Epidemiology
The Basics Only…
Adapted with permission from a class
presentation developed by Dr. Charles
Lynch – University of Iowa, Iowa City
Epidemiology
• Study of the distribution and determinants
of health-related states or events in
specified human populations and the
application of this study to control of health
problems.
Epidemiology Objectives
•
•
•
•
Identify etiology of disease
Determine extent of disease
Study natural history
Evaluate new modes of health care
delivery and new preventive and
therapeutic measures
• Provide foundation for developing public
policy
Usual Pattern of Reasoning
• Develop a hypothesis
• Test the hypothesis on an exposed human
population and include an appropriate
comparison group
• Systematically collect and analyze data to
determine whether a statistical association
exists
Usual Pattern of Reasoning
• Assess validity of any observed statistical
association by excluding possible
alternative explanations such as
– Chance (random error)
– Bias (systematic error)
– Confounding (effects of additional variables)
– Describe interaction
Usual Pattern of Reasoning
• Judge whether the observed association
represents a cause-effect relationship
between exposure and disease
VALIDITY
Definition
The degree to which a
measurement or study
reaches a correct
conclusion
TYPES OF VALIDITY
Definitions
• Internal: Do the results of an
investigation accurately reflect
the true situation of the study
participants?
• External (i.e., generalizability):
Are the results of a study
applicable to other populations?
Internal and External Validity
• Internal validity– must be the primary study objective
because you would not want to generalize
an invalid result
Epidemiologic Study Cycle
Descriptive Studies - data
aggregation and analysis
Analysis of results
suggests further descriptive study
of hypotheses and new hypotheses
Analytic Studies to
test hypotheses
Form hypothesis
Types of Studies
• Observational
– Descriptive
• Study of the amount and distribution of disease
within a population by person, place, and time
– Analytic
• Study of the determinants of disease or reasons
for relatively high or low frequency in specific
groups
Descriptive
• Undertaken when little is known of the
epidemiology of a disease
• Provides information on patterns of
disease occurrence in populations by
characteristics such as age, race, marital
status, social class, occupation,
geographic area, and time occurrence
Descriptive
• Usually uses routinely collected data
IMPORTANT DIFFERENCE
• Used to generate the hypothesis NOT test
the hypothesis
Descriptive
• Populations
– Correlational
– Ecologic
– Aggregate
• Individuals
– Case report (describes
single patient)
– Case series (describes
characteristics of a
number of patients)
Analytic
• Designed to test causal hypotheses that
usually have been generated from
descriptive studies
• Collection of new data
• More definitive conclusions about
causation
Types of Studies for Testing
Hypotheses
Observational
– Cross-sectional
– Case-Control
– Cohort (prospective, retrospective
Intervention (experimental, clinical trials)
Experimental Versus Observational
Study Design
Experimental Study
Population
Observational Study
Population
Random Allocation
Other-than-random
Allocation
(e.g. Self-Selection)
Group A
Group A
Group B
Group B
Sequence of Studies in Human Populations
Clinical Observations
Available Data
Case-Control Studies
Cohort Studies
Randomized Trials
Descriptive
Studies
Design of a Randomized Clinical
Trial
Defined Population
Randomized
New
Treatment
Improved
Not Improved
Current
Treatment
Improved
Not Improved
Clinical Applications of
Various Types of Studies
Type of Study
Application to Clinical Practice
Etiologic
Can risk be reduced among
susceptible persons?
Diagnostic
Can accuracy and timeliness of
diagnosis be improved?
Prognostic
Can prognosis be determined
more definitively?
Therapeutic
Can treatment be improved?
Case Reports
• Describe the experience of a single
patient
• Generally provide detailed
documentation of a unique medical
occurrence
• May lead to the generation of a new
hypothesis
• Traditionally, a common type of study
published in medical journals
• Chief limitation: Sample size of 1
Case Series
• Collections of individual case
reports
• Often used as an early means to
identify the beginning or presence
of an epidemic
• May lead to the generation of a
new hypothesis
• Chief limitation: Lack of an
appropriate comparison group
Descriptive Studies of Population
Groups
• Also called
– Correlational studies
– Ecologic studies
– Aggregate studies
• Studies in which the unit of analysis is
some aggregate of individuals rather
than an individual person
CHANCE
Definition of P-value
The probability that an
effect at least as extreme
as that observed in a
particular study could
have occurred by chance
alone, given that there is
truly no relationship
between exposure and
disease.
CHANCE
P-value
• If p-value < 0.05: Since there is
less than a 5% probability (1 in
20 chance) of observing a
result as extreme as that
observed due solely to chance,
we generally consider the
association between the
exposure and disease to be
statistically significant.
CHANCE
P-value
• If p-value > 0.05 - by convention:
–We generally consider that
chance cannot be excluded as a
likely explanation
–Findings are stated to be not
statistically significant at that
level
BIAS
Definition
Any systematic error in the
design, conduct, or analysis of a
study that results in a mistaken
estimate of an exposure’s effect
on the risk of disease.
CONFOUNDING: ANOTHER TYPE OF
BIAS
Definition
• A variable that:
– Is causally related to (or at least associated with)
the disease under study (or, as often occurs in
practice, serves as a proxy measure for unknown
or unmeasured causes), and
– Is associated with the exposure under study in
the study population but is not a consequence of
this exposure