Science and Judgment in Risk Assessment (1994) / Chapter Skim
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10 Variability
10 Variability
Pages 188-223
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From page 188... ...
, and then for the remainder of the chapter focus only on variability in quantities that directly influence calculations of individual and population risk. When an important quantity is both uncertain and variable, opportunities 188
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From page 189... ...
Certainly, the regulation of air pollutants has long recognized that chemicals differ from each other in their physical and toxic properties and that sources differ from each other in their emission rates and characteristics; such variability is built into virtually any sensible question of risk assessment or control. However, even if we focus on a single substance emanating from a single stationary source, variability pervades each stage from emission to health or ecologic end point: · Emissions vary temporally, both in flux and in release characteristics, such as temperature and pressure.
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From page 190... ...
190 SCIENCE AND JUDGMENT IN RISK ASSESSMENT Ignoring UncertaintyFew Data Ignoring Uncertainty Many Data Ignoring Variation ~I r . ~ ~1 1 'a 1 Reality ~/ FIGURE 10-1 Effects of ignoring uncertainty versus ignoring variability in measuring the distance between the earth and the moon.
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From page 191... ...
For example, a specific type of air-pollution monitor might collect air for 15 min of each hour and report the 15-min average concentration of some pollutant. Such values might then be further aggregated to produce summary values at an even coarser time scale.
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From page 192... ...
This strategy is not the same as ignoring the variability; ideally, it follows from a decision that the average value can be estimated reliably in light of the variability, and that it is a good surrogate for the variable quantity. For example, EPA often uses 70 kg as the average body weight of an adult, presumably because although many adults weigh as little as 40 kg and as much as 100 kg, the average weight is almost as useful as (and less complicated than)
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From page 193... ...
If it is determined for a particular policy rationale that the distribution of individual risks across the population does not matter, then the product of average concentration, potency and population size equals the expected incidence, and the spread of concentrations about the average concentration is similarly unimportant. The average value is also the summary statistic of choice for social decisions when there is an opportunity for errors of underestimation and overestimation (which lead to underregulation and overregulation)
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From page 194... ...
, we cannot know how reliably our estimate of the average value reflects the true average, nor how well the observed minimum and maximum mirror the true extremes. The distribution for an important variable such as metabolic rate should thus explicitly be considered in the risk assessment, and the reliability of the overall risk estimate should reflect knowledge about both the uncertainty and the variability in this characteristic.
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From page 195... ...
replace the linearized-multistage model, default models that ignored human variability or took conservative measures to sidestep it will be supplanted by models that explicitly contain values of biologic measures intended to represent the human population. If the latter models ignore variability or use unverified surrogates for presumed average or worst-case properties, risk assessment might take a step backwards, becoming either less or more conservative without anyone's knowledge.
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From page 196... ...
If, for example, we could precisely measure the airborne concentration of a pollutant in a community around a stationary source (i.e., understand the spatial variability) , but did not know the population distribution of breathing rates, we could not predict anyone's "actual exposure." In fact, even if we knew both distributions but could not superimpose them (i.e., know which breathing rates went with which concentrations)
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From page 197... ...
The variabilities in emissions atmospheric processes, characteristics of the microenvironment, and personal activity are not necessarily independent of each other; for example, personal activities and pollutant concentrations at a specific location might change in response to outdoor temperature; they might also differ between weekends and weekdays because the level of industrial activity changes. Emissions Variability There are basically four categories of emission variability that may need separate assessment methods, depending on the circumstances: · Routine this is the type most frequently covered by current approaches.
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From page 198... ...
Some quantitative information is available about the impact of meteorologic variability on pollutant concentrations. Concentrations measured at one location over some period tend to follow a lognormal distribution.
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From page 199... ...
For example, the lifetime-exposed 70-year-old has been faulted as an extreme case, but it is instructive to consider this hypothetical person in the distribution of personal activity traits. Although it is unlikely, this 70-year lifetime exposure activity pattern is one end of the spectrum in the variability of personal activity and time spent in a specific microenvironment.
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From page 200... ...
Such interindividual differences can be inherited or acquired. For example, inherited differences in susceptibility to physical or chemical carcinogens have been observed, including a substantially increased risk of sunlight-induced skin cancer in people with xeroderma pigmentosum, of bladder cancer in dyestuff workers whose genetic makeup results in the "poor acetylator" phenotype, and of bronchogenic carcinoma in tobacco smokers who have an "extensive debrisoquine hydroxylator" phenotype (both are described further in Appendix H)
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From page 201... ...
, we could estimate the risks that each would face if subjected to the same exposure to a carcinogen. If the estimated risk to the first type of person were 10-2 and the estimated risk to the second type of person were 10-6, we could say that "human susceptibility to this chemical varies by at least a factor of 10,000.-4 There are two distinct but complementary approaches to estimating the form and breadth of the distribution of interindividual variability in overall susceptibility to carcinogenesis.
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From page 202... ...
or as large as a factor of 50,000 (if the logarithmic standard deviation was 2.7~.5 The alternative approach is inferential or "top-down," and combines epidemiologic data with a demographic technique known as heterogeneity dynamics. Heterogeneity dynamics is an analytic method for describing the changing characteristics of a heterogeneous population as its members age.
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From page 203... ...
Exposure Variability and the Maximally Exposed Individual One of the contentious defaults that has been used in past air-pollutant exposure and risk assessments has been the maximally exposed individual (MEI) , who was assumed to be the person at greatest risk and whose risk was calculated by assuming that the person resided outdoors at the plant boundary, continuously for 70 years.
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From page 204... ...
The distribution of exposures, developed from measurements or modeling results or both, should be used to estimate population exposure, as an input in calculating population risk. It can also be used to estimate the exposure of the maximally exposed person.
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From page 205... ...
Furthermore, some exposures to different pollutants may be considered as interchangeable: moving from one place to another may yield exposures to different pollutants which, being interchangeable in their effects, can be taken as an aggregate, single "exposure." This assumption of interchangeability may or may not be realistic; however, because people moving from place to place can be seen as being exposed over time to a mixture of pollutants, some of them simultaneously and others at separate times, a simplistic analysis of residence times is not appropriate. The real problem is, in effect, a more complex problem of how to aggregate exposure to mixtures as well as one of multiple exposures of varying level of intensities to a single pollutant.
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From page 206... ...
On the basis of substantial theory and some observational evidence, it appears that some of the individual determinants of susceptibility are distributed bimodally (or perhaps trimodally) in the human population; in such cases, a class of hypersusceptible people (e.g., those with germ-line mutations in tumor-suppressor genes)
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From page 207... ...
Any error of overestimation in rodent-to-human scaling (or in epidemiologic analysis) will tend to counteract the underestimation errors that must otherwise be introduced into some individual risk estimates by EPA's current practice of not distinguishing among different degrees of human susceptibil
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From page 208... ...
EPA could choose to incorporate into its cancer risk estimates for individual risk (not for population risk) a "default susceptibility factor" greater than the implicit factor of 1 that results from treating all humans as identical.
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From page 209... ...
A 10-fold adjustment might yield a reasonable best estimate of the high end of the susceptibility distribution for some pollutants when only a single predisposing factor divides the population into normal and hypersusceptible people. If any susceptibility factor greater than 1 is applied, the short-term practical effect will be to increase all risk assessments for individual risk by the same factor, except for chemical-specific risk estimates where there is evidence that the variation in human susceptibility is larger or smaller for that chemical than for other substances.
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From page 210... ...
at high exposures are likely to be appropriate for the median or for the average human, and to explore what response is warranted for the estimation and communication of population risk if the median and average are believed to differ significantly. As an initial position, EPA might assume that animal tests and epidemiological studies in fact lead to risk estimates for the median of the exposed group.
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From page 211... ...
does EPA have any information on the presumed average and range of the parameters in the human population. It is perhaps noteworthy that in the one major instance in which EPA has revised a unit risk factor for a hazardous air pollutant on the
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From page 212... ...
Each of EPA's reports of a risk assessment should state its particular assumptions about human behavior and biology and what these do and do not account for. For example, a poor risk characterization for a hazardous air pollutant might say "The risk number R is a plausible upper bound." A better characterization would say, "The risk number R applies to a person of reasonably high-end behavior living at the fenceline 8 hours a day for 35 years." EPA should, whenever possible, go further and state, for example, "The person we are modeling is assumed to be of average susceptibility, but eats F grams per day of food grown in his backyard; the latter assumption is quite conservative, compared with the average." Risk-communication and risk-management decisions are more difficult
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From page 213... ...
, the committee agrees that it is important to think about its potential magnitude and extent, to make it possible to assess whether existing procedures to estimate average risks and population incidence are biased or needlessly imprecise. In contrast with issues involving average risk and incidence, however, some members of the committee consider the distribution of individual susceptibilities and the uncertainty as to where each person falls in that distribution to be irrelevant if the variation is and will remain unidentifiable.
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From page 214... ...
214 SCIENCE AND JUDGMENT IN RISK ASSESSMENT ID a' 0 102 23 10~0 ~ of cr 0 10~c, ID 10-7 10~ . 7 MU B 1st 5 ah 99~ Percentile on Exposure (or Susceptibility Distribution)
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From page 215... ...
VARIABLITY Note: To translate from percentile-relative exposure to absolute exposure, you could add a second x-axis scale based on a figure as follows: c 1~~70 g 50 ° 30 ~ 10 ~ O ~O cog 215 ~0 tOO 15;0 200 Amount of bock Thus, combining figures l and 2 gives you the 2 x-axes: Rib Off Abse~hrb .(~ And) I, 1st , MU ROB Oh ~1 50 100 200 FIGURE 10-2 Continued
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From page 216... ...
In both cases, the expected value of individual risk is 10-5, and it can be argued that the distribution of risks is the same, in that without the prospect of identifiability no one actually faces a risk of 10-3, but just an equal chance of facing such a risk (Nichols and Zeckhauser, 1986~. Some of the members also argue that as we learn more about individual susceptibility, we will eventually reach a point where we will know that some individuals are at extremely high risk (i.e., carried to its extreme, an average individual risk of 10-6 may really represent cases where one person in each million is guaranteed to develop cancer while everyone else is immune)
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From page 217... ...
Exposure Historically, EPA has defined the maximally exposed individual (MEI) as the worst-case scenario a continuous 70-year exposure to the maximal estimated long-term average concentration of a hazardous air pollutant.
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From page 218... ...
Note that the distribution would correctly be used only for individual risk calculations, as total population risk is unaffected by the number of persons whose exposures sum to a given total value (if risk is linearly related to exposure rate)
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From page 219... ...
· EPA should adopt a default assumption for susceptibility before it begins to implement those decisions called for in the Clean Air Act that require the calculation of risks to individuals. EPA could choose to incorporate into its cancer risk estimates for individual risk a "default susceptibility factor" greater than the implicit factor of 1 that results from treating all humans as identical.
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From page 220... ...
· If there is reason to believe that risk of adverse biological effects per unit dose depends on age, EPA should present separate risk estimates for adults and children. When excess lifetime risk is the desired measure, EPA should compute an integrated lifetime risk, taking into account all relevant age-dependent variables.
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From page 221... ...
quantity. This report, unless stated otherwise, will use the terms interindividual variability, variability, and interindividual heterogeneity all to refer to individual-to-individual differences in quantities associated with predicted risk, such as in measures of or parameters used to model ambient concentration, uptake or exposure per unit ambient concentration, biologically effective dose per unit exposure, and increased risk per unit effective dose.
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From page 222... ...
Inclusion of a default factor of 10 could bring cancer risk assessment partway into line with the prevailing practice in noncancer risk assessment, wherein one of the factors of 10 that are often added is meant to account for person-to-person variations in sensitivity. However, if EPA decides to use a factor of 10, it should emphasize that this is a default procedure that tries to account for some of the interindividual variation in dose-response relationships, but that in specific cases may be too high or too low to provide the optimum degree of "protection" (or to reduce risks to "acceptable" levels)
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From page 223... ...
VARIABILITY 223 8. "Currently" is an important qualifier given the rapid increases in our understanding of the molecular mechanisms of carcinogenesis.
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