Mortality Risks Induced by Economic Expenditures

Existing evidence shows that lower incomes are associated with higher mortality risks. This paper examines the implications for fatalities when the relationship is interpreted as an induced relationship, meaning that lower incomes will on average lead to higher mortality risks. A model is developed for estimating the number of fatalities possibly induced by economic expenditures. This model accounts for different allocations of the expenditures on family units with varying income levels. Illustrative calculations provide insights about the possible significance of fatalities induced by economic expenditures. These results suggest that some expensive regulations and programs intended to save lives may actually lead to increased fatalities. Important caveats to reduce the likelihood of misinterpreting or misusing the results are included.     

Fitting the Two-Stage Clonal Expansion Model Based on Exact Hazard to the ED01 Data Using SAS NLIN

The two-stage clonal expansion model is a popular model for carcinogenesis data. One common form of this model is based on the approximate hazard function. In certain situations, this formulation is not appropriate, and the exact hazard should be applied. However, the difficulty of implementing the model based on the exact hazard has deterred many from using it. This paper presents a program implementing the exact hazard model for piecewise constant dosing using SAS, a package that is readily available to most that are interested in this type of analysis. Also, an analysis of the ED₀₁ data is presented using this program, and comparisons are made to an earlier analysis based on the approximate hazard. By allowing for an independent background tumor mechanism, an excellent fit to the bladder tumor incidence data was obtained.     

A Multiattribute Utility Analysis of Alternative Sites for the Disposal of Nuclear Waste

Five potential sites nominated for the Nation's first geologic repository for disposing of nuclear waste are evaluated using multiattribute utility analysis. The analysis was designed to aid the Department of Energy in its selection of 3 sites for characterization, a detailed data-gathering process that will involve the construction of exploratory shafts for underground testing and that may cost as much as $1 billion per site. The analysis produced insights into the relative advantages and disadvantages of the nominated sites and clarified current uncertainties regarding repository performance.     

An Analysis of the Portfolio of Sites to Characterize for Selecting a Nuclear Repository

The U.S. Department of Energy has selected three sites, from five nominated, to characterize for a nuclear repository to permanently dispose of nuclear waste. This decision was made without the benefit of an analysis of this "portfolio" problem. This paper analyzes different portfolios of three sites for simultaneous characterization and strategies for sequential characterization. Characterization of each site, which involves significant subsurface excavation, is now estimated to cost $1 billion. Mainly because of the high characterization costs, sequential characterization strategies are identified which are the equivalent of $1.7-2.0 billion less expensive than the selected DOE simultaneous characterization of the three sites. If three sites are simultaneously characterized, one portfolio is estimated to be the equivalent of $100-400 million better than the selected DOE portfolio. Because of these potential savings and several other complicating factors that may influence the relative desirability of characterization strategies, a thorough analysis of characterization strategies that addresses the likelihood of finding disqualifying conditions during site characterization, uncertainties, and dependencies in forecast site repository costs, preclosure and postclosure health and safety impacts, potential delays of both sequential and simultaneous characterization strategies, and the environmental, socioeconomic, and health and safety impacts of characterization activities is recommended.     

Air pollution and depressive symptomatology: Exploratory analyses of intervening psychosocial factors

Exploratory modelling revealed associations of individual perceptions, social factors, and physical components of air pollution with depressive symptomatology. Residents of the Los Angeles Metropolitan Area who have experienced a recent, undesirable life event and who perceive poor air quality in their neighborhood have greater symptoms of depression. These effects control for socioeconomic status and prior psychological status. In addition we show that perceived air quality is a function of both toxic components of ambient air as well as individual psychosocial experiences.This research was supported by the National Institute for Mental Health (MH 28924-10A1) and the Southern California Edison Health Effects Research Laboratory (J-1909902). We thank Jean Ospital, Len Edwards, and Julian Foon for their assistance. Reprint requests should be sent to Gary Evans, Program in Social Ecology, University of California, Irvine, CA 92717.     

Multiple Attribute Decision Making with Inexact Value-Function Assessment

A major issue in value-function assessment is the possibility of receiving an indefinite response from a decision maker to a question about preferences. The conventional treatment requires a single, definite response from the decision maker. This approach either assumes that response error is zero or accepts the final solution as only approximate, without knowing how approximate it might be. In this paper we examine the issue of indefinite responses, define it more precisely, and present a method for incorporating it into decision making. The method is adaptive in that it is iterative and interactive with the decision maker who, at each iteration, is provided with information regarding the potential advantage of answering more trade-off questions and/or answering questions more carefully to reduce response error. In contrast to other approaches that “force” rationality and decisiveness, we work with irrationality and indecisiveness on the part of the decision maker. The method is demonstrated for the case of concave, increasing value functions.