Life cycle impact assessment: a challenge for risk analysts.

Modern technology, together with an advanced economy, can provide a good or service in myriad ways, giving us choices on what to produce and how to produce it. To make those choices more intelligently, society needs to know not only the market price of each alternative, but the associated health and environmental consequences. A fair comparison requires evaluating the consequences across the whole "life cycle"--from the extraction of raw materials and processing to manufacture/construction, use, and end-of-life--of each alternative. Focusing on only one stage (e.g., manufacture) of the life cycle is often misleading. Unfortunately, analysts and researchers still have only rudimentary tools to quantify the materials and energy inputs and the resulting damage to health and the environment. Life cycle assessment (LCA) provides an overall framework for identifying and evaluating these implications. Since the 1960s, considerable progress has been made in developing methods for LCA, especially in characterizing, qualitatively and quantitatively, environmental discharges. However, few of these analyses have attempted to assess the quantitative impact on the environment and health of material inputs and environmental discharges Risk analysis and LCA are connected closely. While risk analysis has characterized and quantified the health risks of exposure to a toxicant, the policy implications have not been clear. Inferring that an occupational or public health exposure carries a nontrivial risk is only the first step in formulating a policy response. A broader framework, including LCA, is needed to see which response is likely to lower the risk without creating high risks elsewhere. Even more important, LCA has floundered at the stage of translating an inventory of environmental discharges into estimates of impact on health and the environment. Without the impact analysis, policymakers must revert to some simple rule, such as that all discharges, regardless of which chemical, which medium, and where they are discharged, are equally toxic. Thus, risk analysts should seek LCA guidance in translating a risk analysis into policy conclusions or even advice to those at risk. LCA needs the help of RA to go beyond simplistic assumptions about the implications of a discharge inventory. We demonstrate the need and rationale for LCA, present a brief history of LCA, present examples of the application of this tool, note the limitations of LCA models, and present several methods for incorporating risk assessment into LCA. However, we warn the reader not to expect too much. A comprehensive comparison of the health and environmental implications of alternatives is beyond the state of the art. LCA is currently not able to provide risk analysts with detailed information on the chemical form and location of the environmental discharges that would allow detailed estimation of the risks to individuals due to toxicants. For example, a challenge for risk analysts is to estimate health and other risks where the location and chemical speciation are not characterized precisely. Providing valuable information to decisionmakers requires advances in both LCA and risk analysis. These two disciplines should be closely linked, since each has much to contribute to the other.     

The Role of Second-Order Belief-Understanding and Social Context in Children's Self-Attribution of Social Emotions

Children's self-attribution of social emotions was hypothesised (i) to be related to their second-order belief-understanding and (ii) to be more strongly related to social- conventional than moral rule violations. Thirty children aged between 4 and 7 years were presented with Sullivan, Zaitchik & Tager-Flusberg's (1994) second-order false belief task and with four hypothetical scenarios in which they were required to imagine that they had violated particular moral and social conventional rules. As predicted, the self-attribution of social emotions was significantly related to second-order belief understanding, primarily in social-conventional rather than moral contexts.     

Race,Rural Residence,and Wildland Visitation: Examining the Influence of Sociocultural Meaning1

Abstract Previous studies have shown that African Americans have less favorable impressions about wildlands and recreate on wildland areas less frequently than do whites. However, most of these investigations have been conducted on non-rural populations. Rural perceptions of wildlands and visitation to such areas have received relatively little attention. In this exploratory study, we propose that race operates on wildland recreation visitation through the different meanings rural blacks and whites attribute to wildlands. We examine this hypothesis with a structural model which specifies wildland meaning as an intervening factor between race and visitation. Single equation results show blacks visit wildlands less, and have less favorable definitions of wildlands, compared to whites. However, when wildland meaning is included in the structural model, racial differences become insignificant. This suggests that the meanings different racial groups attach to wildlands help explain visitation. Both sex and age are also significant predictors of both wildland meaning and visitation.     

Accelerated life regression modelling of dependent bivariate time‐to‐event data

To analyze bivariate time‐to‐event data from matched or naturally paired study designs, researchers frequently use a random effect called frailty to model the dependence between within‐pair response measurements. The authors propose a computational framework for fitting dependent bivariate time‐to‐event data that combines frailty distributions and accelerated life regression models. In this framework users can choose from several parametric options for frailties, as well as the conditional distributions for within‐pair responses. The authors illustrate the flexibility that their framework represents using paired data from a study of laser photocoagulation therapy for retinopathy in diabetic patients.