, assumptions, and interpretations. Our results demonstrate large differences between toxicologists and laypeople, as well as differences between toxicologists working in industry, academia, and government. In addition, we find that toxicologists are sharply divided in their opinions about the ability to predict a chemical's effect on human health on the basis of animal studies. We argue that these results place the problems of risk communication in a new light. Although the survey identifies misconceptions that experts should clarify for the public, it also suggests that controversies over chemical risks may be fueled as much by limitations of the science of risk assessment and disagreements among experts as by public misconceptions.     

Professional Perspectives on Decision Making about the Long-term Care of Older People

With the increasing pressure on social and health care resources,professionals have to be more explicit in their decision makingregarding the long-term care of older people. This groundedtheory study used 19 focus groups and nine semi-structured interviews(99 staff in total) to explore professional perspectives onthis decision making. Focus group participants and intervieweescomprised care managers, social workers, consultant geriatricians,general medical practitioners, community nurses, home care managers,occupational therapists and hospital discharge support staff.The emerging themes spanned context, clients, families and services.Decisions were often prompted by a crisis, hindering professionalsseeking to make a measured assessment. Fear of burglary andassault, and the willingness and availability of family to helpwere major factors in decisions about living at home. Serviceavailability in terms of public funding for community care,the availability of home care workers and workload pressureson primary care services influenced decision ‘thresholds’regarding admission to institutional care. Assessment toolsdesigned to assist decision making about the long-term careof older people need to take into account the critical aspectsof individual fears and motivation, family support and the availabilityof publicly funded services as well as functional and medicalneeds.     

Ordinal utility models of decision making under uncertainty

This paper studies two models of rational behavior under uncertainty whose predictions are invariant under ordinal transformations of utility. The quantile utility model assumes that the agent maximizes some quantile of the distribution of utility. The utility mass model assumes maximization of the probability of obtaining an outcome whose utility is higher than some fixed critical value. Both models satisfy weak stochastic dominance. Lexicographic refinements satisfy strong dominance.The study of these utility models suggests a significant generalization of traditional ideas of riskiness and risk preference. We define one action to be riskier than another if the utility distribution of the latter crosses that of the former from below. The single crossing property is equivalent to a minmax spread of a random variable. With relative risk defined by the single crossing criterion, the risk preference of a quantile utility maximizer increases with the utility distribution quantile that he maximizes. The risk preference of a utility mass maximizer increases with his critical utility value.     

The Seveso Directive: An Italian Pilot Study in Enabling Communication

In 1982 the Council of the European Communities issued a Directive on the Major Accident Hazards of Certain Industrial Activities, commonly known as the Seveso Directive. Besides other requirements, the Directive specifies that members of the public liable to be affected by a major accident from certain industrial activities must be informed of safety measures and how they should behave in the event of an accident. The Directive was subsequently amended in an extensive way. Upon the transposition of the Seveso Directive and its amendments into national legislations, the 12 European Member States are faced with the task of "appropriately and effectively" informing the public about major accident hazards. Delays are observed throughout the community, both in transposing the Directives and implementing public information. A pilot study on "Risk Information Needs" was commissioned and carried out at two Seveso sites in Italy in order to begin to resolve some of the problems involved in the provision of public information and to suggest appropriate guidelines. One hundred subjects answered an experimental protocol designed to assess their "information needs." This article presents the theoretical background, the pragmatic aims, and the design of the study. It also summarizes its most relevant findings and suggests some recommendations for the provision of information to the public.     

Coherent decision analysis with inseparable probabilities and utilities

This article explores the extent to which a decision maker's probabilities can be measured separately from his/her utilities by observing his/her acceptance of small monetary gambles. Only a partial separation is achieved: the acceptable gambles are partitioned into a set of belief gambles, which reveals probabilities distorted by marginal utilities for money, and a set of preference gambles, which reveals utilities reciprocally distorted by marginal utilities for money. However, the information in these gambles still enables us to solve the decision maker's problem: his/her utility-maximizing decision is the one that avoids arbitrage (i.e., incoherence or Dutch books).     

De minimis and equity in risk

Indices and orderings are developed for evaluating alternative strategies in the management of risk. They reflect the goals of reducing individual and collective risks, of increasing equity, and of assigning priority to the reduction and to the equity of high risks. Individual risk is defined as the (random or non-random) level of exposure to a danger. In particular the role of a lower negligibility level is investigated. A class of indices is proposed which involves two parameters, a negligibility level and a parameter of inequality aversion, and several interpretations of the indices are discussed. We provide a set of eight axioms which are necessary and sufficient for this class of indices, and we present an approach to deal with partial information on the parameters.     

网络时代农产品质量安全事件风险放大机制研究——基于价值累加理论的扎根分析

随着互联网的飞速发展,农产品质量安全事件借助网络媒体持续关联与聚合、发酵与扩散,极大地影响着公众的情感和态度,易引发集体非理性恐慌,网络时代信息扩散和迭代呈现全新特征和趋势,故加强农产品质量安全事件风险放大机制研究具有重要意义。基于斯梅尔塞的价值累加理论,结合“土坑酸菜”事件,利用Python技术获取媒体原始资料,对资料进行扎根编码分析,构建农产品质量安全事件风险放大机制模型。根据编码结果识别出农产品质量安全事件风险放大六大主范畴,包括结构性诱因、结构性紧张、一般化信念、(有效的)组织动员、社会控制、风险放大,将主范畴内容纳入价值累加理论六大因素中,分析表明农产品质量安全事件风险放大是以突发事件为分界点,分为前期蓄势、中期造势、紧急处理三个阶段,前期蓄势和中期造势阶段通过多轮循环相互反馈影响,最终放大农产品质量安全事件风险。在整个风险扩散过程中,网络是农产品质量安全事件风险的“社会放大站”,其加速了信息传播,强化了公众风险感知。本研究运用价值累加理论、基于宏观和微观整合层面,细化探究了网络时代农产品质量安全事件风险放大的完整过程机制,进一步完善了风险放大SARF研究框架,为相关研究做了有益补充。