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Chapter 4
Concepts and Strategies in Planning
Epidemiologic Studies on Air Pollution
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4
CONCEPTS AND STRATEGIES IN PLANNING
EPIDEMIOLOGIC STUDIES ON AIR POLLUTION
INTRODUCTION
-
This chapter addresses the principles that underlie
the epidemiologic approach to air pollution research.
Because ambient air pollution is generally less severe
than in previous years, it is harder than it once was to
detect most adverse health effects of pollution with a
high degree of certainty. Research strategies that used
to be demonstrably successful need further development
and refinement if they are to be equally successful in
solving the major research problems that remain. Initial
success in protecting the public from the effects of air
pollution has led to a situation in which the research
questions must be more precise and the strategies chosen
to address them more focused. The need for precision
makes it necessary to seek out appropriately sensitive
research tools and methods that will be capable of linking
today's exposure with today's and tomorrow's health
effects.
This discussion of research strategies for the epidemi-
ologic study of air pollution is guided by several prin-
ciples. First, the development of research strategies
and the specification of research questions must precede
the creation of specific study protocols. Second,
epidemiology should be part of a larger framework in
which epidemiologic, toxicologic, and clinical studies
inform, complement, and reinforce each other. Third,
epidemiologic studies of air pollution should be highly
sensitive to small risks of disease, because large
numbers of people are exposed; to provide credible
estimates of those risks, they will require careful
attention to all potential sources of error at every
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phase of their design and conduct. Fourth, the multi-
faceted nature of most air pollution problems requires
that planning in epidemiology be interdisciplinary,
involving collaboration between different scientific
disciplines and between research sponsors and inves-
tigators. Fifth, the link between epidemiology and
regulation will be a two-way street, with research
planning illuminated by a clear understanding of the
practical issues and constraints involved in regulation,
and the regulatory process influenced by the product and
capabilities of research.
COMMUNICATION OF EPID=IO=GY W ITH OTHER
RESEARCH DISCIPLINES
Optimal use of the epidemiologic approach requires
that it communicate with the parallel disciplines of
clinical research and animal toxicology. This is
distinct from the development of multidisciplinary
research teams.
Communication between scientists in the
separate disciplines is essential and should not be
limited to scientists who are perceived to be working on
the same research questions. This communication can
always benefit from administrative sponsorship and encour-
agement, including attention to such mundane matters as
attendance at conferences, the locations of offices and
laboratories, and participation in strategic planning of
research and development of individual research projects
.
Interdisciplinary contact will improve any epidemi-
ologic strategy in air pollution in at least three ways.
First, results of experiments in the laboratory and
clinic will generate useful hypotheses for epidemiologic
studies. Examples are the observation of cellular, whole-
animal, or human adaptational responses to irritants as a
basis for studying the responses of various groups to
short-term pollution episodes and the observation of a
synergistic effect of two pollutants as a basis for
selecting communities potentially at high risk. Second,
clinical research and toxicology are needed to provide
better epidemiologic research tools. The development and
validation of short-term biologic markers that reflect
long-term respiratory damage constitute a good example.
Laboratory investigators concentrating on disease mech-
anisms or therapy are often unaware of the potential
applications of their work in population studies. For
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instance, a diagnostic test that is considered to be
superfluous or too inaccurate for clinical work might be
highly appropriate for testing large populations, because
of its low cost and noninvasive nature. Research and
development activity that leads to new research tools for
epidemiology should be distinguished from empirical
research on disease mechanisms and perhaps require
separate administration and funding. Third, as discussed
below, evidence from clinical research and toxicology is
used by epidemiologists to strengthen the inference of
causality in observed relationships between air pollution
and health effects.
Epidemiologic activity also contributes to clinical
research and toxicology. It can be an excellent source
of hypotheses for laboratory studies and, more important,
provide an outlook on disease that is critical for setting
priorities. Apart from its ability to produce data and
answer specific research questions, epidemiology offers a
perspective and a set of concepts that can be used to
guide efforts in disease prevention and research design.
CONSTRUCTING APPROPRIATE RESEARCH QUESTIONS
~ m e epidemiological method is the only way of asking
some questions in medicine, one way of asking others, and
no way at all to ask many.
Research planners can reduce the chances of investing
in inappropriate or inconclusive studies by clearly
identifying research questions in advance. We refer here
to a research question as a broad statement of a problem,
rather than a specific epidemiologic hypothesis for an
individual study. Major air pollution research questions
seldom emerge ab-initio from the intellects of creative
scientists. Most are public health questions that are
developed through interplay of the interests and capabil-
ities of the scientific community with extrascientific
forces, such as the availability of research funds and
the regulatory process. Once a question has been articu-
lated and is determined to be important from the stand-
point of public health, research planners have the goal
and responsibility of finding the most productive inves-
tigative strategy or determining that epidemiologic
studies are not feasible. In practice, an iterative
process is used both to develop and refine the formulation
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of research questions and to match each formulation with
the optimal strategy. The cycle of marshaling facts to
make a question explicit, devising a strategy, and then
refining the question with new facts is parallel to the
cycle of hypothesis-test-hypothesis that takes place at
the level of individual studies. In this type of applied
research, the development and refinement of the question
and of the strategy are inseparable, and the investigator
contributes equally to both.
The importance of specifying research questions cannot
be overemphasized. As in all scientific disciplines,
epidemiologic research questions begin in a rather general
form and are pruned to testable hypotheses that form the
basis for design of individual studies. Every epidemio-
logic study of the adverse health effects of air pollution
has to be crafted around the pollutant in question and
the adverse effect under consideration. The characteris-
tics of the population at risk, the time between exposure
and effect, and the amounts of exposure needed to produce
an effect of a given magnitude are specified to some
degree in the formulation of a study hypothesis. These
elements of a hypothesis usually cannot be specified to
the last detail; but, for a hypothesis to be useful, some
specification of each element must at least be implied.
Each study must conform to various investigative
constraints. These constraints, which must be appreciated
early in planning, are imposed by such factors as:
.
The frequency and natural history of the disease.
· The rate and the extent to which exposure to the
pollutant in question changes over time.
· The availability of biologic markers of exposure
or early effect.
· Other known or suspected causes of the health
effects in question.
The overall research strategy has to be chosen with
the best possible understanding of these four separate
dimensions, and the detailed research protocol has to be
designed to take them fully into account. The more we
recognize that exposures to pollutants change and that
given diseases have various causes, the more challenging
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it becomes to design a penetrating and efficient epidemi-
ologic research protocol. Protocols are most penetrating
and rewarding when the detailed research plan focuses on
a single answerable hypothesis. The few exceptions to
this important general rule include broad epidemiologic
surveys designed explicitly for surveillance and the
development of new hypotheses.
Epidemiology can be used to produce several different
kinds of information about air pollution and health. The
kind of information sought depends on the goals of the
researcher. The remainder of this section discusses six
types of broad research questions that can be addressed
epidemiologiclly and briefly describes the capabilities
of epidemiology to answer each type (for a more complete
discussion of these issues, see, for example, Morris's
Uses of Epidemiology 6 ) :
1. How does the state of health of a particular
community with respect to disease Y compare with that of
other communities? With itself over time?
2. What is the natural history of disease Y?
clinical spectrum?
How does it progress?
3. Is there any association between exposure X and
disease Y? Is the association causal?
4. How much does the risk of disease increase as
exposure increases (dose-response relation)? Is there a
magnitude of exposure for which the disease risk is zero
(a threshold)?
5. What are the risks of disease among various groups
in the general population?
6. How much of disease Y is due to exposure X? How
much will be prevented if exposure is reduced?
Question 1, regarding the monitoring of the health of
a population, can be addressed only with epidemiologic
methods. The relation of this question to air pollution
concerns is indirect, however, except for its role in
identifying study populations on the basis of contrasting
disease patterns. Question 2, about the pathogenesis and
natural history of a disease, can be answered through
clinical observation and through epidemiology; but this
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type of question is rarely at the center of interest in
air pollution studies, because there appear to be no
unique fair pollution diseases. n Moreover, although
epidemiology can undoubtedly contribute to the under-
standing of how an exposure results in disease, detailed
information of this kind is normally best provided by
intensive clinical and laboratory studies.
Most applications of epidemiology in air pollution
research have been to answer questions about correlations
and causal relationships between air pollutants and
various human health effects--Questions 3, 4, and 5. To
address them, the epidemiologist normally uses the measure
known as relative risk, the ratio of the incidence or
prevalence of an adverse effect in one population to the
incidence or prevalence in another population with a
different degree of exposure.
Epidemiology can be very effective in answering
Question 3, about the existence of any association
between air pollutants and disease, particularly if the
relative risk involved is large (sometimes arbitrarily
defined as 3.0 or greater).14 In such a situation, it
is usually most sensible to compare populations at
highest exposure with those whose exposures are low or
nil. If the relative risk is extremely large and the
disease is relatively rare in nonexposed persons, the
association will often be noticed first by clinical
observation, as in the case of the relationship between
vinyl chloride and angiosarcoma of the liver or between
asbestos and mesothelioma. It is reasonable to presume
that, in most populations without extreme exposure,
relative risks of overt clinical disease associated with
air pollution are of low to moderate magnitude (approxi-
mately 1.2-3.0). Detection and accurate quantification
of effects of this magnitude present the greatest
methodologic challenges to contemporary epidemiology.
Nevertheless, because it is unethical to conduct studies
involving deliberate long-term exposures or acute
exposures that might produce irreversible effects,
epidemiologic studies will remain the only way to detect
pollution-related forms of common chronic or serious
acute diseases in humans.
Epidemiologic studies of air pollution have much
greater limits in providing finely tuned information
about dose-response relationships or about thresholds or
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"safe levels (Question 4), particularly when small
relative risks of chronic diseases are produced by years
of low-dosage exposure. In those situations, it is
extremely difficult to discriminate, with the necessary
degree of precision, among populations with relatively
minor differences in exposure, for instance, long-term
exposure to ozone at 0.08 ppm versus 0.12 ppm. In
addition, if the amounts of individual pollutants are
highly correlated and tend to rise and fall together from
time to time and place to place, the role of each pol-
lutant can be difficult to isolate. Larger exposures can
be studied to construct models that simulate the behavior
of pollutants at lower dosages, but the reliability of
mathematical extrapolation is limited by its dependence
on unavoidable and untestable assumptions about the
dose-response relationships. Future studies will gradu-
ally become better at providing quantitative information
about the relationships between air pollutants and health,
if the techniques for assessing exposure and effect
mentioned in this report are developed and if research
planning is appropriate.
Epidemiology, the basic science of preventive medicine
and public health, views disease at the population level,
but it can be used to predict the risks of disease in
individuals or groups with various characteristics of
interest (Question 5). By virtue of the mandate of the
Clean Air Act (if for no other reason), it is essential
to understand the range of susceptibility to air-
pollution-related disease in the general population.
Except in a few instances of controlled-exposure studies
of volunteers with defined characteristics, such as
pre-existing illness, epidemiology is necessary to
identify high-risk groups. But precise determination of
dose-response relations for each sensitive group is
generally not feasible today.
The epidemiologic approach is uniquely suited to
answer Question 6, although it seems to have been asked
only rarely in relation to air pollution. This type of
question, which deals with attributable risk rather than
relative risk, asks how much of the overall burden of
disease in a population is attributable to air pollution
over the entire range of exposure. The answer has
obvious and important public health implications, because
it indicates the total amount of disease that is
potentially preventable and the amount that would not
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occur if air pollution were reduced. Results of research
to answer this kind of question are useful in making
decisions about reducing exposures across the board,
regardless of local or individual variations in suscep-
tibility or risk and regardless of the relative impor-
tance of direct effects and synergistic effects, which
are more difficult to know ahead of time. Epidemiology
offers a direct means for predicting and later assessing
the public health impact of changes in the environment,
whether positive or negative, deliberate or unintentional.
In summary, Questions 1 and 2 are fundamentally
epidemiologic, but are likely to be of limited interest
in EPA's air pollution activities; epidemiology has made
and can continue to make substantial contributions toward
answering Questions 3 and 5 and, to a smaller extent,
Question 4; and the epidemiologic approach has scarcely
been applied to Question 6, although that application
might be valuable.
CONS IDERATIONS IN STUDY DES IGN,
ANALYS IS, AND INTERPRETATION
Epidemiologic projects concerning air pollution are
among the most difficult to design. One reason is that
ambient air pollution adds small increments to the
respiratory morbidity risks of large masses of people,
rather than large increments to the risks of a few. The
dynamic and complex nature of air pollution makes it
particularly difficult to measure, and its very nature
surrounds it with confounding factors, such as temperature
and humidity. Study design thus affords little margin--
yet frequent opportunities--for error. Furthermore,
epidemiologic studies, unlike laboratory experiments, are
not easily repeated, so elimination of potential errors
during study design is of paramount importance. Evalua-
tion of all potential errors (such as that caused by the
combination of very low exposure and low risk of effect)
might lead study planners to conclude that epidemiologic
studies are not feasible for providing the particular
information desired.
The design of each study is a multistage process that
begins with the extraction of a specific hypothesis from
a general research question and ends with detailed budget
estimates. In between, the designers must decide what
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exposure and what outcome are most pertinent and which
measurements of each to use. They must then identify
potential confounding variables, choose a study method
and study populations that accommodate the hypothesis,
and plan for the eventual analysis and interpretation of
the data. This by no means involves a rigid sequence;
the order of the steps varies, and often a decision about
one step contains or implies decisions about others.
Nonetheless, each step plays a distinct role in the
study's integrity and the certainty that can be attached
to its results.
The overall goal is to design studies so as to increase
their validity in detecting and estimating the magnitude
of the relationships between air pollution and health.
Validity has two components: sensitivity and specificity.
Sensitive studies have a low probability of labeling a
harmful situation as harmless, and specific studies have
a low probability of labeling a harmless situation as
harmful. Ideal studies are sensitive enough to detect
small but widespread effects, yet specific enough to
discriminate real from spurious effects.
The complexity of the relationships among all the
variables that could affect results of air pollution
studies has two important implications:
· Study design and planning require expertise
regarding the concepts of epidemiologic research design.
· The success or failure of future studies will
depend increasingly on how well exposure, effect, and
confounding variables have been characterized during
study planning.
Study designers must have as much prior information as
possible concerning the distribution of the factors
responsible for nonrandom errors and confounding in the
various populations being considered for study. The
information can be inferred from previous studies of
similar populations or obtained directly from the study
populations themselves either before or during the study
in question. If the information is obtained during
planning, it can be used to alter the design of the
study, change sample sizes, or influence the selection of
study populations. Random errors (and nonrandom errors
that behave as random ones in populations) can be
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complete data on individual residential and occupational
histories, exercise and other personal habits, and perhaps
even preventive and curative medical expenditures.
In an effort to uncover other data sets of potentially
high value but relatively low cost, research planners
should investigate the possibility of working with insur-
ance companies, providers of prepaid health care, and
agencies that collect DRG records on hospital admissions.
In some cases, such groups might have mortality and
morbidity data of high quality coupled with data on
residential histories. These latter data are important
if links between air pollution and chronic illness are to
be investigated. By the same token, some international
data bases might have great utility in epidemiologic
analyses. Data from countries that have national health-
insurance programs might permit not only cross-sectional
analysis, but also time-series or longitudinal studies.
These data, if available, will be most useful if they
originate in countries where ambient air pollution data
are of high quality.
COST AND INFORMATION
m e feasibility and limits of epidemiologic strategies
are determined by their costs, as well as by their bene-
fits. Estimating the productivity and cost-effectiveness
of various ways to answer specific questions has become
an integral part of epidemiologic research planning. For
this purpose, benefits are usually conceived of as infor-
mation value--the degree to which the study's results
bridge the gap between the question and its definitive
answer or provide spinoff knowledge for other studies.
The benefits of a particular study are a function of its
pertinence and of the quality and amount of information
it delivers. Comparisons of the relative productivity of
optional research strategies and studies might contribute
more than any other planning effort to the establishment
of research priorities and the ultimate refinement of
question and design.
Cost considerations can enter at two levels of
planning. At the individual study level, the inves-
tigator strives to reduce costs as much as possible
without compromising the information value of the study.
At the strategic level, the planner balances information
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needs versus costs and distributes many kinds of resources
over a collection of studies. Planning at these two
levels is interdependent, because the relative costs of
possible studies are needed as input in the development
of the research strategy, and the evolution of the
strategy determines which study designs receive the most
thorough cost estimation. Cost and productivity analysis
must be viewed as an inherent part of the process of
planning overall strategy, and not simply in terms of
proposals for individual, isolated studies.
The range of epidemiologic study costs is particularly
wide, and the relationship between cost and information
value is remarkably unpredictable. Some very inexpensive
studies provide information of enormous value, and some
large and expensive ones contribute little. The infer-
ential value of a study often has more to do with its
timing and context than with its cost. In most air
pollution studies, it is easy to spend large amounts of
money by directing resources at the wrong potential
sources of error. For example, greater precision in
exposure measurements might be unprofitable if sample
sizes are inadequate or study populations are poorly
characterized.
A research program that aims to produce the best
possible epidemiologic studies will have to include
funding for complementary nonepidemiologic research,
including methodologic and technical development and
exposure characterization. Technologic research and
development, designed to provide better tools for
exposure and effect assessment, must be closely woven
into epidemiologic research strategies. Some of the
barriers to progress are technologic, just as others stem
from ignorance of the biology of disease or the limita-
tions of study method. From the viewpoint of the
strategic research planner, investment in critical
technology is cost-saving--when appropriate technology is
lacking, it might be impossible to answer contemporary
questions within reasonable costs. The removal of
technologic constraints can often be hastened if
scientists clearly specify their needs for research and
development. An obvious example is the lack of a
personal monitoring badge for nitrogen dioxide that can
measure short-term exposures. The limits of epidemi-
ologic research depend in part on the changing state of
the art of measurement in several disciplines, so they
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differ from one problem to another and from one time to
another.
THE MILIEU OF EPID=IO~IC BESEECH
The development of productive epidemiologic strategies
in a difficult field like air pollution research will
require time, organization, and patience. The creation
of the necessary milieu for such research depends on
several factors:
Stable administrative and financial support.
Adequate amounts of overall funding.
· An appropriate range of contact with sponsoring
and regulatory agency personnel.
· Provisions for training and career development of
new scientists.
.
Opportunities for assembling multidisciplinary
research groups consisting of epidemiologists, atmospheric
scientists, statisticians, and health effects scientists.
.
Opportunities for interaction among epidemiologists,
clinicians, and toxicologists.
Some potential adverse health effects of current air
pollution can be detected only through serial observations
over time. Such studies often entail followup of popula-
tion groups for several years by well-organized research
teams led with an exceptional degree of administrative
skill. Successful examples of long-term studies include
the 25-year British study of a cohort of children from
birth to young adulthood and the Harvard Air Pollution
Health Study of the growth and decay of lung function.5 2 6
The need for administrative and financial stability also
applies to a sequence of closely linked studies. The
Environmental Protection Agency's record of support for
epidemiologic studies since 1970 is one of cataclysmic
variation, from strong support to nearly complete with-
drawal of funds, in spite of heavy reliance on epidemi-
ologic research for risk assessment and standard-setting.
A minimal long-term base budget for epidemiologic studies
should be considered. With it, the research community
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could develop confidence in the stability of resources
necessary for long-term studies of exposed populations.
The conduct of long-term studies or of a sequence of
studies in a research strategy relies on some degree of
isolation from short-term changes in federal research
managers and agency priorities. However, a portion of
the epidemiologic research program should have the
flexibility to respond quickly to short-lived oppor-
tunities or demands and in so doing work closely with
research sponsors and regulators.
The expertise for designing and conducting epidemi-
ologic studies of air pollution is a rare resource that,
once established, needs to be cultivated and maintained.
Mechanisms to encourage the training of qualified epidemic
ologists and to assist in their career development are
needed. Continued failure to provide the appropriate
milieu for studies will have a downward-spiraling effect:
many young and qualified investigators will avoid air
pollution problems--a situation that will lead to a
further decline in the performance of epidemiologic
studies, which in turn impedes the recruitment of new
trainees.
.
-
the successful completion of epidemiologic studies on
air pollution requires a continuing collaboration among
members of various disciplines, including epidemiologists,
atmospheric scientists, health effects scientists, and
statisticians. It is essential that all members of a
research team be active in the initial planning of a
study to optimize the use of pertinent information and
tools available from different fields. Monitoring
specialists must be involved in population selection on
the basis of characterization data and must help determine
which types of exposure data need to be collected to
evaluate the biologic model of concern. It is equally
important for health effects scientists to be involved in
planning, to ensure that the biologic markers or indexes
of specified health effects are matched to the pollutants
being monitored. The sensitivity and specificity of
techniques, the appropriate time for sampling, and the
doses of material received by target organs need to be
considered. Statisticians are essential in planning, to
help to ensure that data of the appropriate type and
amount will be collected and that problems in data
reduction, modeling, and analysis are anticipated.
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The difficulty and necessity of establishing
multidisciplinary groups in the framework of existing
academic and government research institutions must be
recognized. And it is necessary for the epidemiology
units to interact with clinicians and animal toxicologists
in the same or other institutions. Five-year grants,
specialized centers of research, and multiyear cooperative
agreements are some of the mechanisms possible for
creating stable and productive research groups. It is
important to incorporate appropriate peer review of these
centers and long-term projects into the funding process,
to help to ensure quality.
EPIDEMIOLOGIC DATA AND THE REGULATORY PROCESS
At the heart of the regulatory process for ambient air
pollutants in the United States is the determination of
approximate "safe" exposures to specific pollutants. In
some instances, for some aspects of the standards, epi-
demiologic data can provide the direct basis for such
determination. In other instances, epidemiologic studies
cannot yet provide the type of quantitative answer
required for control of a particular pollutant. Even in
the latter case, the determination of a standard will
hardly rely on a single definitive study, and standard-
setting inevitably involves the careful weighing of many
pieces of evidence of various kinds. It is often not
recognized that it is the cumulative force of different
studies (each of which could be faulted in one respect or
other) that gives strength-to the data. Each piece of
evidence can contribute to regulatory decisions; in the
process of making regulatory decisions, the nature and
extent of the uncertainty attached to each piece must be
carefully evaluated.
Although the proper domains of ~science" and "regula-
tion,~ or risk assessment and risk management, are
becoming well understood, problems of communication
remain. Those charged with the responsibility of making
decisions might find it difficult to understand why
straightforward answers to simple questions are not
forthcoming. Attempts (praiseworthy in themselves) to
avoid overinterpretation of data can be interpreted as
disbelief in the significance of any data; efforts to
reduce what must remain subjective to a formal quasi-
mathematical process, which the data base might be too
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fragile to support, might mislead those who are
unfamiliar with the details of studies into believing
that the data are stronger than they really are.
Such difficulties cannot be resolved by refinement of
data, although that is always desirable. What is needed
is the opportunity for those who analyze the data in
detail or participate in collecting them to exchange
ideas with those who are involved with policy, until each
side is sure that the other fully grasps the strengths
and weaknesses of the data being relied on. One of the
objectives of this chapter has been to describe how
uncertainty in epidemiologic studies of air pollution
might be characterized, so that it can be captured and
conveyed properly to policy-makers. This uncertainty
must be weighed against the uncertainty that has been
built into the process for setting standards and margins
of safety.
Epidemiology has many uses in protecting the public
from air pollution, beyond the setting of specific stan-
dards. Epidemiologic studies can point out areas or
major pollution sources that need regulation or some form
of intervention and can monitor the health of communities,
to assess the results of favorable or unfavorable changes
in pollution. Research that is directly applicable to
standard-setting should not always take priority over
research that is needed for the understanding of broader
health issues.
Finally, evidence of safety is not the converse of
evidence of risk; safety is often much harder to demon-
strate. m at is the critical difference between the
interpretation of studies that find an effect and studies
that do not. There are several reasons for the differ-
ence: statistical power of studies might be adequate to
show large effects, if they are present, but not to
exclude smaller effects that are of regulatory interest;
nonrandom errors might be more easily dealt with in
positive studies; clear demonstration of an effect in one
population segment might create a presumption of effects
elsewhere that is not balanced by similarly clear demon-
stration of the lack of effects in other segments; and
control measures might be required if a small part of the
population is affected, but not rendered superfluous if a
large part is shown to be unaffected. Thus, good large
studies with negative results can often have less meaning
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than smaller poorer studies that are positive. Fairness
is not the issue; negative studies, no matter how large
and well conducted, can rarely be used to exclude
important health effects in other populations and other
circumstances.
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Representative terms from entire chapter:
longitudinal studies
