U-.ited States Office o* An Qaalitv EPA-450/5-85-005d
Environmental Protection Planning an: Gianaards August 1985
Agency Rese&rcn Triangle Par\ NC 27711
A:r
Executive Summary
Ambient Ozone And
Human Health:
An Epidemioiogical
Analysis
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AMBIENT OZONE AND HUMAN HEALTH:
AN EPIDEMTOLOGICAL ANALYSIS
aul R. Purtnev and John Mullahv
Resources for ths Future
1616 P Street, N.W.
Washington, D.C. 20036
June
Submitted to the Economic Analysis Branch, Office of Air Quality Planning
and Standards, Envirorir/iental Protection Agency, Research Triangle Park,
North Carolina 27711, under contract number 68-02-3583.
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DISCLAIMER
This report has been reviewed by the Office of Air Quality Planning
and Standards, U. S. Environmental Protection Agency, and approved for
publication as received from Resources for the Future. The analysis and
conclusions presented in this report are those of the authors and should
not be interpreted as necessarily reflecting the official policies of
the U. S. Environmental Protection Agency.
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EXECUTIVE SUMMARY
In June of 1982 Resources for the Future (RFF) began a project for the
Economic Analysis Branch of the Environmental Protection Agency's Office of
Mr Quality Planning and Standards (OAQPS). The purpose of that project
was to provide information to OAQPS on the human health benefits that might
be associated with possible alternative National Ambient Air Quality
Standards for ozone, one of six so-called "criteria" air pollutants. In
September of 1983, RFF completed work on a two-volume Draft Final Report on
that project, "Ambient Ozone and Human Health: An Epidemiological
Analysis." Since that time RFF has conducted additional analysis in
response to comments, criticisms, and suggestions arising from the draft
report. Many of these comments were offered at a Public Peer Review
Meeting held in Raleigh, N.C. on April 3, 1984. This Executive Summary
briefly reviews the methodology and conclusions in Volumes I and II, the
original draft report, as well as those in the recently completed Volume
III, the sequel to RFF's initial work.
Volume I
Volume I of the 1983 Draft Final Report presents the data, methodology
and findings of RFF's original epidemiological analysis. Chapter 2
discusses in great detail the health and socioeconoraic data used in the
study, the air pollution measurements used to link exposure to health
status, and the meteorological and other data that were also used. Chapter
3 discusses the methodology used to explore possible links between ozone
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and other pollutants on the one hand and acute and chromic Illness on the
other. Neither chapter is reviewed in detail in this Executive Summary.
Rather, we prefer to review here the findings of the "Results" chapter,
Chapter U. However, a brief review of chapters 2 and 3 may prove useful.
The health and socioeconomic data upon which the analysis in Volume I
is based come from the 1979 Health Interview Survey (HIS) of more than
110,000 adults and children drawn randomly from the United States (Volume
I, pp. 2-1 through 2-21). For each individual included in the HIS,
information is elicited on personal characteristics (age, race, sex, etc.),
occupational or educational status, and on any of several types of acute
health episodes during the two weeks immediately prior to the week of the
interview. Also included is information on the presence or absence, as
well as the severity, of any chronic illnesses from which the respondents
may suffer. For all acute and chronic illnesses, coding in the HIS is
according to the standard International Classification of Diseases. Thus,
one can identify from the HIS, for instance, the number of "bed disability"
days a respondent suffered on account of respiratory disease during a
two-week period in 1979. Similarly, one can identify all individuals
suffering from asthma, emphysema or other chronic respiratory disease.
Finally, the 1979 HIS contained two very useful supplements. The first was
a detailed lifetime smoking history for 26,000 of the 78,000 adults
interviewed in the HIS. The second was a residential history, again
administered to one-third of the adult respondents.
The air pollution data used in the RFF Draft Final Report, and in the
more recent Volume III analyses, all come from EPA's SAROAD system (Volume
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3
I, pp. 2-22 through 2-46). Hourly data were used to meaaure ozone, carbon
monoxide, and nitrogen dioxide concentrations. Total suspended
particulates and sulfates were measured on a 24-hour basis with the
readings being taken every six days generally. Thus, exposure to the
latter two pollutants may be measured less accurately than for the former.
Before matching these data to individuals (through a process described on
p. 2-46), all data were subjected to a variety of tests to eliminate
potentially incorrect values or outliers resulting from coding errors.
Also described in Chapter 2 are the procedures used to average some of the
air pollution data over the two-week recall period used in the acute
epidemiological analysis as well as over a six-year period used to
facilitate RFF's chronic epidemiological analysis. The data on
temperature, humidity, precipitation, windspeed and other weather
conditions come from NOAA's meteorological monitoring stations around the
U.S.
Finally, Chapter 2 discusses the sources of data on pollen
concentrations, the use of gas stoves in kitchen cooking, the average
amount of annual paid sick leave permitted workers, and the availability of
medical care by geographic area in the United States.
The measures of health status used in the Volume I analyses are, for
acute illness, the number of restricted activity days, work loss (or school
loss) days, and bed disability days during each individual's two-week
recall period. The category "restricted activity day" is an inclusive one
that encompasses both work (or school) loss and bed disability days as well
as days on which respondents had to curtail their normal activities to some
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extent short of missing work (or school) or bed confine-ent. These latter
impairments we referred to in Volume I as "minor restricted activity days."
Each type of acute illness was analyzed separately. Also separate analyses
were conducted using acute episodes due to all causes, and then episodes
limited to respiratory illness alone. In addition, logistic regressions
were performed in which the dependent variable indicated whether or not the
respondent had at least one day of illness during the two-week period.
Logistic regression was used exclusively in the analysis of respiratory and
other types of chronic illness. In all cases, children and adolescents
(those < seventeen years of age) were analyzed separately from adults.
Chapter 4 of Volume I, wherein are reported RFF's empirical findings,
represents the heart of the Draft Final Report, The major part of that
chapter is devoted to the analysis of acute illness, particularly
respiratory disease, and its possible link to short-term exposure to ozone
and other air pollutants. (Throughout the analysis of acute illness,
exposure to ozone is characterized by the average over the fourteen-day
recall period of the daily maximum one-hour reading at the monitor closest
to the respondent's residence; no individuals are included in the estimate
sample if they live more than twenty miles from the nearest air pollution
monitor.) More attention is devoted to dose-response estimation among
adults than among children.
This emphasis on acute illness in adults as related to ozone follows
from a strategy adopted throughout Volume I: use sensitivity analysis
primarily to test the robustness of any positive and significant
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associations discovered between ozone and illness. Sine; such associations
arose almost exclusively among adults and when examining acute illness, the
report reflects this emphasis. This approach reflects the fact that both
time and resources were finite in the original analysis, as they are in all
such undertakings.
Generally speaking, and this is an important qualification, the
analysis of acute illness among adults supports the following conclusion:
there appears to be no consistent association between average daily maximum
ozone concentrations and either work loss days or bed disability days, the
two more severe types of acute impairments analyzed in Volume I; however,
it was frequently the case that ozone was positively and significantly
associated with "minor" restrictions in activity, i.e., those that did not
necessitate work loss or bed confinement. While there were few or no
exceptions to the former conclusion, there were a number of exceptions to
the latter. Nevertheless, when the analysis concentrated on respiratory
disease in particular—where air-pollution health effects are most likely
to occur—ozone was regularly found to be related in a positive and
significant way to either the number of restricted activity days or the
likelihood of having at least one during the two-week recall period (see
Volume I, Tables 4-7, 4-8 and 4-10). For no other air pollutants was such
a_ regular association found.
Among the sensitivity analyses conducted to test this conclusion were
the following: (i) varying combinations of air pollutants other than ozone
were included in the estimating equation; (ii) the square of ozone was
introduced to examine possible non-linearities; (iii) logistic regressions
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were run in place of ordinary least squares; (iv) tighte- requirements were
imposed on the availability of ozone data (a greater percentage of the
maximum number of hourly readings were required); (v) the analysis was
restricted to respondents interviewed during summer months; (vi) pollen
concentrations were introduced as an additional explanatory variable; (vii)
the analysis was restricted to those suffering from chronic illness; (viii)
the twenty-mile distance cut-off was tightened to ten and then five miles;
(ix) lagged values for ozone (from a previous two-week period) were used to
proxy exposure; (x) possible synergistic effects between ozone and other
air pollutants were examined; and (xi) separate regressions were run for a
set of "self-respondents," i.e., those who answered the HIS for themselves.
As suggested above, in some of these sensitivity analyses the ozone
variable was not positively and significantly associated with acute
respiratory disease (or disease due to all causes). More often than not,
however, it was.
The findings in the Draft Final Report regarding acute illness among
children can be summarized more readily. Virtually no positive and
significant associations were found between ozone and any of the types of
acute impairments that were considered. This was the case when the focus
was on all types of illness as well as when the analysis focused
exclusively on acute respiratory illness. Ozone was associated with school
loss at the 10 percent confidence level in one or two models, it should be
added, but never at the 5 percent level used as the "cutoff" in Volume I of
the report. The only association significant at the 5 percent level
occurred in one model exploring ozone and bed disability days due to
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7
respiratory disease. Of the other air pollutants include! in the analysis,
nitrogen dioxide was found to be positively and significantly related to
school loss days among children in the analysis of illness due to all
causes. While its coefficient was positive in the analysis of minor
restrictions in activity and bed disability, nitrogen dioxide was not
significantly associated with these forms of acute illness. The one caveat
that should be issued here is this: very few sensitivity analyses were
conducted using the children's data set because of the absence of initial
findings concerning ozone pollution/acute illness associations. More
careful analysis of possible air pollution health effects among children
should be conducted.
Volume I of the Draft Final Report also devotes considerable attention
to the possible role of ozone and other air pollutants in chronic illness.
In this analysis, which begins on p. 4-50, the focus shifts away from the
two-week recall period and the number of days of restricted activity
experienced by each respondent during that period. Instead, the dependent
variable in the chronic analysis is whether or not the respondent has
chronic respiratory (or, in some cases, cardiovascular or other) disease.
Accordingly, the measurement of ozone and the other air pollutants is no
longer specific to the two-week recall period, as it was in the analysis of
acute illness. Rather, ozone and other air pollution concentrations are
averaged over longer periods of time.
Generally, the longer averaging time is one year. However, a
multi-year air pollution data set was created for this project. Thus, in
some of the models fit in Chapter 4, individuals are matched to air
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pollution concentrations over the six year period V.- —79. The logic
behind this is straightforward. Chronic illness, if related to air
pollution at all, is likely to result from prolonged exposure over many
years. Frequently, a single year's data are used to proxy exposure over a
much longer period of time. However, where a longer-term air pollution
data set could be assembled, as it was in this study, it is preferable to
the use of one year's data. As on the analysis of acute illness, the air
pollution data matched to an individual came from the monitor nearest his
home, so long as minimum requirements regarding data completeness were
satisfied.
In general, the analysis of chronic respiratory and other diseases in
adults revealed no pattern of positive and statistically significant
associations between illness and ozone or most of the other air pollutants.
There were occasional exceptions, some of which are discussed below, but
the results contrast with the findings about ozone and minor restrictions
in activity due to respiratory disease.
In the initial analysis (see Table 4-13 in Volume I), all pollutants
were measured using a single year's data, 1979> to proxy long-term
exposure. No significant associations were observed for any of the air
pollutants. When the multi-year data set was brought into play, the
results changed somewhat (see Table U-14). In some models, the coefficient
on ozone was positive and significant at the 10 percent level (see
equation (9)» for example). In addition sulfur dioxide concentrations were
positively and significantly related to the probability of chronic
respiratory disease (CRD). This latter finding was consistent throughout
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much of the analysis using the multi-year data set. Among the adults
analyzed in the report, this was the one strong Association to occur
frequently. The lack of any significant findings with respect to ozone
persisted across a number of sensitivity tests.
There was one exception to the negative findings regarding ozone and
CRD. This occurred when the adult sample was divided into three groups
consisting of those who had never smoked, those who were ex-smokers, and
those who were current smokers. Among the never-smokers, ozone (measured
by the multi-year average) was positively and significantly associated with
CRD (Table 4-15, equations (23) and (26)). Among the never and former
smokers, sulfur dioxide was positively and significantly associated with
CRD.
In the analysis of CHD among children, there was but one positive and
significant association—that concerned nitrogen dioxide in one model
(equation (32), Table M-16). As in the case of acute illness among
children, very little sensitivity analysis was conducted because of the
largely negative findings.
Brief attention was devoted in Volume I to chronic cardiovascular
disease (CCD) (see Table U-17). Explorations here found multi-year average
ozone concentrations positively but never significantly associated with
CCD. Nor were any such associations identified for other of tie air
pollutants considered. Confidence in these findings was bolstered by the
fact that other risk factors identified in previous studies of CCD all had
the expected sign and were highly significant in the analysis. These
included age, race, smoking habits, weight, and education. In addition to
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CCD, a variety of chronic diseases, neoplastic and other rise, were examined
for possible links to ozone and other air pollutants. No such associations
were found. Once again, a caveat to this analysis is that only the most
superficial tests were conducted. It is always possible that additional
analyses might produce different results.
Volume II
Volume II of the Draft Final Report requires virtually no summary.
Its primary purpose is to present the Health Interview Survey for 1979 and
the two supplements, one on smoking and the other on residential mobility
(which is actually pp. 110-111) of the HIS itself). In addition, Appendix
B of Volume II contains the data documentation and cross-referencing.
Appendix C (actually the third part of Volume II) does present research
output from the RFF ozone project. However, this output is theoretical
rather than empirical.
Specifically, Appendix C is a paper deriving the conceptually correct
measure of the benefits of a pollution control program in a simple model of
consumer behavior. In the model, pollution not only affects welfare by
leading to illness but also enters individuals' utility functions directly.
In addition, in the model individuals can protect themselves against
illness by making "defensive" expenditures. (these might be purchases of
air conditioners or filters, water purifiers, preventive health measures,
and so on.) It was the purpose of this work to see how the presence of
such defensive or averting expenditures might affect the valuation of
health benefits, and how the correct valuation compared to the
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out-of-pocket and opportunity costs associated with pollution-induced
illness.
The results can be summarized as follows. First, the measure of an
individual's willingness-to-pay for a pollution reduction contains only
derivatives of the dose-response function, specifically those relating to
the effect of pollution on health and defensive expenditures on health.
Next, the conceptually correct measure will in general not only exceed the
change in out-of-pocket and opportunity costs of illness but also the sum
of these costs plus the change in averting or defensive expenditures.
Finally, this conclusion holds for several different variations of the
basic model in which workers are given paid sick leave, sickness affects
the wage rate, and other changes as well.
Volume III
The third volume of work completed by RFF for OAQPS is more recent
than the first two. It represents work undertaken since the April 1984
Public Peer Review Meeting and consists largely of additional analysis done
in response to comments received at that meeting or elsewhere.
Chapter 2 is methodological. It discusses in some detail the kinds of
problems that can arise when ordinary least squares techniques are used to
estimate the likely effects of air pollution on health outcomes. On
account of these problems—the most important of which is the frequent
truncation or censoring of the range of health outcomes—alternative
estimating techniques are reviewed. These include Tobit and Cragg-class
models, truncated normal estimation, the sample selection model, Poisson
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and geometrically distributed measures of health outcomes, and multinomial
techniques.
The third chapter of Volume III is quite brief and is designed to
answer a specific and important question: How would the analysis in Volume
I have changed if the air pollution readings assigned to individuals had
come not just from the single nearest monitor but from all monitors within
some specified distance of the individuals' homes?
The answer suggested by the analysis in Chapter 3 is "Not very much at
all." This conclusion follows from the simple correlation coefficients
between the nearest monitor readings and the readings averaged over all
monitors within ten and then twehty miles of the respondents' homes. For
ozone the correlation coefficients are 0.97 and 0.93 for the ten and twenty
mile averages, respectively. Thus, substituting either of the latter two
for the nearest monitor readings would make virtually no difference in the
results. The smallest of all the correlation coefficients thus calculated
for all pollutants was 0.82.
Chapter 4 presents the results of some substantial reanalysis of the
Volume I findings concerning ozone and acute respiratory disease. It
differs from (and improves upon) the original work in several important
respects. First, Poisson regression is used in place of ordinary least
squares. For reasons discussed in Chapter 2 of Volume III, this is a more
appropriate way to model acute health outcomes. Second, no individual was
included in the analysis if the nearest air pollution monitor was more than
ten miles from his home, as opposed to twenty in the original analysis.
Third, the analysis of possible non-linearities is more sophisticated in
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the later analysis. Finally, air pollution was measured not only by the
reading at the nearest monitor during the two-week recall period but also
by the average reading during that period of all monitors within ten and
also twenty miles. Annual average readings were also employed in several
of the models estimated.
The analysis in Chapter 4 supports the findings in Volume I.
Specifically, ozone (however measured) is found to be positively and
significantly associated with the number of restricted activity days due to
respiratory disease during the two-week recall period. No effect is found
for sulfates, the other air pollutant included in the Chapter 4 analysis.
Of the other independent variables, race, income, the presence of a chronic
illness, and temperature were also found to be associated in a
statistically significant way with acute respiratory disease.
In other findings in Chapter 4, the possibility of interactive effects
between ozone and sulfates and ozone and temperature are rejected. In
addition, no evidence is uncovered supporting the idea of a "threshold"
below which ozone concentrations are harmless. However, the analysis does
support the finding that the dose-response relationship between ozone and
acute respiratory disease is non-linear. That finding (see equation 4.5 in
Table 4-4) suggests that the square root of the average daily maximum ozone
concentration at the nearest monitor is a potentially important and
significant determinant of acute respiratory disease.
Chapter 5 summarizes recent research on the construction of proxy
measures for lifetime smoking profiles. The smoking controls used in both
the statistical analyses in Volume I and in Chapter 4 of this volume were
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typically either the current rate of daily cigarette ccisumption or dummy
variables indicating whether the individual was a current, former, or never
smoker. As noted at various points in the analysis, such variables are
acceptable controls for assessing the possible linkages between current
cigarette consumption and respiratory illness. However, because the
relationship between cigarette smoking and respiratory illness is also
thought to have lagged or cumulative dimensions, separate explanatory
variables are required to effect controls for such relationships.
Given this requirement, and since no single value given in the data
provides such information, we explored the detailed data available in the
HIS Smoking Supplement in order to assess whether plausible proxies for
lifetime cigarette consumption could be created. Using information on peak
and current rates of consumption, age, age started smoking, and duration
since quits, it was ascertained that various plausible controls for
lifetime smoking could indeed be obtained from the HIS data. It turns out
that the measures are created in a manner analogous to how capital stock
values are obtained from investment and depreciation profiles in applied
microeconomic research. Chapter 5 presents in considerable detail the
procedures used for creating these lifetime cigarette consumption profiles.
Drawing on the results of Chapter 5, Chapter 6 proceeds in several
directions to a more sophisticated analysis of the relationships between
ambient air pollution and respiratory illness. Not only are the lifetime
smoking profiles discussed in Chapter 5 used to control for longer-term or
cumulative relationships between cigarette smoking and respiratory illness,
but a new, and we believe particularly interesting, measure of respiratory
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illness is used. That is, we consider in Chapter 6 the Distinction between
minor limitations in activity due to respiratory illness, i.e., those where
the individual is not confined to bed, and major restrictions in activity
due to respiratory illness, i.e., those where some bed confinement occurs.
Moreover, we also consider in Chapter 6 the distinction used by the
National Center for Health Statistics between inherently acute and
inherently chronic respiratory illness.
To assess econometrically the relationships between the explanatory
covariates and the new measures of respiratory illness, we use a
multinomial logit estimator of the determinants of the various respiratory
illness outcome probabilities. Like Chapter 4, it is found that nonlinear
transformations of the ozone variable, as well as of the smoking controls,
give superior results. Ozone is found to be positively related to the
probability of all the respiratory illness outcomes, and the relationship
is statistically significant for the minor or non-bedridden illnesses. The
results also demonstrate that the additional effort involved in
constructing the lifetime smoking profiles was worthwhile: in many of the
specifications of the respiratory illness measures, both the current rate
of consumption and the cumulative lifetime consumption were statistically
important determinants of the probability of respiratory illness. In
addition, the last section of Chapter 6 produces some calculations of the
relative risks of various respiratory illness outcomes attributable to
plausible hypothetical changes in ambient air pollution concentrations and
current and lifetime cigarette consumption.
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Chronic rather than acute illness is the focus of vie seventh chapter
of Volume III. In particular, the focus there is on the possible role of
ozone, sulfates, and total suspended particulate matter in chronic
respiratory disease (CRD). The analysis in Chapter 7 improves upon the
analysis of CRD in Volume I in several ways. First, the sample of
individuals used was restricted to respondents who has been living in their
present location for ten years at the time of the 1979 HIS (compared with
five years in the original work). Also, the more sophisticated measures of
lifetime smoking described in Chapter 6 were used. Third, the sample of
respondents was divided into two groups: one group was comprised of
individuals who received the special "probe" questions in the 1979 HIS
pertaining to respiratory disease; the other group consisted of individuals
who received one of the five other disease probes. The sample was divided
in this way because of evidence of differential response rates.
The results of this reanalysis of air pollution and CRD are ambiguous,
in much the same way as were the findings in Volume I. For instance, when
ozone was measured by the 1979 annual average daily maximum at the nearest
monitor, it was positively and significantly related to CRD in the "probe"
group. When averaged over more than one monitor in an area, the
coefficient on ozone declined somewhat in significance, and it was by any
reasonable standard indistinguishable from zero where the multiyear ozone
data were used. In regressions using respondents from the probe group,
neither sulfates nor total suspended particulates were significantly
associated with CRD, nor were any of the other independent
variables—including the smoking measures. In the regressions run using
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the non-probe group, ozone was never significantly associated with CRD.
However, when the multi-year averaged air pollution data were used,
particulates were positively and significantly associated with CRD. So,
too, were both current and prior smoking habits, as well as income.
On the whole, then, reflecting on both the original work and the
recent reanalysis, no consistent relationship between ozone (or any other
air pollutants) and CRD has emerged in the RFF work. It is an area of
continuing investigation, however.
Chapter 8 presents the results of a variety of sensitivity analyses of
the Volume I research. That is, the results discussed in this chapter
summarize analyses of the sensitivity of the Volume I empirical results to
different assumptions about various data and model specification issues.
Specifically, Chapter 8 treats the following topics. Discussed first is
the question of proper specification of the precipitation measures. Our
analysis suggests that the measures used in the models in both Volume T and
in several of the chapters of Volume III are appropriate. Second, we
assess the effects of sample size and selection on a set of the estimates
presented in Volume I. It is found that the implications of varying sample
size are largely manifested in the efficiency properties of the parameter
estimates rather than in inferences about the central tendencies of the
estimates themselves.
The third section of Chapter 8 presents a reestimation using Poisson
regression of some of the models estimated by ordinary least squares in
Volume I. The upshot of this exercise is that the alternative Poisson
estimation techniques appear to be superior on statistical grounds.
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However, the inferences about the relationships between ozone and
respiratory health drawn from the corresponding models in Volume I are
largely corroborated by the reanalysis. The analysis discussed in Section
8.U concerns the question of structural aggregation. Specifically, this
section examines whether structures of the relationships between
explanatory variables and respiratory health outcomes differ for
individuals with different cigarette smoking behaviors or with different
chronic illness statuses. The results generally suggest that the
hypothesis of structural homogeneity across the various smoking status or
chronic illness categories be rejected.
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Executive Summary Ambient Ozone and Human Health:
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the public, with address and price.
19. & 20. SECURITY CLASSIFICATION
DO NOT submit classified reports to the National Technical Information service
21. NUMBER OF PAGES
Insert the total number of pages, including this one and unnumbered pages, but exclude distribution list, if any
22. PRICE
Insert the price set b> the National Technical Information Service or the Government Printing Office, if known
EPA Fo—i 2220-1 (Rev. 4-77) (Reverse)
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