This manuscript was prepared as part of the Environ-mental
Epidemiology Planning Project of the Health Effects Institute, September
1990 - September 1992.
This paper was prepared under a contract from the Health
Effects Institute. The National Institute of Environmental Health Sciences
grant ES-00002 provided additional support. The author is grateful to Jonathan
Samet and William Lambert for their comments and to Grace La for preparing
the manuscript.
Introduction
From its earlier roots, epidemiologists have recognized air pollution
as a potentially important determinant of increased morbidity and mortality.
In the classic analysis of the Bills of Mortality in 1662 (1), Graunt
attributed the high week-to-week variability in mortality to changes in
the "airs" of London. Modern air pollution epidemiologists have
attempted to attribute health effects to specific constituents of these
"airs." However, it has become clear that these airs are in fact
a complex mixture of contaminant gases and particles.
Methods for epidemiologic studies of the health effects of air pollution
have been reviewed comprehensively by the National Research Council Committee
on the Epidemiology of Air Pollutants (2). This paper builds on that
state-of-the-art report, plus discussions by Samet and Lambert (3),
to consider epidemiologic study designs for assessing health effects of
complex air pollution mixtures.
Difficulties in Air Pollution Epidemiology
Epidemiologic studies of air pollution are particularly challenging.
Air pollution exposures are universal and, as Rose (4) has pointed
out:
the more widespread is a particular environmental hazard, the less it
explains the distribution of cases. The cause that is universally present
has no influence at all on the distribution of disease, and it may be quite
unfindable by the traditional methods of clinical impression and case-control
and cohort studies, for all of these depend on heterogeneity of exposure.
The challenge, therefore, is to develop study designs that provide contrasting
exposures in natural settings. Given that environmental exposures are generally
to multiple pollutants, studies that differentiate response to the air pollution
mixture will require careful and innovative designs.
A second problem is that while exposures are common, the risks tend to
be low. Environmental controls that have been put in place in the United
States have reduced exposures generally to levels below the National Ambient
Air Quality Standards. The standards, established by the EPA, and based
on the best available scientific data, were set to prevent any adverse health
effects, even among the most sensitive members of the general population.
Thus, expected health effects of air pollution at concentrations currently
observed in the United States should be expected to be weak, that is, with
relative risks less than 2 and often less than 1.5 for typical exposures.
At the present time, it is not sufficient to demonstrate that a certain
air pollutant, or mix of air pollutants, is associated with an adverse health
effect. Adequate information is available to demonstrate adverse health
effects at high concentration. Regulators now require quantitative estimates
of the exposure-response associations at concentrations below the National
Ambient Air Quality Standards to evaluate adequacy of the standards and
for risk and cost-benefit analyses as required under the most recent amendments
to the Clean Air Act (5).
Misclassification of exposure is a particular problem in air pollution
studies. Personal exposures to air pollution may differ substantially from
ambient air data. Innovative methods have been developed for measuring personal
exposures, but these methods are labor intensive and often very intrusive
on the participants. Thus, the investigator should expect substantial random
misclassification of exposure in designing an epidemiologic study. This
means that statistical associations will be weakened and larger sample sizes
required. Particular attention should be given to the potential for information
bias associated with exposure misclassification.
Adverse health effects of environmental pollutants, and air pollution
in particular, are generally nonspecific. For example, the development of
chronic-obstructive pulmonary disease is a cumulative process in which air
pollution is only one of many factors that produce irreversible loss of
lung function. Likewise, reversible changes in lung function, as in asthma,
may be triggered by many environmental exposures, including allergens (e.g.,
house dust mites, pollens, mold spores, fungi, and animals), infections,
medication, exercise, heat, cold, and air pollution (SO2 and
O3). This implies that respiratory health end points are often
common in the study populations. However, this also implies that studies
to evaluate the health effects of air pollution must carefully consider
such covariates in the design.
Just as the cause of the respiratory health end points is likely to be
multifactorial, exposures to air pollution are, in general, multidimensional.
It is the purpose of this paper to address methods of designing and analyzing
epidemiologic data to evaluate the health effects of such complex air pollution
mixtures.
As an example, consider the association between environmental tobacco
smoke (ETS) and lung cancer. It is clear that there is a strong association
between active smoking and lung cancer. If these risks are extrapolated
down to the exposures expected for a never-smoker exposed to environmental
tobacco smoke (ETS), the estimated risk ratios would be of the order 1.4
for men and somewhat lower for women (6). Estimates combining results
from case-control and cohort studies of lung cancers among nonsmoking women
married to smokers in the United States (6) produce a summary relative-risk
estimate of 1.14. At such low relative risks, alternative environmental
causes, such as indoor radon, must be considered. Estimates from population-based
studies may be biased toward the null because exposure to ETS is so common
that it is impossible to identify a truly nonexposed control population.
Thus, risk estimates in ETS epidemiologic studies are based on comparisons
to controls with low, rather than no, exposure.
Respiratory Health Effects of Concern
For most air pollutants, indoor or outdoor, singly or in complex mixtures,
the respiratory system is the sole or predominant portal of entry into the
body and the principal locus of injury. The definition of what constitutes
an adverse health effect has been addressed by a committee of the American
Thoracic Society (7). Health effects generally are divided into acute
and chronic effects. Acute effects are characterized by sudden onset; are
usually short-lived, that is, lasting minutes to days; and may be reversible.
Chronic effects are characterized by conditions that persist over extended
periods of time, possibly years. Although there may be recovery from chronic
effects, they may be irreversible and may lead to early mortality.
Examples of acute respiratory effects of air pollution include triggering
or aggravation of asthmatic attacks, exacerbation of symptoms of chronic
obstructive disease, increased upper or lower respiratory infections, transient
changes in pulmonary function, increased respiratory symptom reporting,
increased respiratory hospital admissions or doctor visits, and increased
daily mortality.
Examples of chronic respiratory effects of air pollution include promotion
of the development of asthma, increase in nonspecific airway responsiveness,
reduced level of lung function, increased rate of lung-function decline,
decreased rate of lung growth, development of chronic-obstructive pulmonary
disease, increased reporting of persistent respiratory symptoms, lung cancer,
and increased mortality.
Epidemiologic Study Designs
Epidemiologic methods applied in air pollution research can be described
by a small number of study designs. Some study designs are not appropriate
or have not been applied to air pollution. Discussing these designs provides
a structure for evaluating the potential for investigating the health effects
of complex air pollution mixtures.
Cross-Sectional Studies
In cross-sectional studies, health and exposure information are determined
at a single point in time. These studies are often described as surveys.
This approach is most appropriate for acute rather than chronic effects,
that is, health effects that are temporally close to the exposures. They
also are appropriate for exposures that have been stable over time. Cross-sectional
studies are readily feasible with manageable costs. In such study designs,
it is possible to perform intensive monitoring of exposures to complex mixtures.
Cross-sectional studies are not appropriate for studying the effects
of exposures (or mixtures) that are changing over time or health effects
that occur only after a long latency period. In particular, cross-sectional
data cannot describe the longitudinal relation between exposure and the
health end point. The potential for selection and information bias in such
studies must be considered carefully.
Ecologic studies are a class of cross-sectional studies in which a group
rather than an individual is the unit of comparison. Aggregate information
rather than individual information is used to describe both exposure and
effect. Ecologic studies are straight-forward, easily undertaken, and low
in cost. However, confounding can be a severe problem in these studies.
In air pollution epidemiology in particular, semiecologic studies are common
in which individual health-status data is collected but exposure is determined
from a single ambient-air pollution monitor.
In designing cross-sectional studies, it is often possible to select
study populations such that exposures are limited to only one pollutant,
or the range of exposures to one pollutant is very limited. For example,
exposure to ETS could be limited in a study of NO2 or radon by
restricting the population to households with no smokers, as in the Albuquerque
study of respiratory illness and NO2 exposures in infants (8).
In studies of oxidants, exposures to acid aerosols could be limited by considering
only communities with low sulfur emissions (e.g., west coast communities).
By such restrictions, the effects of individual pollutants that usually
are found in mixtures can be assessed.
Alternatively, a factorial design can be implemented in which groups
of participants having similar proportions of exposure are chosen based
on prior knowledge of exposure or some marker of exposure. A factorial design
allows estimation of the separate effects of each pollutant, as well as
estimation of the effect of interaction.
In the Six Cities Study of indoor ETS and NO2 (9),
participating households were selected randomly from strata defined by previously
obtained reports of smoking in the home and the presence of an unvented
combustion appliance. The correlation between annual mean concentration
of respirable particles (PM2.5) and NO2 measured in
these homes was only 0.1, so that the effect of PM2.5 and of
NO2 could each be estimated without strong confounding by the
other pollutant. In the Harvard 24 Cities Study of the health effects of
acid aerosols and ozone, study communities were selected to provide a contrast
in the two pollutants (10). Existing ozone measurements for each
community were examined along with measured sulfate and other indicators
of the potential for acid-aerosol exposure. The purpose of this design was
to optimize the power of this study to estimate the separate effects of
acid aerosols and ozone. Similar selection criteria could be used in selecting
households for inclusion in a study of ETS and radon.
Populations also can be studied cross-sectionally in time. For example,
rates of diseases can be compared temporally within a community with time-varying
air pollution. Chronic effects can be estimated by comparison of annual
disease rates with changing concentrations of air pollution. For example,
can communities be identified in which sulfates concentrations, a marker
of maximum aerosol acidity, have dropped while ozone concentration has risen?
Acute effects, such as daily mortality or hospital admissions, can be
compared with daily air pollution measurements. These acute health-effects
studies are usually described as time-series analyses. For a complex mixture,
if the pollutants are not correlated perfectly, it is possible that the
separate and joint effects can be estimated. In studies of ozone and acid
aerosols, there is generally high correlation between the two exposures.
An alternative strategy might be to perform a time-series study in separate
communities with contrasting mixtures of these pollutants. For example,
a community with both ozone and acid aerosols versus a community with ozone
alone might be studied. Optimally, we would want to study a community with
acid but no ozone.
In this sense, point sources of pollution may offer unique opportunities
to investigate individual effects of pollutants that are usually found in
complex mixtures. For example, NO2 usually is found in photochemical
smog along with CO and O3. Shy et al. (11) examined the
effects of NO2 produced by a TNT plant in Chattanooga, Tennessee.
Similarly, a study of a community adjacent to a sulfuric acid plant could
provide unique information on the health effects of acid aerosols in the
absence of oxidants.
Populations in developing countries are exposed routinely to air pollution
concentrations and mixtures that are no longer seen in the United States
or elsewhere in the developed world. Unique opportunities exist in such
communities for studying mixtures of air pollution at extreme concentrations
or in mixtures of pollutants not generally observed in the United States.
Cohort Studies
In cohort studies, subjects are selected based on exposure status and
are followed to monitor the development of a specific health end point.
Cohort studies can be conducted prospectively or retrospectively. In a prospective
cohort study, exposure status is determined from current or historical records
and the subjects are followed to monitor the development of disease. This
design is not appropriate for rare diseases but works well for common end
points. Many disease end points can be considered simultaneously with little
increase in cost. For prospective cohort studies, extensive exposure assessment
can be undertaken. Prospective cohort studies are especially efficient for
assessing acute associations of air pollution exposures and respiratory
health end points that vary over time.
The disadvantages of this design are the potential difficulty and high
cost of implementation. The follow-up of study populations over extended
periods of time is difficult. Large numbers of subjects are required if
rare diseases are to be considered. This study design generally has weak
power to measure interactions.
As in the cross-sectional study, interaction between pollutants in a
complex mixture can be limited by restriction criteria on the sample cohort
such that one pollutant is missing or its range is limited. Factorial designs
also can be implemented to insure adequate sample sizes for each pollutant
individually and for the joint distribution.
For a two-pollutant mixture, a factorial design allows the separate and
joint effects of each pollutant to be estimated. In such a design, study
subjects are selected such that there are equal numbers (or constant proportions)
in each of the four cells defined by dichotomized exposure (high versus
low) to one pollutant crossed with dichotomized exposure to the second pollutant.
As an example, in a study of indoor radon and ETS exposures, never-smoking
subjects could be selected based on radon levels in their homes (e.g., above
or below 4 picocuries/m3) and having a spouse who is a smoker
(yes or no). A cohort with equal numbers of subjects in each of the four
exposure groups would allow estimation of separate effects of radon and
smoking, as well as their interaction. However, as has been noted earlier,
for a rare event or an end point with a long latency, such as cancer, such
a factorial cohort study would require extremely large sample sizes.
Prospective cohort studies have been used successfully to evaluate the
acute effects of time-varying exposures to single air pollutants on daily
reports of symptoms and changes in pulmonary function. For example, Pope
et al. (12) studied a panel of school children and asthma patients
in a location with pollution from particles only. Symptom reporting, peak
flows, and medication for asthma were each associated with PM10.
Clinical studies have suggested that exposure to one pollutant may potentiate
the subsequent effect of exposure to a second pollutant. For example, Koenig
et al. (13) found that exposure to ozone potentiates the subsequent
response to sulfur dioxide among adolescent asthmatics. In the ambient environment,
however, exposures to complex mixtures usually are highly correlated temporally
such that differentiating associations may be impossible. Study populations
with unique characteristics may allow the investigation of serial exposure
to multiple pollutants. For example, the acute effects of ETS and NO2
may be different among subjects exposed to both pollutants simultaneously,
as opposed to subjects exposed only to ETS at work and NO2 at
home.
Case-Control Studies
In a case-control study, subjects with a specific outcome of interest,
the cases, are identified. A control series also is identified consisting
of persons without the disease who potentially would be selected as cases
if they were to develop the disease. Exposure histories of both cases and
controls are determined and compared to estimate the risk of disease associated
with exposure.
Case-control studies are efficient particularly for assessing risks associated
with infrequent diseases and diseases with long latency periods. Generally,
only one health end point can be considered, but multiple exposures can
be evaluated with little additional cost.
Exposure is ascertained retrospectively or estimated from current measurements.
Thus, there is potential for substantial random misclassification of exposure.
Information bias is possible if there is not careful blinding of disease
status of the participants. Selection bias is possible if cases and controls
are not drawn from comparable populations. Case-control studies of the effects
of air pollution have been infrequent perhaps because of the difficulty
of reconstructing past exposures with acceptable precision (1).
Nested case-control studies are a hybrid design in which cases and controls
are selected from within a larger cohort of subjects being followed historically
or prospectively. The disease outcome is determined for all subjects in
the cohort, but exposure information is determined only for the subset of
subjects who develop the disease, that is, all cases, and a subset of subjects
selected as controls. Nested case-control studies have been efficient particularly
in cohort studies in which blood or other biological samples have been obtained
and stored as part of regular evaluations of the study cohort. This approach
makes efficient use of the measurement of biomarkers when the costs of the
measurement are high. If biologic indicators of exposures to air pollutants
can be identified, this design could be especially efficient.
The case-control design has been used widely to investigate the associations
of lung cancer with exposure to ETS and to indoor radon. However, because
exposures are estimated retrospectively, it is not clear that such a study
can be designed to assess interaction of pollutants. Lubin et al. (14)
have shown that testing for the interaction of active smoking and indoor
radon exposure will require substantial numbers of subjects, possibly more
than would be feasible in a single study. Evaluating interactions of indoor
radon with ETS will be even more difficult. The off-diagonal exposures,
that is, subjects with exposure to one but not both pollutants, can be enriched
by selecting cases from populations with limited exposure to one of the
pollutants. Restriction can improve the power of the study to estimate separate
effects of pollutant mixtures. For example, cases and controls could be
identified in areas with low smoking rates to reduce exposure to ETS but
with high potential for radon exposures, or in areas with low radon potential
to investigate the univariate associations with ETS.
Intervention Studies
In intervention studies, the investigator adds or reduces exposures to
a cohort and then follows the cohort, assessing the impact of the intervention.
In medical interventions, this approach, in which patients are assigned
randomly to a treatment regimen (the randomized clinical trial), is considered
the standard for inference and tests of causality. Studies in which air
pollution is increased for specific subjects may be unethical. However,
studies of subjects with reduced exposures would be acceptable.
In particular, Goldstein et al. (15) have described a cohort study
of the acute effects of NO2 in which lung function of women was
measured before and after cooking a meal on a gas range. Lung function was
also measured before and after cooking an equivalent meal with a portable
electric stove replacing the gas stove. A larger scale intervention could
be considered in which a cohort of subjects were evaluated for acute effects
before and after changing their stove from gas to electric or electric to
gas. A less intrusive intervention might be possible through the installation
of an air-cleaning device specifically to remove ETS or to vent the exhaust
of the cooking stove.
Special opportunities can sometimes be found in which specific pollutants
are controlled unexpectedly. For example, Pope (16) performed an
elegant analysis of the effects of particulate air pollution on hospital
admissions based on a strike at a steel mill in Utah Valley. The steel mill
was the primary source of particulate pollution in the valley. During the
winter, when inversions develop, particulate levels build up to concentrations
above the standards. Concentrations of other pollutants usually associated
with particulates, that is, SO2, NO2, and O3,
were low. During the winter of 1986-1987, the steel mill was closed because
of a strike, and particulate concentrations were reduced substantially.
Comparison of respiratory hospital admissions in the strike year compared
to the years before and after showed a 2-fold decrease in admissions among
children. This study of opportunity has provided the clearest information
yet on the effects of particulates alone, a pollutant usually observed in
a mixture with other pollutants.
Occupational Studies
Occupational cohorts are valuable resources for epidemiologic studies
of environmental risks. Cohorts are assembled easily and exposure estimation
methods are well developed. The range of exposures can be large, facilitating
the detection of associations. On the other hand, exposures often are much
greater than those relevant for air pollution studies.
Occupational studies may provide opportunities to study exposures to
single pollutants that are not possible in the ambient environment. For
example, ozone exposures can be found in occupational settings without acid
aerosols or nitrogen oxides.
Occupational studies also have furnished information on interactions
that provide guidance for environmental studies. The interaction of active
smoking and radon exposures has been demonstrated in uranium miners. Direct
tests of interaction may be possible only at such extremes of exposure.
Migrant Studies
Epidemiologic studies of migrant workers have been useful particularly
in disentangling the effects of heredity and environment. It is possible
that studies of families moving into or out of areas of high pollution could
provide insights into the relative contribution of individual components
of multipollutant mixtures. For example, families moving from southern California,
where oxidant concentrations are high but where acid aerosol concentrations
are very low, to the Northeast, where both oxidants and acid aerosols can
be elevated, could provide information on the modification of the ozone
effect by acid aerosols. However, there are many other environmental changes
that would be associated with such a move that also must be considered.
Selection bias is also possible if the families have moved, at least in
part, for health reasons.
Summary
Epidemiologic studies of the respiratory health effects of air pollution
are difficult for the following reasons: a) Exposures are common,
so developing contrasts is challenging. Maximum exposures have been reduced
in the United States by control strategies. Populations free of exposure
to air pollution cannot be found. b) There may be substantial misclassification
of exposure. Ambient monitors do not reflect the range of exposures experienced
by individuals. Personal monitors provide only a short sample of an individual's
time-varying exposure. c) Exposures are multifactorial. Air pollution
exposures are universally to multiple pollutants. In addition, other environmental
insults, such as temperature and aero-allergens, may be correlated with
air pollution exposures. d) Respiratory health end points are multifactorial,
with air pollution being only one, and possibly only a minor, etiologic
factor. e) Effects are weak and, therefore, difficult to detect.
Nevertheless, information is needed to quantify health effects to the lowest
observed concentrations.
If the investigation of mixtures of pollutants is not considered in the
design of an epidemiologic study, then it is unlikely that the study will
have sufficient power to detect interactions or even the separate effects
of the individual pollutants in the analysis. Nevertheless, with innovative
and well-thought-out study designs, it should be possible to measure the
separate and joint effects of multiple pollutants in a mixture. No particular
study design stands out as offering the most potential for disentangling
the separate and joint effects. Creative epidemiologic designs and studies
of opportunity can provide insights into these issues. If epidemiology were
simply a matter of analyzing health and exposure data, we could set a computer
to work regressing the vast stores of national health data against the immense
amount of air pollution data that has been gathered. Fortunately for the
epidemiologist, an elegant study design is more compelling than an elegant
analysis.
