Population risk, estimation

Mohrenweiser, H.W. and I.M. Jones, "Variation in DNA Repair is a Factor in Cancer Susceptibility A Paradigm for the Promises and Perils of Individual and Population Risk Estimation " Mutat. Res., 400, 15-24 (1998). 

It is challenging to extrapolate general surveillance data, particularly with limited health-effects data, to individual risk estimates without the genetic, external-exposure, lifestyle, and other data that a clinician could use to adjust population risk estimates for individual cases. As a result, previous comments about communication difficulties with respect to health implications apply far more to surveillance studies than they do to the interaction of a personal or occupational physician with an individual patient or worker on whom the physician also has extensive nonbiomarker information. For example, clinicians might in rare cases determine that BEIs are appropriate comparison values for a specific patient s biomarker concentrations. 

The model contains a surface energy method for parameterizing winds and turbulence near the ground. Its chemical database library has physical properties (seven types, three temperature dependent) for 190 chemical compounds obtained from the DIPPR" database. Physical property data for any of the over 900 chemicals in DIPPR can be incorporated into the model, as needed. The model computes hazard zones and related health consequences. An option is provided to account for the accident frequency and chemical release probability from transportation of hazardous material containers. When coupled with preprocessed historical meteorology and population den.sitie.s, it provides quantitative risk estimates. The model is not capable of simulating dense-gas behavior. 

A risk estimate indicates Uie likelihood of occurrence of the different types of health or enviroinnental effects in exposed populations. Risk assessment should include both liuimn health and environmental evaluations (i.c., impacts on ecosystems). Ecological impacts include actual or potential effects on plants and animals (other than domesticated species). The number produced from the risk characleriznlion, representing the probability of adi crse... 

One should identify exposure pathways that have the potential to expose the same individual or sub-population at the key exposure areas evaluated in the exposure assessment, making sure to consider areas of highest exposure for each patliway for both current and future land-uses (c.g., nemest down-gradient well, nearest dowiuvind receptor). For each pathway, the risk estimates and hazard indices have been developed for a particular exposure area... 

Other ground water Laek of information individual risks eonsidered less tluui 10" , with rough estimate of total population risk at <1... 

Risk characterization estimates tlie healtli risk associated with tlie process under investigation. The result of tliis cliaracterization is a number tliat represents tlie probability of adverse healtli effects from tliat process or from a substance released in tliat process. Tlie major types of risk include Individual Risk, Maximum Individual Risk (MIR), Population Risk (PR), Societal Risk, and Risk Indices. 

The health effect side of the diagram shows that unit risk estimates result from interactive analyses of health-affecting processes in the human body and observed effects in human populations (epidemiology). Health effects are identified by integrating clinical studies on humans or animals with studies of physical and chemical responses to pollutant agents in the human body. 

Taking the possible health effects caused by inhaled Rn-222 progeny in the general public into account, better risk estimates based on epidemiological studies on the general population are urgently needed. 

Infection with Helicobacter pylori is widely spread in the world and as many as 50% of the population is estimated to be infected, with the highest incidence in Asia and developing countries. The bacterial toxins of Helicobacter pylori damage the epithelial cells in the stomach and can in the long term lead to gastric atrophy (Pilotto 1996, Faisal et al. 1990, Pilotto et al. 1999). The consequential decrease in secretion of acid causes a higher gastric pH level which can increase the risk of enteric infections, for example, with Campylobacter and Clostridium difficile. 

There have been attempts to develop explicit risk estimates for agents presumed to act through threshold mechanisms. Some investigators have proposed the use of models which assume that toxic responses and the thresholds for them follow a certain distribution over the population. The use of such models may reveal how the distribution of response shifts as dose shifts. Unfortunately most toxicology data are not reported in a form that allows ready use of such distribution models. 

On the basis of the foregoing discussion, it appears that, if traditional criteria for hazard evaluation are applied to the toxicologic data on experimental animals, there is little room for complacency r arding current ambient concentrations of ozone. Functional, biochemical, and structural effects in both pulmonary and extrapulmonary sterns have been reported by numerous investigators at or near concentrations that are at least occasionally achieved in some polluted urban centers. Unfortunately, there are no adequate methods for extrapolating data to obtain reliable quantitative estimates of population risk at environmental concentrations near the standard, and there is no assurance that the risk is zero. 

In view of the considerable uncertainties in the extrapolation of results over several orders of magnitude, specification of risks in terms of predicted incidence or numbers of excess cancers per unit of the population implies a degree of precision that is considered misleading by some. Larsen (2006), e.g., noted that the model most often used in low-dose extrapolation is a linear extrapolation from the observable range, and the apparent precision of the calculations does not reflect the uncertainty in the risk estimate the results are therefore open to misinterpretation because the numerical estimates may be regarded as quantification of the actual risk. 

Some EU Member States have also applied similar lifetime cancer risk estimates in judging tolerable risk levels. There is as yet no EU harmonized view on such default risk estimates at a policy level, although the starting point for the derivation of limit values for the general population in relation to the EU directives on ambient air and drinking water quality is the 10 lifetime risk for genotoxic carcinogens. 

The WHO has cautioned that the risk estimates presented should not be regarded as being equivalent to the true cancer risk, and that the crude expression of risk in terms of excess incidence or numbers of cancers per unit of the population at doses or concentrations much less than those on which the estimates are based may be inappropriate. Estimated risks are believed to represent only the plausible upper bounds, and may vary widely depending on the assumptions on which they are based. 

Because an agent may induce multiple mmor types, the dose-response assessment includes an analysis of aU tumor types, followed by an overall evaluation that includes a characterization of the risk estimates across tumor types, the strength of the mode of action information of each mmor type, and the anticipated relevance of each mmor type to humans, including susceptible populations and fife stages (e.g., childhood). 

Risk characterization is Estimation of the incidence and severity of the adverse effects likely to occur in a human population or environmental compartment due to actual or predicted exposure to a substance, and may include risk estimation , i.e., the quantification of that likelihood. ... 

In 1976, a final report from the International Register of Lithium Babies contained information on 225 infants exposed to lithium in the first trimester. Cardiovascular anomalies occurred in 18 (8%) of the newborns, of which 6 (2.7%) had Ebstein s anomaly (Weinstein, 1976). A comprehensive review of this report and the multiple studies that have been conducted since (Cohen et ah, 1994) revealed that the risk of congenital defects after in utero exposure to lithium is less than previously anticipated. Currently, the risk for Ebstein s anomaly after first-trimester exposure to lithium is estimated to be 1 in 1000 (0.1%) (Altshuler et ah, 1996), or 10-20 times greater than the general population risk of 1 in 20,000 (Weinstein, 1976). Thus, the absolute risk for Ebstein s anomaly is small. 

Radiation-induced genomic instability and bystander effects are now well-established consequences of exposure of living cells to ionizing radiation. Cells not directly traversed by radiation may still exhibit radiation effects. This phenomenon, known as bystander effect, has become a major activity in radiation biology and in some cases has challenged the conventional wisdom. An example is the currently accepted models used for low-dose extrapolation of radiation risks. The currently used models assume that cells in an irradiated population respond individually rather than collectively. If bystander effects have implications for health risks estimates from exposure to ionizing radiation, then the question of whether this is a general phenomenon or solely a characteristic of a particular type of cell and the radiation under test becomes an important issue. 

When epidemiological data are available, the issues to be dealt with include selection of the appropriate study and control populations, evaluation of exposure levels and tissue doses, determination of the reliability of cancer ascertainment, allowance for the latent period and age distribution of cancers, control of biases and confounding factors, fitting of models to the data to characterize the dose-incidence relationship, and derivation of risk estimates with their associated ranges of uncertainty. 

In order to determine the effective dose of a given agent to the population at risk, evaluators need to take into account such variables as the duration and intensity of exposure, the age distribution of exposed persons at the time of their exposure, their sex, state of disease or health, and the estimated concentrations of the agent and its metabolic derivatives in various tissues of the body. Also, insofar as possible, the mode of action of the agent should be characterized in order to enable selection of the appropriate dose-incidence model for use in risk estimation. 

Reproductive risk descriptors are intended to address variability of risk within the population and the overall adverse impact on the population. In particular, differences between high-end and central tendency estimates reflect variability in the population but not the scientific uncertainty inherent in the risk estimates. There is uncertainty in all estimates of risk, including reproductive risk. These uncertainties can result from measurement uncertainties, modelling uncertainties and assumptions made due to incomplete data. Risk assessments should address the impact of each of these uncertainties on confidence in the estimated reproductive risk values. 

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