Risk assessment, influencing factors

Performance-influencing factors analysis is an important part of the human reliability aspects of risk assessment. It can be applied in two areas. The first of these is the qualitative prediction of possible errors that could have a major impact on plant or personnel safety. The second is the evaluation of the operational conditions under which tasks are performed. These conditions will have a major impact in determining the probability that a particular error will be committed, and hence need to be systematically assessed as part of the quantification process. This application of PIFs will be described in Chapters 4 and 5. 

The risk assessment steps and the risk characterization are influenced by uncertainty and variability. Variability arise from heterogeneity such as dose-response differences within a population, or differences in contaminant levels in tlie environment. Uncertainty on tlie other lumd, represents lack of knowledge about factors such as adverse effects or contaminant levels. 

All risk assessment techniques, whether qualitative or quantitative, require an estimate of frequency of event occurrence. This frequency, which is extremely site specific, can be influenced by many factors. 

Risk management is the process of deciding what to do to reduce a known or suspected risk. Risk management balances the various community demands with the scientific information generated from the risk assessment. Public perception of risk is also considered. Table 19.2 characterizes some of the factors that influence perception of risk. An individual s perception of risk is sometimes very different from a risk... 

Studies of working women present the potential for additional bias, because some factors that influence employment status may also affect reproductive end-points. For example, because of child care responsibilities, women may terminate employment, as might women with a history of reproductive problems who wish to have children and are concerned about workplace exposures (Joffe, 1983 Lemasters Pinney, 1989). Thus, retrospective studies of female exposure that do not include terminated female workers may be of limited use in risk assessment, because the level of risk for some of the outcomes is likely to be overestimated (Lemasters Pinney, 1989). 

Answers to these questions provide preliminary insight into the variables for which extrapolation can be considered most urgent, due to an estimated numerical influence on the assessment results. For example, matrix and media extrapolation might be identified as the most important modifying factor, and the risk assessment might fully focus on this factor in the lowest tier. Information on issues for which no extrapolation will be applied need to be kept in the dossier, for reporting which factors have been considered and what numerical influence (magnitude and direction) is expected. 

Finally, the results of the uncertainty analysis should be adequately communicated, together with the results of the assessment. Addressing the uncertainties of the exposure assessment enables the risk assessor to distinguish risk characterization and risk assessment. Further, the results of the exposure assessment enable the risk manager to identify the key factors that influence exposures and risks. 

These four sub-criteria of the last category reflect many factors that have been proven to influence risk perception. The appraisal guidance published by the UK Treasury Department in 2005 recommends a risk appraisal procedure that is similar to our proposal and includes as well both the results of risk assessment and the direct input from data on public perception and the assessment of social concerns (HM Treasury 2005). 

In this chapter we have pointed to some fundamental physical environmental factors that in our view are important to take into account in order to improve REACH (and likely other chemical legislations). We have also pointed to the potential of an increased use of mathematical population models to obtain more relevant data for environmental risk assessment. With increased knowledge about how various physical environmental factors (e.g. temperature, pH, salinity, 02) on one hand influence toxicity and on the other may be taken into account in the process of environmental risk assessment, chances will improve to achieve a process that is efficient, cost effective, scientifically robust, and meets the demands of science-based precaution. Environmental risk assessment within REACH would thus become a more diverse but at the same time more adequate process than the one presented in the current version. 

Risk assessment evaluates risk in terms of hazard and exposure, but reference to risk levels must account for different perceptions of risk as well as scientific uncertainties in risk assessment. In short, this research project considers the importance of social and institutional processes in influencing risk perceptions and risk acceptability. This book therefore takes a constrained relativist approach by incorporating risk perceptions in the research framework. An unconstrained relativist perspective would imply that no scientific study is reliable or robust. By contrast, a constrained relativist approach can provide a useful basis for examining the different social and cultural factors involved in regulatory risk management. 

Dermal absorption is influenced by several factors, e.g. the physico-chemical properties of the substance, vehicle, occlusion, concentration, exposure pattern and skin site of the body (ECETOC, 1993 Howes et al., 1996 Schaefer and Redelmeier, 1996). Despite the fact that guidance exists for the conduct of dermal absorption studies (USEPA, 1998, 2004 OECD, 2004a,b,c), there continues to be discussion on some experimental details. In order to harmonize the use of dermal absorption data in human risk assessment within the EU, a guidance document was prepared by the Commission (EC, 2002). 

In addition to in vivo and in vitro experimentation, mathematical models and quantitative structure-permeability relationship (QSAR) methods have been used to predict skin absorption in humans. These models use the physico-chemical properties of the test compound (e.g. volatility, ionization, molecular weight, water/lipid partition, etc.) to predict skin absorption in humans (Moss et al 2002). The models are particularly attractive because of the low cost and rapidity. However, because of the above-mentioned factors influencing dermal absorption, mathematical models are of limited use for risk assessment purposes. Since these models are currently not accepted by regulatory agencies involved in pesticide evaluations, they will not be further discussed in this chapter. 

This chapter provides an overview of factors affecting dermal absorption. Factors influencing absorption are among others related to the skin (e.g. anatomical site, difference between species, metabolism, etc.) and the exposure conditions (e.g. area dose, vehicle, occlusion and exposure duration). In order to provide relevant information for the risk assessment of pesticides, dermal absorption studies should take these aspects into account. With respect to the methods being used nowadays for the assessment of dermal absorption, it is important to realize that neither in vitro nor in vivo animal studies have been formally validated. Available data from various in vitro studies, however, indicate that the use of the total absorbed dose (i.e. the amount of test substance in the receptor medium plus amount in the skin) could be used in a quantitative manner in risk assessment. Tape stripping of the skin can be adequate to give a good indication of test chemical distribution, and hence its immediate bioavailability. 

Hie quantitative estimate of the risk is tlie principal interest to tlie regulatory agency or risk manager making a decision. The risk manager must consider tlie results of tlie risk cliaracterization when evaluating tlie economics, societal aspects, and various benefits of the assessment. Factors such as societal pressure, technical uncertainties, and severity of tlie potential hazard influence how the decision makers respond to the risk assessment. As one iniglit suppose, there is room for improvement in this step of tlie risk assessment. ... 

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