Estimating the Public Health Benefits of Proposed Air Pollution Regulations (2002) / Chapter Skim
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4 Exposure and Response
4 Exposure and Response
Pages 75-125
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From page 75... ...
. EXPOSURE ASSESSMENT Estimating changes in population exposures to air pollutants is an essential component of EPA's benefits analyses, providing the link between anticipated emissions changes and resulting changes in health outcomes.
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From page 76... ...
As in all other stages ofthe benefits analysis, the assumptions and methods used in the exposure assessment should be well justified and clearly described, with careful attention paid to assessing and communicating key sources of uncertainty. EPA's exposure assessment methods have evolved considerably over time, as is evident in the health benefits analyses reviewed by the committee.
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From page 77... ...
Two classes of study designs have been used to assess mortality effects: time-series and prospective cohort studies (Kinney 1 9994. The timeseries studies examine day-to-day associations between citywide mean daily outdoor PM concentrations and citywide daily death counts.
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attempt to Incorporate this source of uncertainty in an overall uncertainty analysis. Another important characteristic of the exposure assessments in the epidemiological studies that evaluate PM mortality is their dependence on relatively simple measures of airborne PM, notably PM~o (moss lime-series studies)
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From page 79... ...
Over time, such information would also help to make effect coefficients derived from epidemiological studies more specific to actual exposures. .¢ When effect coefficients from epidemiological studies are used to derive benefits estimates, they should be applied at the same spatial scales used in the original studies to avoid biased benefits estimates.
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From page 80... ...
These uncertainties include the assumption that ambient concentrations consistently represent population exposures across locations and at future times, the assumption that sources affect population exposures in the same way that they affect modeled ambient concentrations, and the availability of health information only for aggregate PM measures, such as PM~o. Other important uncertainties in exposure assessment for benefits analysis result from methods used to model air quality under alternative regulatory scenarios.
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From page 81... ...
Finer resolution should improve model results and allow more accurate determination of exposure changes, especially for sources, such as mobile sources, that exhibit strong spatial gradients over fine spatial scales. However, the degree of improvement that can be achieved is limited by the resolution ofthe input data, such as the emissions inventory data.
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The latter is currently the more dominant factor. Thus, the credibility ofthe model results is determined by the modeling process.
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Although these uncertainties are poorly characterized, they may be decreasing with time. The models that have been used in past benefits analyses noted above are subj ect to many uncertainties, the older ones more so than the newer ones.
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From page 84... ...
The temporal resolution of the model outputs in days or weeks is well-suited for modeling of episodic excursions in the standards implementation context, which is the purpose for development of most models, but relatively less useful forbenefits analysis, for which longer exposure records would result in more reliable health benefits estimates. For the HD engine and diesel-fuel rule, full benefits analyses were conducted only for the year 2030, although exposure modeling results were also given for two intermediate time periods (2007 and 2020~.
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From page 85... ...
were considered by EPA for its benefits analyses (see Tables 2-1 and 2-5~. However, many health outcomes were not quantified (EPA 1999, 2000; see Table 7-1 )
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From page 86... ...
Although misclassification may be a problem for epidemiological studies, it is less important for health benefits analyses, because the available estimates for valuation of mortality are relatively similar to those for specific causes of mortality, such as cardiovascular and chronic respiratory disease, considered in health benefits analyses for criteria air pollutants. This situation may change over time with the development of disease-specific cost estimates.
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From page 87... ...
Furthermore, they might overlap with clinical outcomes that have been quantified, and including them .¢ would result in double-counting in the total benefits estimate. For example, quantification of changes in lung function may be possible because several cohort studies are available that show a relationship between reduced lung function and mortality.
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From page 88... ...
EPA has recognized that studies of hospital admissions often use different groupings of ICD codes, which can cause overlap and double-counting. In the United States, most evidence for the fourth category relates to admissions for individuals aged 65 or more, because the most accessible data for epidemiological studies are from Medicare.
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From page 89... ...
Nevertheless, averting behaviors may represent a substantial cost to society and should be acknowledged as being unmeasured in benefits analyses. Any health benefits analysis presupposes that the concentration-response function can be applied to a population or to subgroups within the population.
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. The analyses reviewed by the committee relied on observational epidemiological studies.
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From page 91... ...
There are too few cohort studies to satisfy the consideration of consistency, and there is less supporting experimental evidence. However, there is some specificity for cardiopulmonary outcomes and lung cancer, considerable coherence ofthe study results, and an analogy with similar exposures (environmental tobacco smoke)
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From page 92... ...
Another factor to consider is the possibility that the given association can be explained by confounding. For example, in cohort studies, it is important to control for such factors as education, smoking, environmental tobacco smoke, occupation, and region.
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From page 93... ...
The following sections describe the strengths and weaknesses of using animal studies, human experimental studies, andepidemiological studies as sources for concentration-response functions. Animal Studies As Sources of Response Functions Animal toxicological studies typically involve controlled experiments of animals in chambers exposed to specified doses of pollutants.
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From page 94... ...
In summary, toxicological animal studies may be useful in determining whether a given pollutant is toxic and in helping to elucidate potential biological mechanisms end pathways. However, application of results from animal studies to estimate the health benefits of ambient air pollution control requires several extrapolations, each of which involves considerable uncertainty.
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The epidemiological studies described in the next section allow one to estimate concentration-response functions for the general population exposed to ambient air pollutant concentrations. Epidemiological Studies As Sources of Concentration-Response Functions Observational epidemiological studies involve the study of humans in
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Therefore, using concentration-response functions from epidemiological studies for benefits analyses will require extrapolation from the study populations to the target populations in the benefits analysis. The extrapolation of results from epidemiological studies assumes a fairly similar spatial relationship between pollution monitors and population.
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This uncertainty may diminish for gaseous pollutants, such as ozone. Sources of Concentration-Response Functions For EPA's Analyses For the health benefits analyses reviewed by the committee, EPA used concentration-response functions from epidemiological studies.
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2000~. The committee believes that generally the most appropriate approach is to calculate a weighted mean estimate rather than choose one study from a set of studies conducted on the same health outcome to derive the concentration-response function.
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Including a highly correlated copollutant increases the standard error of the estimate and the associated confidence interval and often results in highly unstable effect estimates for the pollutant of interest. In addition, the relative effect estimates ofthe two pollutants may be influenced by the relative magnitudes oftheir exposure measurement errors.
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.` EPA,s Selection of Epidemiological Studies Overall, the committee found that the studies selected by EPA for use in its benefits analysis were generally reasonable choices. However, the criteria and process by which EPA reached its decisions are not clearly articulated in many cases.
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EPA may want to consider derivation of a weighted mean estimate from the cohort studies following review of the entire database.
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Data on morbidity outcomes is less comprehensive and must be improved, especially if the value assigned to mortality decreases and morbidity outcomes play a more dominant role in the benefits analyses. Short-term exposures typically have been studied using time-series methods that test the hypothesis that daily changes in air pollution are followed within days or weeks by changes in mortality or morbidity among the exposed population in a specific area.
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From page 103... ...
However, because exposure history is not a part of the time-series study design, the time-series studies do not distinguish between cases where cumulated exposure has had an impact on terminal susceptibility and cases where past air pollution exposure is irrelevant.
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From page 104... ...
The best approach would be to assess the effect of various degrees of exposure on life expectancy using a randomized intervention study, but this study design is not feasible in the field of ambient air pollution research. Studies of longterm exposure have involved both cross-sectional and prospective cohort study designs.
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From page 105... ...
The cohort studies are not restricted to a narrow time period between exposure and health effect but assume that some cumulated exposure experience might result in shorter life expectancy due to, for example, illnesses, such as chronic bronchitis or lung cancer (Abbey et al. 1995; Nyberg et al.
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. Prospective cohort studies could include the cases of mortality due to short-term exposure, as well as cases resulting from long-term exposure.
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From page 107... ...
Despite some differences in the central estimates of concentrationresponse coefficients, the cohort studies from the United States suggest important associations between long-term exposure and time to death and appear to be the most appropriate study design to assess the impacts of air pollution on health. One finding that supports using the cohort study design over the time-series study design is the reported association between lung cancer and air pollution exposure (Nyberg et al.
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From page 108... ...
Theoretically, a cohort study measures the total life-years lost due to long-term exposure to air pollution. However, the available cohort studies use crude measures of cumulative exposure, such as the annual mean value, and the effects of short-term exposures are unlikely to be fully captured in the cohort studies.
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From page 109... ...
For this reason, the impact of the existence of a threshold may be considerable. In epidemiological studies, air pollution concentrations are usually measured and modeled as continuous variables.
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From page 110... ...
A review of the time-series and cohort studies may lead to the conclusion that although a threshold is not apparent at commonly observed concentrations, one may exist at lower levels. An important point to acknowledge regarding thresholds is that for health benefits analysis a key threshold is the population threshold (the lowest ofthe individual thresholds)
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From page 111... ...
Differential health effects may occur because the effects of the regulation result in different reductions in population exposures or because subgroups within the population vary in response to a given exposure reduction. The latter effect can occur because baseline rates of health outcomes may vary across subgroups or because the concentration-response function may differ across
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From page 112... ...
As indicated previously, when estimating health benefits associated with finely mapped exposures, concentration-response functions should be derived from epidemiological studies conducted at similar geographical exposure scales. Given the assumption that the relative risk of a health outcome is proportional to the level of exposure, the predicted number of cases for a specific health outcome will also be proportional to the baseline rate for that health outcome.
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From page 113... ...
If the subgroup findings are driven by exposure measurement issues, a subgroup benefits analysis may be less appropriate than simply applying the aggregate total risk function for the full population. EPA's Analysis of Subgroups EPA analyzed subgroup-specif~c effects only to the extent that benefits were assessed for the subgroups considered in the original studies (for example, restriction by age for mortality [more than 30 years]
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From page 114... ...
For example, certain health benefits resulting from a change in air quality may occur only after several years. Although it appears that mortality following short-term exposure to PM occurs within a relatively short time, little is known about the temporal relationship between longer-term exposure and mortality as demonstrated in the prospective cohort studies.
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From page 115... ...
These uncertainties include the assumptions that ambient pollutant concentrations consistently represent population exposures across locations and at future times, that sources affect actual exposures in the same way that they affect ambient concentrations, and that all particle types have a constant potency. · The appropriate selection end definition of adverse health outcomes is integral to any assessment of health benefits.
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· For the analysis of mortality, EPA used cohort studies to derive benefits estimates in the analyses reviewed by the committee. The committee supports this approach.
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· EPA provided little information in the benefits analyses reviewed by the committee on causal association between particular types of air pollution and adverse health outcomes. EPA should summarize the evidence for causality to justify the inclusion or exclusion of the health outcomes and to assess the uncertainty associated with the assumption of causality.
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From page 118... ...
1997. Lung function and long-term exposure to air pollutants in Switzerland.
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From page 119... ...
1998. PM2.5 and mortality in long-term prospective cohort studies: Cause-effect or statistical associations?
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2000. Reanalysis of the Harvard Six Cities Study and the American Cancer Society Study of Particulate Air Pollution and
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2001b. RE: Assessment of death attributable to air pollution: Should we use risk estimates based on time series or on cohort studies?
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1998. Assessing the health benefits of reducing particulate matter air pollution in the United States.
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Part 2: Morbidity and Mortality from Air Pollution in the United States, Research Report 94. Health Effects Institute, Cambridge, MA.
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1998. Alternative hypotheses linking outdoor particulate matter with daily morbidity and mortality.
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In Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance, R Brookmeyer and D
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