Epidemiologic Reviews
Copyright © 2000 by The Johns Hopkins University School of Hygiene and Public Health
All rights reserved
Vol. 22, No. 1
Printed in U.S.A.
Epidemiology and Policy: The Pump Handle Meets the New Millennium
Jonathan M. Samet
INTRODUCTION
immediate relevance to the formation of policies
affecting health; therefore, these findings are often
prominent in the various processes by which policies
are made. On occasion, this prominence has resulted in
targeted review and criticism of specific epidemiologic
findings and of the discipline in general. As epidemiologic research has addressed increasingly complex
questions concerning the causes of disease, the risks of
environmental factors, and the benefits of interventions, the resulting evidence has in instances been subject to uncertainties that cloud decision-making, leading some to question the utility of epidemiologic data.
One widely quoted 1995 news report in Science, entitled "Epidemiology Faces Its Limits," offered the view
that epidemiologic inquiry may not be useful for
addressing "subtle links between diet, lifestyle, or
environmental factors and disease" (4, p. 164). The
topics that have sparked such criticism are well
known—for example, the relations between dietary fat
and breast cancer risk, breast implants and collagen
vascular disease, and air pollution and health.
The community of epidemiologic researchers is
divided in its own view of epidemiology and policy (1,
5). At one extreme, some would consider epidemiology no different from other branches of science in
which advancing knowledge is often given as the primary rationale for research; at the other, epidemiologic
research is construed as being justified only if the evidence is relevant to the advancement of public health.
Epidemiologists are similarly divided in their view of
their role in policy-making processes. Some eschew
such involvement, and one respected journal,
Epidemiology, prohibits authors from offering policy
recommendations in their papers. Others have called
for renewed activism by epidemiologists and engagement with sweeping social problems that underlie
many of the increased risks epidemiologists have elegantly and repetitively described (6, 7). Even as debate
continues, the use of epidemiology for policy purposes
is burgeoning with the rise of the outcomes movement
and the calls for evidence-based medicine, as well as
the need to apply the explosively expanding knowledge of the human genome in clinical and population
contexts.
The direct linkage of epidemiologic evidence to the
formulation of policy intended to advance public
health is widely acknowledged (1). Almost universally,
epidemiologists tell the story of John Snow and the
Broad Street pump to illustrate the immediacy of
observational findings for solving public health problems. Based on observation of cholera cases clustered
along Broad Street in London, Snow recommended the
removal of the municipal pump handle, and his advice
was heeded (2, 3). This example is particularly compelling, because Snow demonstrated waterborne transmission of cholera before there was knowledge of the
existence of the Vibrio cholerae organism. Numerous
other examples also considered triumphs of epidemiologic inquiry include the establishment of cigarette
smoking as a cause of lung cancer and other diseases;
the identification of powerful and remediable causes of
cancer, such as asbestos exposure and diethylstilbestrol administration during pregnancy; and the characterization of risk factors for acquired immunodeficiency syndrome. In spite of these evident successes,
the place of epidemiologic evidence in supporting
policy-making, as well as the role of epidemiologists
in the process of policy-making, remains controversial
and in flux.
As a core discipline of biomedical research, epidemiology is not unique in generating evidence relevant to policy: the ultimate goal of all biomedical
research is to advance the health of people.
Epidemiology as a scientific method brings evidence
that bears directly on the health of the population, and
it is this direct linkage that distinguishes epidemiology
from other branches of biomedical research. As a consequence, epidemiologic findings generally have
Received for publication August 24, 1999, and accepted for publication March 21, 2000.
Abbreviations: BEIR, Biological Effects of Ionizing Radiation; EPA,
Environmental Protection Agency.
From the Department of Epidemiology, School of Hygiene and
Public Health, Johns Hopkins University, 615 North Wolfe Street,
Suite W6041, Baltimore, MD 21205. (Reprint requests to Dr.
Jonathan M. Samet at this address).
145
146 Samet
Through example, we have also learned that use of
epidemiologic evidence as a foundation for policymaking may have consequences for the conduct of epidemiologic research and for the researchers themselves. Scientific evidence on the health effects of both
active smoking and passive smoking led to vigorous
campaigns by the tobacco industry to discredit the
findings. Epidemiologists whose research has been
cited in litigation may find themselves subjected to
subpoenas for the data and to having their credibility
questioned. Other recent examples include studies of
silicone breast implants and collagen vascular disease
and of involuntary smoking and lung cancer.
The turn of the millennium prompts an appraisal of
the relation between epidemiology and policy. The
future relevance of epidemiologic evidence for policymaking is certain, and experience provides examples
of successes and failures in the use of epidemiologic
evidence as a foundation for policy development. The
community of epidemiologists continues its debate on
the appropriate uses of the data generated in epidemiologic research. At the same time, we face emerging
new research paradigms that are driven by genetic
technology and information, and by a growing capacity to carry out large-scale studies using public and
administrative databases. However, we are still learning how to synthesize information from epidemiologic
and other research and how to interpret data combined
from multiple studies by meta-analysis or pooling of
individual-level data.
The research landscape has changed quickly for epidemiology, and the policy implications of this change
need exploration and resolution. This paper considers
some of the emerging challenges in the use of epidemiology for support of policy development. I first
consider general approaches for using epidemiologic
data in policy-making contexts and then discuss the
specific example of radon and lung cancer. I next turn
to emerging issues at the start of the new century.
From epidemiology to policy
The paths and processes leading from hypothesis to
policy (figure 1 and table 1) are diverse and often
lengthy and ill-defined. In the area of infectious disease epidemiology, findings may lead quickly to
action; for example, John Snow called for an immediate response to his findings on the waterborne transmission of cholera. Continuing in this tradition, investigators addressing infectious disease problems make
policy recommendations more often than their colleagues working in other areas (8). For some areas of
inquiry, however, evidence may accumulate slowly
(e.g., diet and cancer) and only reach a level of certainty sufficient for policy-making after decades of
Hypothesis
Environmental data
Observational data
Experimental data
Scientific Evidence
Synthesizing Process
Values
Costs
Ethics
Politics
"I
J
Mi
Model
Risk
Ri assessment
}
Strength of evidence
Uncertainty
Value for decision-making
Policy
FIGURE 1 . The interface of science and health policy.
research. Of course, research and policy-making are
interactive and iterative, and policies may change as
evidence evolves.
Some of the routes for translating epidemiologic and
other data into policy are listed in table 1. They range
from formal and structured, as in the requirements of
specific regulations, to informal and unstructured, as in
the choices which individuals make for their own
lifestyles. For example, the 1996 draft cancer policy
guidelines of the US Environmental Protection
Agency (EPA) (9) offer instruction for evaluating and
interpreting epidemiologic data, while criteria for
causality have been rigorously applied in the reports of
the Surgeon General on smoking and health (10, 11).
Specific actions may be invoked if the evidence
reaches a threshold of certainty—e.g., if a causal association is found or a target level of risk is reached.
TABLE 1. Some possible pathways for translation of
epidemiologic evidence into policy
Regulatory mechanisms
Occupational health and safety
Environmental quality
Drug safety
Public health recommendations
Vaccination
Diet
Smoking
Legal system
Causation of injury
Heath care delivery
Practice guidelines
Outcome assessment
Epidemiol Rev Vol. 22, No. 1, 2000
Epidemiology and Policy
Embedded within these translation routes are
processes for identifying and evaluating the relevant
evidence (table 2).
Historically, processes involving expert judgment
have been widely applied for translation. For example,
expert panels are convened by governmental agencies,
such as the Department of Health and Human Services,
the National Institutes of Health, and the EPA, by the
National Research Council and the Institute of
Medicine, and by nongovernmental agencies.
Operating principles for these committees are often
only loosely structured and based around gaining consensus. The consensus conferences of the National
Institutes of Health are based around a timed schedule
for being presented with evidence, evaluating the evidence, and reaching consensus, and then offering the
findings at a planned public presentation. Groups may
not readily come to consensus when the scientific evidence is ambiguous, or the consensus may be forced by
necessity. For example, the 1997 consensus conference
on mammographic screening for women under age 50
years sparked extraordinary controversy through its
conclusion that screening could not be universally recommended, and some committee members later disavowed the consensus (12). Similarly, when asked to
provide their recommendations for a new standard for
fine airborne particulate matter, members of the Clean
Air Scientific Advisory Committee convened by the
EPA offered a range of opinions based on epidemiologic and other data (table 3) (13). As table 3 shows,
there was not a clear consensus among the panelists,
and rifts across scientific disciplines were evident.
The evidence-based review process represents
another approach. Through literature searches and
other methods, all studies relevant to a particular topic
can be identified, their quality evaluated, and the
results organized. Quantitative summaries may be
undertaken by meta-analysis or pooled analysis, which
has the seeming advantage of replacing the judgment
of experts with quantitative objectivity. However, the
application of meta-analysis to observational data
remains controversial (14, 15), and in the example of
the EPA's use of meta-analysis for the effects of environmental tobacco smoke, the method's application
TABLE 2. Some possible processes for translation of
epldemiologic evidence into policy
Application of causal criteria
Expert opinion
Consensus methods
Committee review
Quantitative synthesis
Risk assessment
Jury evaluation
Epidemiol Rev Vol. 22, No. 1, 2000
147
was set aside by the North Carolina federal district
court (16). Nonetheless, organized and objective
approaches for evaluating evidence should be part of
evidence synthesis for policy development.
EXAMPLE: RADON AND LUNG CANCER
Radon, one of the first respiratory carcinogens identified, is an invisible and naturally occurring radioactive gas that contaminates the air in some types of
underground mines and in homes. Strong descriptive
evidence raised concern early in the 20th century that
radon caused lung cancer in underground miners. This
suspicion was confirmed in the early 1960s by the
excess lung cancer deaths observed in a prospective
cohort study of Colorado Plateau uranium miners (17,
18). The findings of the study were reviewed, as they
were reported, by the states and by the federal government, which held jurisdiction for the health and safety
of the miners. Although the mining industry raised
questions about the validity of the data, a federal standard for exposure in the mines was eventually implemented in 1971, driven by the epidemiologic evidence.
Even before the establishment of that standard, some
western states had implemented their own standards
and inspection programs. Subsequent studies of other
miners confirmed the risks shown in the Colorado
Plateau study (19) and eventually led to a proposal in
the 1980s for a lowering of the maximum radon concentration allowable in mines.
Beginning in the 1970s, there was increasing recognition that radon is also present in homes, sometimes
at remarkably high levels equivalent to those in underground mines. Policy-makers were confronted with the
problem of ubiquitous contamination of indoor air by
an established respiratory carcinogen, and they turned
to the scientific community for estimates of the associated risk of lung cancer as a guide to the needed level
of policy response (20). Initially, such risk estimates
were developed by extending the findings of individual epidemiologic studies to indoor exposures, but
more complex risk models based around the same
studies soon followed (21). These risk models indicated that radon should be considered a cause of a significant number of lung cancer deaths, with initial estimates of approximately 10,000 attributable deaths
annually (21). By the mid-1980s, the EPA declared the
evidence to be sufficient to warrant a call for measurement of radon levels in most of the nation's residences,
and mitigation if the guideline level was exceeded.
Extrapolation of risks from mines to homes was
viewed as a substantial uncertainty, and beginning in
the early 1980s, a wave of epidemiologic studies on
indoor radon was initiated (22). These included ecologic studies, which could not provide the risk esti-
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Samet
TABLE 3.
Recommendations of members of the Clean Air Scientific Advisory Committee, Environmental Protection Agency*
Committee
member
Paniculate measure (ng/m3)
Discipline
24-hour
Annual
PMJ
Current National Ambient Air Quality Standard
EPAt staff proposal
Ayres
Hopke
Jacobson
Koutrakis
Larntz
Legge
Lippmann
Mauderly
McClellan
Menzel
Middleton
Pierson
Price
Shy
Sametttt
Seigneur
Speizer
Stolwijk
Utell
White
Wolff
Physician
Atmospheric scientist
Plant biologist
Atmospheric scientist
Statistician
Plant biologist
Health expert
Toxicologist
Toxicologist
Toxicologist
Atmospheric scientist
Atmospheric scientist
Atmospheric scientist;
state official
Epidemiologist
Epidemiologist
Atmospheric scientist
Epidemiologist
Epidemiologist
Physician
Atmospheric scientist
Atmospheric scientist
24-hour
p
M,ot
Annual
PM,0
N/A*
18-65
N/A
12.5-20
150
150*
50
40-50
Yes§
20-50H
Yes§
Yes§
20-30
Yes§
Yes§,**,tt
Yes§,**,tt
25-3044
150
No
150
No
No
150
No
150
150
150
150*,H
50
40-50#
50
Yes#
Yes§
40-50
40-50
50
50
50
50
Yes#
Yes#
No
>65
20-50§§
50
NoHH
No
Yes§,HU##
Yes§,§§
Yes§§,***
20-30
Yes§,tt4
Yesfl,**
20-50
75t4
>65
No
>75§,«
No
15-20
20
Noirn
No
Yes§,**
Yes§,§§
Yes***
15-20
No
No
No
25-30*4:
No
20
No
Yes#
NoH,#
No
150
150*
No
150
150
150
150HH
50
Yes§
50
40-50
50
50
50
50
* Reproduced from Wolff (13).
t PM 25 , particulate matter < 2.5 u.g/m3 in diameter; PM10, particulate matter s 10 ng/m3 in diameter; NA, not applicable; EPA, Environmental Protection Agency.
X The annual standard may be sufficient; 24-hour level is recommended if 24-hour standard is retained.
§ Declined to select a value or range.
Tl Recommends a more robust 24-hour form.
# Prefers a PM 1(K , 5 standard rather than a PM10 standard.
** Concerned that upper range is too low based on a national PM 25 : PM ]0 ratio,
f t Leans towards high end of staff recommendation range.
XX Desires equivalent strigency as present PM10 standards.
§§ Yes, but decision was not based on epidemiologic studies.
ffll If the EPA decides that a PM 25 National Ambient Air Quality Standard is required, the 24-hour and annual standards should be 75
u.g/m3 and 25 ng/m3, respectively, with a robust form.
## Concerned that the lower end of the range is too close to background level.
* * * Low end of the EPA's proposed range is inappropriate; desires levels selected to include areas for which there is broad public and
technical agreement that they have P M 2 i pollution problems.
t t t Not present at meeting; recommendations are based on written comments.
XXX O n| y if the EPA has confidence that reducing PM will indeed reduce the components of particles responsible for their adverse effects.
mates needed by policy-makers (23), and case-control
studies, which were judged to be appropriate in design
for determining whether indoor radon posed a hazard.
The limitations of the case-control approach for precisely characterizing risk—exposure misclassification
and inadequate power—were quickly recognized, and
plans were made for future pooling of the studies' data
to gain the most precise risk estimates possible (24,25).
The most recent models for estimating the risk of
radon are based on epidemiologic data and are derived
by applying pooled analysis and meta-analysis. The
models were developed by a National Research
Council committee, the Biological Effects of Ionizing
Radiation (BEIR) VI committee (19), which obtained
and analyzed individual-level data from 11 studies of
underground miners, including 68,000 persons and
nearly 3,000 deaths from lung cancer. Two timedependent risk models relating lung cancer risk to
radon exposure were developed and used to estimate
risk for different exposure scenarios. A meta-analysis
of eight case-control studies, involving 4,263 cases
and 6,612 controls, provided a picture of risk quite
consistent with the projections from the underground
miner data (26). Uncertainties were evaluated systemEpidemiol Rev Vol. 22, No. 1, 2000
Epidemiology and Policy
atically, and their consequences for risk estimates were
quantified. The report was written with knowledge of
the needs of risk managers, and it offered a bridge
from the epidemiologic data to the numbers needed to
guide the selection of risk management approaches.
Future risk models for radon will continue to be based
on epidemiologic data. The prospective planning for
pooling of the case-control studies has proved successful, and within several years data from all of the studies
will be merged to create a total of more than 10,000
cases. Follow-up of the underground miner cohorts is
also ongoing, assuring the accrual of further detailed
data on the pattern of lung cancer risk over time.
Biologically based models that fold mechanistic concepts into the development of models from epidemiologic data are also on the horizon. The potential of such
models has been shown in the application of the twostage model of carcinogenesis to the Colorado Plateau
data by Moolgavkar et al. (27) and Luebeck et al. (28).
Policy actions have followed the evolution of the epidemiologic evidence. Initially, the findings of the
Colorado Plateau study motivated the establishment of a
federal standard for radon concentrations in mines. The
recent Presidential Commission on Radiation Experiments questioned retrospectively the ethics of even carrying out the study, given its view of the evidence available on risks to underground miners at the time (29). The
findings of the study of Colorado Plateau miners and of
subsequent studies of miners prompted calls for reduction of radon levels in mines in 1980 (30) and for legislation, the Radiation Exposure Compensation Act, in
1990 (31). The miner data have been analyzed for estimation of probability of causation as an epidemiologically informed basis for determining causation. For the
problem of indoor radon, increasingly certain risk estimates have been derived, all indicating a public health
problem of substantial magnitude.
In spite of the abundance of data, the pooling of
large data sets, and elegant analytical approaches, criticism of the risk models continues. The points of attack
relate to exposure error and confounding and to the
external validity of the miner-based models, even
though these issues were considered and addressed in
the BEIR VI report (19) and other reports. The continued questioning reflects the immediate policy implications of the epidemiologic data and the costly programs needed to reduce exposures of miners and the
general population to radon.
INTO THE NEW MILLENNIUM
Terris, an influential commentator on epidemiology
and policy, prefaces his 1980 paper, "Epidemiology as
a guide to health policy" (32), by lamenting the imbalance between clinical medicine and preventive mediEpidemiol Rev Vol. 22, No. 1, 2000
149
cine and the failure of health professionals and the
health establishment to embrace epidemiology. He further comments on "the unwillingness to accept the
validity of epidemiologic discoveries" and "the power
of private interests" (32, p. 551). While Terris may
paint a pessimistic but realistic picture for the last
decades of the century, I offer far more optimism, tempered with realism, concerning the role of epidemiology in policy formation in the new millennium.
In my view, epidemiology is better embraced and
more widely understood today than it was two decades
ago when Terris offered his somewhat gloomy
overview. The rise of clinical epidemiology has
brought epidemiologic methods into the mainstream of
clinical research, and epidemiology and biostatistics
are now recognized as core scientific methods for clinical investigation (33). We have seen the emergence of
other branches of epidemiology with acknowledged
relevance for clinical care—for example, pharmacoepidemiology and outcomes and effectiveness evaluation. In other domains, such as environmental health
and cancer, epidemiology is an equal partner with
other types of investigation, including toxicology.
Other reasons for optimism include technical
enhancement of the capabilities of epidemiologists;
the need for observational evidence for answering
questions related to disease outcomes; the utility of
genetic and other marker information; and the continued but more penetrating application of epidemiologic
methods to the characterization of causes of disease
and the course of disease.
New tools for conducting epidemiologic research,
together with the increasing capacity to manage and
analyze large databases, have increased the usefulness of epidemiologic evidence for answering policymakers' questions. Large administrative databases,
such as the Medicare files of the Health Care
Financing Administration, can be explored for testing
of hypotheses that have immediate relevance to policy; two examples are outcome of myocardial infarction in relation to hospital volume (34) and patterns
of care by race and gender (35, 36). Increasingly
powerful multivariable methods of data analysis can
detect patterns of association that are relevant to policy with confidence that the associations are not spurious, while new models for longitudinal data analysis facilitate our ability to describe disease and its
development in time (37, 38).
For some policy issues, evidence comes from
numerous and sometimes heterogeneous studies.
Synthesis of such data for policy purposes has often
been accomplished by expert review and consensus,
tabular summary, or application of criteria for causality. These processes have proved effective, especially
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Samet
for strong associations, but uncertainties in the evidence have undermined conclusions, particularly those
weighted by policy. An example is passive smoking,
for which the epidemiologic evidence has been the scientific basis for programs to reduce smoking in public
places: it has been repeatedly questioned by the
tobacco industry and its consultant scientists.
Combining evidence from multiple studies, whether
experimental or observational, has proved to be an
efficacious approach for synthesis. This combination
can be accomplished by meta-analysis, combining
summary estimates from individual studies, and
pooled analysis, analyzing data jointly from individual
participants in multiple studies. While the use of metaanalysis has been questioned (12), meta-analyses conducted properly have yielded useful and sometimes
unexpected findings (39). Pooled analysis is a more
powerful approach, offering the possibility of controlling for confounding and exploring effect modification
at the individual level. It is more demanding analytically and requires the effort of creating the pooled data
set for analysis. The array of alternative approaches for
synthesis, ranging from expert opinion to quantitative
summary, has not been rigorously evaluated, but more
recent approaches involving systematic evaluation and
quantitative summary of data seem preferable.
Challenges for the future
To paraphrase a quotation often attributed mistakenly to Niels Bohr, "making predictions is difficult,
particularly about the future." The breathtaking pace
of technological advances in the biomedical sciences is
certain to bring challenging new questions at an
increasingly rapid pace to epidemiology and its
researchers; the public will expect answers at a pace
which matches that of technological change, and this is
likely to lead to frustration in the translation of epidemiologic research into policy. Some of these challenges can be anticipated from recent events, and I
address some of the most recent and evident challenges below.
Data access
During the last decade, there have been numerous
attempts to obtain data that supported particular policies
by various parties affected by those policies. Examples
include the tobacco industry's repeated requests to the
courts to obtain data from key studies on smoking and
health, such as the American Cancer Society's Cancer
Prevention Studies (40, 41) and the multicenter US
study of passive smoking and lung cancer risk (42); the
many attempts, again through the courts, to obtain the
epidemiologic data on risks of connective tissue dis-
eases following breast implants (43,44); and the efforts
of trade organizations, and more recently chambers of
commerce, to obtain data from several epidemiologic
studies on air pollution and mortality that were critical
in the evidence base for the 1997 EPA standard on particulate matter (45). The results of two studies,
Harvard's Six Cities Study (46) and the American
Cancer Society's Cancer Prevention Study II (47), were
posed as the critical evidence linking paniculate air pollution to significant shortening of life.
In the latter case, the investigators were portrayed as
keeping their data "secret," even though they were
adhering to the assurances of privacy and confidentiality that had been given to participants who enrolled
years previously. The furor that followed resulted in the
already infamous Shelby Amendment, inserted by
Senator Shelby into the 1998 omnibus appropriations
bill, which requires public access to policy-relevant
data collected with federal financial support. The implications of this amendment for epidemiologic research
are potentially sweeping, and the implementing regulation, Circular A-110, has now been released by the
Office of Management and Budget. Federal grantawarding agencies are now required to ensure that all
data produced under an award will be made available
under Freedom of Information Act procedures (48).
Sound arguments can be advanced for and against
data-sharing (49). Often, epidemiologic studies are
unique and not readily replicable, particularly on a
short term basis, so one study or a few studies may
become heavily weighted in decision-making.
Proponents of data-sharing argue that significant public health decisions should not be made without assurances regarding the validity of data and the integrity of
analyses. They also point to the inherent subjectivity of
analysis as requiring further assurance that conclusions have been reached properly. Opponents of datasharing voice concerns about violating the conditions
of privacy and confidentiality under which the data
were collected originally, and about potentially misleading findings from analysts seeking to provide the
answers needed by their sponsors.
One possible solution has been applied by the
Health Effects Institute, a nonprofit organization
which funds research on air pollution with matching
funding from the EPA and motor vehicle manufacturers. In 1994, when considerable controversy arose concerning the findings of time-series studies of particulate air pollution and mortality, the Health Effects
Institute funded independent validation and analysis of
the most critical data sets (50). More recently, the
Institute has supported independent validation and
analysis of data from the two critical long term studies
of particulate air pollution and mortality. In both
Epidemiol Rev Vol. 22, No. 1, 2000
Epidemiology and Policy
examples, the new investigators were selected through
competitive processes, and independent oversight
groups were established. This model has proved useful, but it has the possibly constraining drawbacks of
requiring additional financial support and introducing
delay into policy development. Nevertheless, for the
most controversial problems involving epidemiologic
evidence, this type of process is likely to be needed
again and again.
The genomic revolution
The capacity to incorporate hypothesis-testing
related to the genetic basis of disease into epidemiologic studies has now arrived. With the anticipated
completion of the sequencing of the human genome
early in the 21st century, it is inevitable that population-based studies will increasingly incorporate the
collection of biologic specimens into their core
research (51, 52). Difficult issues related to research
policy have already arisen: the collection of biologic
specimens for future use when all of the possibilities
cannot be relayed to participants; the provision of
research findings to participants on their own genetic
risks; and the labeling of particular population groups
as being at risk, as in the example of Ashkenazi Jews
and breast cancer (53). The National Institute of
Environmental Health Sciences has launched an "environmental genome" initiative to explore the genetic
basis of disease susceptibility; in this instance, we will
need methods for handling genetically susceptible
individuals within regulatory frameworks that are
intended to provide broad public health protection
(54). Perhaps the Clean Air Act, which calls for standards to protect public health within an "adequate margin of safety" for the major pollutants for virtually all
persons regardless of susceptibility, can provide an
example. Undoubtedly, difficult issues will continue to
arise as we apply the results of studies of genetic factors in policy contexts; the potential for surprises and
challenges is recognized (55).
Further elaboration of policy translation processes
The difficulties of interpreting epidemiologic evidence and providing clear "bottom line" messages for
policy-makers are well recognized. Processes intended
to provide distilled messages include various forums
for expert committees, such as those convened by the
National Research Council and the Institute of
Medicine; the consensus conferences convened by the
National Institutes of Health; and the prescribed syntheses used by some regulatory agencies, including the
EPA. For the development of clinical guidelines, structures for systematic reviews of evidence have also
Epidemiol Rev Vol. 22, No. 1, 2000
151
been elaborated (56, 57). Quantitative methods have
been applied as well: meta-analysis of summary findings from published and unpublished reports and
pooled analyses of individual-level data from multiple
studies. Other frameworks include risk assessment
(58) and cost-benefit and decision analysis (59).
Epidemiologic data, if available, can indicate the
potential impact in these frameworks. In a recent
attempt to gain scientific guidance, a federal judge
appointed a scientific panel including an epidemiologist to advise him on silicone breast implants (60).
To date, the relative merits of these approaches for
translation of epidemiologic findings to policy have
received little systematic analysis. There is a persistent
tension between the carefully guarded and uncertaintyshrouded findings of epidemiologic research and the
needs of policy-makers. This would appear to be an
appropriate topic for research and for exchange with
policy-makers. How can research designs be improved
to meet the potential policy applications of the findings? How should findings be expressed? How should
the level of certainty be quantified? What are comparative strengths and weaknesses of methods used to reach
conclusions from epidemiologic and other evidence?
Global-scale questions
The last few decades have brought the first evidence of global environmental change: stratospheric
ozone depletion secondary to the release of chlorofluorocarbons and rising carbon dioxide concentrations from the release of "greenhouse" gases (61).
Scientists anticipate direct and indirect health effects.
Stratospheric ozone depletion increases exposure to
skin cancer-causing ultraviolet radiation, and rising
carbon dioxide concentrations have been postulated to
have a variety of potential health consequences
through global warming (62-64). The time scale of
effects exceeds that of usual epidemiologic inquiry,
since the environmental changes are taking place at a
pace measured in centuries and decades, not years.
Lessons can be learned from incidents such as the
1995 epidemic of heat-related deaths in Chicago,
Illinois (65), but the principal tool for policy analysis
is integrated assessment modeling, which joins models of climate change, adaptation, and health impact.
Epidemiologists can play a key role in developing
models of health impact—for example, by linking
ultraviolet radiation exposure to risk for malignant
melanoma, or by assessing the potential for spread of
malaria if the territory of its mosquito vector expands
because of climate change. Epidemiologists taking on
this critical problem will work in an interdisciplinary
environment that draws more on modeling than on
gathering of data and empirical analysis. Policies for
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limiting global environmental change will be based
largely on such models.
Meeting public expectations
Epidemiologic evidence will continue to be of great
interest to the public and to draw the attention of
policy-makers. The public has high expectations as it
seeks straightforward answers to seemingly simple
questions: What is a healthy diet? Is it safe to have several alcoholic drinks each day? Is the black smoke
from diesel vehicles dangerous? Do pesticides in food
increase risk for childhood cancer? What about cellular telephones? Epidemiologic research on these questions and others of concern to the public will continue;
we have no preferable investigational approach at present. The findings of new studies may be dramatized to
the public by the media, and the public may be confused by seemingly conflicting information as emphasis is given to the most recent study without placement
in the context of prior work.
As we start the next century, the public's expectations
will be—and should be—high. We are in an unprecedented era of ample research funding in the United
States and have increasingly powerful tools available for
investigation. Collectively, we have promised to answer
difficult research questions, and we face being held
accountable by the public and policy-makers. For example, the National Research Council's Committee on
Research Priorities for Airborne Particulate Matter has
charted a multiyear "research portfolio" costing several
hundred million dollars, inherently promising that completion of the portfolio will address critical scientific
uncertainties in our understanding of particulate air pollution (66). Epidemiologists should tackle challenging
questions, but with recognition of their responsibility to
state clearly what has been learned from the research.
We need to work more effectively with those who communicate with the public: the media, public health officials, and others; and we should sharpen our ability to
communicate our findings and target them more effectively. Above all, we need to remain cognizant of our
responsibility to the public. A call for "more research" is
itself a policy statement, indicating a level of uncertainty
that calls for continued collection of data. While future
research may be an appropriate "bottom line," public
and private funding of research is made to find answers
to society's questions today.
risk factors at the individual level to the neglect of the
broad social and economic factors that shape health;
emphasis on methods to the exclusion of public health
application; and a focus on molecular minutiae rather
than populations (6, 7, 67, 68). I believe the debate is
indicative of the rising relevance of epidemiologic
research for addressing societal questions, and, of
course, there is no exclusivity to the seemingly competing domains. The debate also speaks to the collective ferment in the field and to the quickly shifting paradigms for research. Epidemiologic evidence will
remain relevant to policy-making, if research
approaches evolve with sufficient rapidity.
How will the community of epidemiologic researchers respond to these challenges? Unfortunately, our
record to date is not promising, as professional organizations of epidemiologists have not had a perceived
mandate to address such issues. The American College
of Epidemiology, a relative newcomer, has identified
policy-relevant issues in its charge, and the American
Public Health Association speaks on a wide array
of policy issues, some relevant to epidemiologists.
Epidemiologists and the field's organizations have
largely responded as needed rather than moving ahead
proactively. Issues critical to the field, e.g., data-sharing,
have often arisen quickly and without warning. We lack
mechanisms for identifying these challenges prospectively and even for generating responses that will be
seen as carrying weight. In anticipation of still more
challenges, education in epidemiology needs to be
accompanied by a broad understanding of the use of epidemiologic evidence, and the field's journals should be
bulletin boards for notification and discussion.
I am not pessimistic about the future. In just a short
time, the relevance of epidemiologic evidence to policymaking has been demonstrated repeatedly, and benefits
for public health can be shown. The field's current introspection and near self-flagellation should lead to a deepening of the links between epidemiologic research and
public health, through heightened policy relevance; but
it is time to move from serf-criticism to solutions. Some
future commentator at another landmark date will probably turn to this and other articles written at the turn of
the millennium for a snapshot of epidemiology's status
at the time. For that future reader, I predict that epidemiology will remain central in guiding policy to better the world's health.
THE FUTURE OF EPIDEMIOLOGY
Perhaps sparked by the new millennium, a spate of
recent articles have appeared on the status and future
of epidemiology and policy (1, 67, 68). The discussion
seems to be polarizing: there seems to be concern with
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