Exposure-risk relationship

Hazard identification is the process of collecting and evaluating information on the effects of an agent on animal or human health and well-being. In most cases, this involves a careful assessment of the adverse effects and what is the most sensitive population. The dose-response assessment involves evaluation of the relationship between dose and adverse effect. Typically, an effort is made to determine the lowest dose or exposure at which an effect is observed. A comparison is often made between animal data and any human data that might be available. Next is exposure assessment, in which an evaluation of the likely exposure to any given population is assessed. Important parameters include the dose, duration, frequency, and route of exposure. The final step is risk characterization, in which all the above information is synthesized and a judgment made on what is an acceptable level of human exposure. In the simplest terms, risk is the product of two factors hazard and exposure (i.e. hazard x exposure = risk). In real risk assessments, all hazards may not be known and exposure is often difficult to quantify precisely. As a result, the calculated risk may not accurately reflect the real risk. The accuracy of a risk assessment is no better than the data and assumptions upon which it is based. 

In the most straightforward risk-based approach, epidemiologic studies have developed exposure-response relationships based on biomarker measurements in hair, blood, urine, or other matrices (e.g., mercury, lead) (see Figure 5-2a). The relationships can be applied directly to new biomonitoring data to determine where on the exposure-response curve any person is. That may facilitate an understanding of risk, but it does not analyze sources of exposure, so other techniques (such as environmental sampling and behavioral surveys) may be needed to assess where the exposure came from. 

Because human biomarkers are rarely the basis of exposure-response relationships, practitioners generally rely on more traditional risk assess-... 

Another option attempts to convert biomonitoring results into a form that is directly useful for risk assessment. The chapter describes both the human pharmacokinetic (PK) modeling used to relate internal concentration to dose and the development of exposure-response relationships in animal studies that use biomarker concentrations rather than applied dose (see Figure 5-2c). Finally, the chapter describes how biomonitoring studies can augment and help to interpret traditional risk assessments. 

The acceptable risks for substances that induce stochastic responses discussed in this Section are values in excess of unavoidable risks from exposure to the undisturbed background of naturally occurring agents that cause stochastic responses, such as many sources of natural background radiation and carcinogenic compounds produced by plants that are consumed by humans. This distinction is based on the assumption of a linear, nonthreshold dose-response relationship for substances that cause stochastic responses and the inability to control many sources of exposure. Risk management can address exposures to naturally occurring substances that induce stochastic responses, but only when exposures are enhanced by human activities or can be reduced by reasonable means. 

Kimmel GL (1995) Exposure-duration relationships The risk assessment process for health effects other than cancer. Inhal Toxicol, 7 873-880. 

First, this chapter will describe a conceptual framework to illustrate the special challenges posed because exposures assessed for epidemiologic studies must be relevant to the health outcome under investigation. Secondly, some of the most commonly applied epidemiological study designs will be introduced, with special emphasis on exposnre assessment issnes associated with the design. Thirdly, some widely applied exposure assessment approaches will be introduced, ranging from qualitative classifications of exposure to quantitative exposure assessment of pesticide concentrations. The influence of measurement error on measures of association between exposure and disease, such as the slopes of exposure-response relationships and risk or odds ratios, will be briefly reviewed. Finally, exposure proxies used in case-control studies of chronic effects of pesticide exposure will be reviewed and the concepts introduced earlier will be applied. 

As a result, to date epidemiological studies of pesticide exposures have only been indicative of the presence of elevated health risks. Quantitative studies contributing to evidence on exposure-response relationships which could be used for quantitative risk assessment purposes are not widely available. This implies that the epidemiological potential has not been explored to its limits, as has been done for certain other agents such as asbestos and lead, for which present legislation has been based, to a large extent, on quantitative evidence of health risks in humans obtained from epidemiological studies. 

Knowledge of the relationship between dose and response (effect), and the threshold for this, is crucial in defining the risk of exposure to a chemical. Safety evaluation is a legal requirement for drugs, food additives, and contaminants in food, and a risk assessment has to be carried out in order to set the limits of exposure. The relationship between the dose and the response (effect) can be established and plotted as a graph. This is called a dose-response curve (see Figure 29 and box), which often shows that there is a dose(s) of the chemical that has no effect and another, higher dose(s) which has the maximum effect. It is a visual representation of the Paracelsus principle that, at some dose, all chemicals are toxic. The corollary to this is that there is a dose(s) at which there is no effect. 

Secondly, the above issues then need to be placed in a concentration-effect relationship. The main issue then is the determination of the appropriate dose metric. What is the amount (or concentration) of the chemical under study that is responsible for the effect In other words how do we determine the appropriate exposure at the site of toxic action related to the primary chemico-biological interaction that forms the basis of the compound s toxicity The commonly used practice is to relate the effects to the nominal concentration, i.e., the amount of compound added to the in vitro system divided by its volume. If data from this exposure-effect relationship are to be the basis of an estimation of risk for an organism, this approach may be a source of errors in those cases where the local exposure of the cells in vitro differs from the exposure of targets in the in vivo situation [9], These differences can result from differences in protein binding in plasma vs. culture medium or other processes that may influence the local exposure at the target, e.g., binding to culture plastic [10, 11], More appropriate dose metrics, depending on the in vitro system as well as on the chemical s mechanism of action, may be the freely available concentration, either as the peak concentration or as the area under the curve (AUC) for the free concentration, or the intracellular concentration [12]. 

A recent study examined the exposure-response relationship between biomass combustion and ARI in children of rural Kenyan households [41]. This was preceded by rigorous quantitative exposure assessments in the same households [22]. Quantitative exposure assessments are therefore crucial for the development of exposure-response relationships and greatly facilitate subsequent health risk assessments. 

Pharmacokinetic models to describe, as a function of formaldehyde air concentration, the rate of formation of formaldehyde-induced DNA-protein cross links in different regions of the nasal cavity have been developed for rats and monkeys (Casanova et al. 1991 Heck and Casanova 1994). Rates of formation of DNA-protein cross links have been used as a dose surrogate for formaldehyde tissue concentrations in extrapolating exposure-response relationships for nasal tumors in rats to estimate cancer risks for humans (EPA 1991a see Section 2. 4.3). The models assume that rates of cross link formation are proportional to tissue concentration of formaldehyde and include saturable and nonsaturable elimination pathways, and that regional and species differences in cross link formation are primarily dependent on anatomical parameters (e g., minute volume and quantity of nasal mucosa) rather than biochemical parameters. The models were developed with data from studies in which... 

Controlled human exposure studies are essential to establish the health consequences of PM exposures. These studies are typically designed to study inhalation of size-defined PM under highly controlled conditions that will allow the characterization of exposure-response relationships. Since humans are exposed to the pollutant of interest, specifically size-fractionated PM, causahty can be established easily and the confounding effects of other pollutants can be minimized (Devlin et al. 2005). Another advantage of such clinical studies is the abihty to select subjects with a known clinical status (i.e., healthy vs. a specific disease, typically cardiovascular or pulmonary disease) and observe the pathophysiological responses of interest. However, controlled human exposures have some limitations (Utell and Frampton 2000). For both practical and ethical reasons, clinical studies are restricted to exposure concentrations and durations that will only ehcit transient responses in human subjects. These studies involve a small number of sample subjects, which excludes susceptible populations at higher risk. Chronic exposure or high PM concentration related health effects are not attainable by the clinical studies. These experiments are also very costly to perform. 

The purpose of this chapter is to give a literature survey of the most important macro factors and concepts in road accidents. It describes the road safety problem as a junction of three dimensions (exposure, risk and consequences). The chapter discusses the relationship between different factors and accident risk. This will be useful to choose the most important performance indicators that could be used as benchmarks in international comparisons. I also give a brief literature review of the most important and/or recent macroscopic models in road safety that are used for describing the development in road safety in a country and internationally. Finally, I conclude this chapter with important notes regarding under-reporting of data and the correction factor. 

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