Study Designs: Cohort Studies Chapter 7 Learning Objectives • Differentiate cohort studies from other study designs • List main characteristics, advantages, and disadvantages of cohort studies • Describe three research questions that lend themselves to cohort studies • Calculate and interpret a relative risk • Give three examples of published studies discussed in this chapter Temporality • Temporality refers to the timing of information about cause and effect. • Did the information about cause and effect refer to the same point in time? • Or, was the information about the cause garnered before or after the information about the effect? Limitations of Other Study Designs • Demonstrating temporality is a difficulty of most observational studies. Limitations of Other Study Designs (cont’d) • Cross-sectional and case-control study designs are based on exposure and disease information that is collected at the same time. • Advantage: Efficient for generating and testing hypotheses. • Disadvantage: Leads to challenges regarding interpretation of results. Limitations of Other Study Designs (cont’d) • Cross-sectional studies: – Present difficulties in distinguishing the exposures from the outcomes of the disease, especially if the outcome marker is a biological or physiological parameter. Limitations of Other Study Designs (cont’d) • Case-control studies: – Raise concerns that recall of past exposures differs between cases and controls. Limitations of Other Study Designs (cont’d) • There has been no actual lapse of time between measurement of exposure and disease. • None of the previous study designs is well suited for uncommon exposures. What is a cohort? • A cohort is defined as a population group, or subset thereof, that is followed over a period of time. • The term cohort is said to originate from the Latin cohors, which referred to one of ten divisions of an ancient Roman legion. What is a cohort? (cont’d) • Cohort group members experience a common exposure associated with a specific setting (e.g., an occupational cohort or a school cohort) or they share a non-specific exposure associated with a general classification (e.g., a birth cohort—being born in the same year or era). Cohort Effect • The influence of membership in a particular cohort. • Example: Tobacco use in the U.S. – Fewer than 5% of population smoked around the early 1900s. – Free cigarettes for WWI troops increased prevalence of smoking in the population. – During WWI, age of onset varied greatly; then people began smoking earlier in life. – One net effect was a shift in the distribution of the age of onset of lung cancer. Cohort Analysis • The tabulation and analysis of morbidity or mortality rates in relationship to the ages of a specific group of people (cohort) identified at a particular period of time and followed as they pass thro.

1. Study Designs: Cohort
Studies
Chapter 7
Learning Objectives
• Differentiate cohort studies from other
study designs
• List main characteristics, advantages, and
disadvantages of cohort studies
• Describe three research questions that
lend themselves to cohort studies
• Calculate and interpret a relative risk
• Give three examples of published studies
discussed in this chapter
Temporality
• Temporality refers to the timing of
information about cause and effect.

2. • Did the information about cause and effect
refer to the same point in time?
• Or, was the information about the cause
garnered before or after the information
about the effect?
Limitations of Other Study
Designs
• Demonstrating temporality is a
difficulty of most observational
studies.
Limitations of Other Study
Designs (cont’d)
• Cross-sectional and case-control study
designs are based on exposure and
disease information that is collected at the
same time.
• Advantage: Efficient for generating and
testing hypotheses.

3. • Disadvantage: Leads to challenges
regarding interpretation of results.
Limitations of Other Study
Designs (cont’d)
• Cross-sectional studies:
– Present difficulties in distinguishing the
exposures from the outcomes of the disease,
especially if the outcome marker is a
biological or physiological parameter.
Limitations of Other Study
Designs (cont’d)
• Case-control studies:
– Raise concerns that recall of past
exposures differs between cases and
controls.
Limitations of Other Study

4. Designs (cont’d)
• There has been no actual lapse of time
between measurement of exposure and
disease.
• None of the previous study designs is well
suited for uncommon exposures.
What is a cohort?
• A cohort is defined as a population group,
or subset thereof, that is followed over a
period of time.
• The term cohort is said to originate from
the Latin cohors, which referred to one of
ten divisions of an ancient Roman legion.
What is a cohort? (cont’d)
• Cohort group members experience a
common exposure associated with a

5. specific setting (e.g., an occupational
cohort or a school cohort) or they share a
non-specific exposure associated with a
general classification (e.g., a birth
cohort—being born in the same year or
era).
Cohort Effect
• The influence of membership in a particular
cohort.
• Example: Tobacco use in the U.S.
– Fewer than 5% of population smoked around the
early 1900s.
– Free cigarettes for WWI troops increased
prevalence of smoking in the population.
– During WWI, age of onset varied greatly; then
people began smoking earlier in life.
– One net effect was a shift in the distribution of the
age of onset of lung cancer.

6. Cohort Analysis
• The tabulation and analysis of morbidity or
mortality rates in relationship to the ages
of a specific group of people (cohort)
identified at a particular period of time and
followed as they pass through different
ages during part or all of their life span.
Wade Hampton Frost
• Popularized cohort analysis method.
• Arranged tuberculosis mortality rates in a
table with age on one axis and year of
death on the other.
• One can quickly see the age-specific
mortality for each of the available years on
one axis and the time trend for each age
group on the other.

7. Wade Hampton Frost
Life Table Methods
• Give estimates for survival during time
intervals and present the cumulative
survival probability at the end of the
interval.
• Example: Life tables can be constructed to
portray the survival times of patients in
clinical trials.
Life Table Methods (cont’d)
• There are two life table methods:
– Cohort Life Table
– Period (Current) Life Table
Life Table Methods (cont’d)
• Cohort life table:

8. – Shows the mortality experience of all persons
born during a particular year, such as 1900.
• Period life table:
– Enables us to project the future life
expectancy of persons born during the year
as well as the remaining life expectancy of
persons who have attained a certain age.
Describing the Mortality
Experience of the Population
• Years of Potential Life Lost (YPLL)
• Disability-adjusted life years (DALYs)
YPLL
• Years of potential life lost (YPLL)
– Computed for each individual in a
population by subtracting that person’s
life span from the average life
expectancy of the population

9. DALYs
• Disability-adjusted life years (DALYs)
– Adds the time a person has a disability
to the time lost to early death
Survival Curves
• A method for portraying survival times
• In order to construct a survival curve, the
following information is required:
– Time of entry into the study
– Time of death or other outcome
– Status of patient at time of outcome, e.g.,
dead or censored (patient is lost to follow-up)
Cohort Studies
• Start with a group of subjects who lack a

10. positive history of the outcome of interest
and are at risk for the outcome
• Include at least two observation points:
one to determine exposure status and
eligibility and a second (or more) to
determine the number of incident cases
Cohort Studies (cont’d)
• Permit the calculation of incidence rates
• Can be thought of as going from cause to effect
• The individual forms the unit of observation and
the unit of analysis.
• Involve the collection of primary data, although
secondary data sources are used sometimes
for both exposure and disease assessment
Cohort Studies
Timing of Data Collection

11. Sampling and Cohort Formation
Options
• Cohort studies differ according to
sampling strategy used.
• The two strategies are population-
based samples and exposure-based
samples.
Population-Based Cohort Studies
• The cohort includes either an entire
population or a representative sample of
the population.
• Population-based cohorts have been used
in studies of coronary heart disease.
Framingham Study
• Conducted in Framingham,
Massachusetts
• Ongoing study of CHD initiated in 1948

12. • Used a random sample of 6,500 from
targeted age range of 30 to 59 years
Tecumseh Study
• Conducted in Tecumseh, Michigan
• A total community cohort study
• Examined the contribution of
environmental and constitutional factors to
the maintenance of health and origins of
illness
• Started in 1959-1960 and enrolled 8,641
(88% of the community)
Population-Based Cohort
Studies (cont’d)
• Exposures unknown until the first period of
observation when exposure information is
collected
• Examples: After administration of
questionnaires, collection of biologic

13. samples, and clinical examinations, there
can be two or more levels of exposure.
Exposure-Based Cohort Studies
• These studies overcome limitations of
population-based cohort studies, which
are not efficient for rare exposures.
• Certain groups, such as occupational
groups, may have higher exposures than
the general population to specific hazards.
Definition of Exposure-Based
Cohort
• An exposure-based cohort is made up of
subjects with a common exposure.
• Examples:
– Workers exposed to lead during battery
production

14. – Childhood cancer survivors
– Veterans
– College Graduates
Comparison (Non-Exposed Group)
• Cohort studies involve the comparison of
disease rates between exposed and non-
exposed groups.
• The comparison group is similar in
demographics and geography to the
exposed group, but lacks the exposure.
• In an occupational setting, several
categories of exposure may exist.
Outcome Measures
• Discrete Events
–Single events and multiple occurrences
• Levels of Disease Markers

15. • Changes in Disease Markers
–Rate of change, change in level within
time
Temporal Differences in Cohort
Designs
• There are several variations in cohort
designs that depend on the timing of data
collection.
• These variations are:
– prospective cohort studies
– retrospective cohort studies
Prospective Cohort Study
• Purely prospective in nature;
characterized by determination of
exposure levels at baseline (the present),
and follow-up for occurrence of disease at

16. some time in the future
Advantages of Prospective
Cohort Studies
• Enable the investigator to collect data on
exposures; the most direct and specific
test of the study hypothesis
• The size of the cohort is under greater
control by the investigators
Advantages of Prospective Cohort
Studies (cont’d)
• Biological and physiological assays can be
performed with decreased concern that the
outcome will be affected by the underlying
disease process.
• Direct measures of the environment (e.g.,
indoor radon levels, electromagnetic field

17. radiation, cigarette smoke concentration) can
be made.
Retrospective Cohort Study
• Despite substantial benefits of prospective
cohort studies, investigators have to wait
for cases to accrue.
• Retrospective cohort studies make use of
historical data to determine exposure level
at some baseline in the past.
Advantages of Retrospective
Cohort Studies
• A significant amount of follow-up may
be accrued in a relatively short period
of time.
• The amount of exposure data
collected can be quite extensive and
available to the investigator at minimal
cost.

18. Historical Prospective Cohort Study
• A design that makes use of both
retrospective features (to determine
baseline exposure) and prospective
features (to determine disease incidence
in the future)
• Also known as an ambispective cohort
study
Practical Considerations Regarding
Cohort Studies
• Availability of exposure data
• Size and cost of the cohort used
• Data collection and data management
• Follow-up issues
• Sufficiency of scientific justification
Availability of Exposure Data

19. • High quality historical exposure data are
absolutely essential for retrospective
cohort studies.
• Need to trade off between a retrospective
study design (with the benefits of more
immediate follow-up time) and collection of
primary exposure data in a prospective
cohort design.
Size and Cost of the Cohort
• The larger the size of the cohort, the
greater the opportunity to obtain findings
in a timely manner.
• Resource constraints typically influence
design decisions.
Data Collection and Data
Management

20. • Larger studies are more demanding than
smaller ones; challenges due to data
collection and data management.
• Explicit protocols for quality control (e.g.,
double entry of data and scannable
forms) should be considered in the
design and implementation stage.
Data Collection and Data
Management (cont’d)
• Organizational and administrative burdens are
increased when there are multiple levels of data
collection (such as phone interviews, mailed
questionnaires, consent forms to access
medical records).
Follow-up Issues
• There are two types of follow-up:

21. –Active follow-up
–Passive follow-up
Active Follow-up
• The investigator, through direct contact
with the cohort, must obtain data on
subsequent incidence of the outcome
(disease, change in risk factor, change in
biological marker).
• Accomplished through follow-up mailings,
phone calls, or written invitations to return
to study sites/centers.
Active Follow-up (cont’d)
• Example: Minnesota Breast Cancer
Family Study
– Mailed survey
– A reminder postcard 30 days later

22. – A second survey
– A telephone call to non-responders
Passive Follow-up
• Does not require direct contact with cohort
members.
• Possible when databases containing the
outcomes of interest are collected and
maintained by organizations outside the
investigative team.
• Example: Used in the Iowa Women’s
Health Study.
Sufficiency of Scientific
Justification
• There should be considerable scientific
rationale for a cohort study.
• Additional justification for cohort studies may
come from laboratory experiments or animal
studies.

23. • Cohort studies are the only observational study
design that permits examination of multiple
outcomes.
Cohort Studies:
Measures of Effect
• Relative risk is the ratio of the risk of disease or
death among the exposed to the risk among the
unexposed.
• Recall that risk is estimated in epidemiologic
studies only by the cumulative incidence.
• When the relative risk is calculated with
incidence rates or incidence density, then the
term rate ratio is more precise.
Relative Risk
Relative risk =
Incidence rate in the exposed
Incidence rate in the non-exposed

24. Relative Risk
• Using the notation from the 2 by 2
table, the relative risk can be
expressed as
[A/(A+B)] / [C/(C+D)]
Measures of Association
(cont’d)
Disease Status
Incidence
Exposure Yes No Totals Total
Status
Yes A B A+B A/(A+B)
No C D C+D C/(C+D)
A + C B + D N
Relative Risk [A/A+B]/[C/C+D]

25. Cohort Studies:
Sample Calculation
• Is there an association between child abuse
and suicide attempts among chemically
dependent adolescents?
• Source: Deykin EY, Buka SL. Am J Public
Health. 1994;84:634-639.
Sample Calculation (cont’d)
Examples of Major Cohort Studies
• The Alameda County Study
– Studied factors associated with health and
mortality
– Involved residents of Alameda County, CA,
ages 16-94 years
– Data collected through mailed
questionnaires; telephone interviews or home
interviews of non-respondents
– Follow-up with same procedures at years 9,

26. 18, and 29
Examples of Major Cohort Studies
(cont’d)
• Honolulu Heart Program
– Studied coronary heart disease and stroke in
men of Japanese ancestry
– Involved men of Japanese ancestry living on
Oahu, HI, ages 45-65 years
– Data were collected through mailed
questionnaires, interviews, and clinic
examinations.
Examples of Major Cohort
Studies (cont’d)
• Nurses’ Health Study
– Originally studied oral contraceptive use;
expanded to women’s health

27. – Married female R.N.s ages 30-55 years
– Data collected through mailed questionnaires
– Follow-up every 2 years; toenail sample at
year 6 and blood sample at year 13
Nested Case-Control Studies
• A nested case-control study is defined as a type
of case-control study “. . . in which cases and
controls are drawn from the population in a
cohort study.”
• Example: nested case-control breast cancer
study
– Controls are a subset of the source population for
the cohort study of breast cancer.
– Cases of breast cancer identified from the cohort
study would comprise the cases.
Advantages of Nested Case-

28. Control Studies
• Provide a degree of control over
confounding factors.
• Reduce cost because exposure
information is collected from a subset of
the cohort only.
• An example is an investigation of suicide
among electric utility workers.
Strengths of Cohort Studies
• Permit direct determination of risk.
• Time sequencing of exposure and
outcome.
• Can study multiple outcomes.
• Can study rare exposures.
Limitations of Cohort Studies
• Take a long time

29. • Costly
• Subjects lost to follow-up
Table 7-6
• Table 7-6 summarizes various study
designs by comparing their characteristics,
advantages, and disadvantages.
Chapter 6
Study Designs: Ecologic,
Cross-Sectional, Case-
Control
Learning Objectives
• Define the basic differences between
observational and experimental epidemiology
• Identify an epidemiologic study design by its
description

30. • List the main characteristics, advantages, and
disadvantages of ecologic, cross-sectional, and
case-control studies
• Describe sample designs used in epidemiologic
research
• Calculate and interpret an odds ratio
How Study Designs Differ
• Number of observations made
• Directionality of exposure
• Data collection methods
• Timing of data collection
• Unit of observation
• Availability of subjects
Observational vs. Experimental
Approaches
• Manipulation of study factor
– Was exposure of interest controlled by

31. investigator?
• Randomization of study subjects
– Was there use of a random process to
determine exposure of study subjects?
Typology of Epidemiologic
Research
Overview of Study Designs
• Experimental studies
• Quasi-experimental studies
• Observational studies
– Descriptive studies: cross-sectional
surveys
– Analytic studies: many ecologic studies,
case-control studies, cohort studies

32. The 2 by 2 Table Represents the
Association Between Exposure and
Disease Status
Ecologic Studies
• The unit of analysis is the group, not the
individual.
• They can be used for generating
hypotheses.
• The level of exposure for each individual
in the unit being studied is unknown.
• Generally makes use of secondary data.
• Advantageous with cost and duration.
Types of Ecologic Studies
• Ecologic comparison study—involves an
assessment of the correlation between
exposure rates and disease rates among

33. different groups over the same time period.
• Ecologic trend study—involves correlation of
changes in exposure with changes in disease
within the same community, country, or other
aggregate unit.
Example of an Ecologic
Correlation
• The association between breast
cancer and dietary fat for 39
countries.
• High intakes of dietary fats
associated with high rates of breast
cancer mortality.
Examples of Questions Investigated
by Ecologic Studies

34. • Is the ranking of cities by air pollution levels
associated with the ranking of cities by mortality
from cardiovascular disease, adjusting for
differences in average age, percent of the
population below poverty level, and
occupational structure?
• What are long-term trends (1950-1995) for
mortality from the major cancers in the US,
Canada, and Mexico?
Applications of Ecologic
Approach
• The effect of fluoridation of the water
supply on hip fractures
• The association of naturally occurring
fluoride levels and cancer incidence rates
• The relationship between neighborhood or
local area social characteristics and health

35. outcomes
The Ecologic Fallacy:
Definition
• Observations made at the group level may
not represent the exposure-disease
relationship at the individual level.
• The ecologic fallacy occurs when incorrect
inferences about the individual are made
from group level data.
Implications of the Ecologic
Fallacy
• The conclusions obtained from an
ecologic study may be the reverse of
those from a study that collects data on
individual subjects.

36. The Ecologic Study: Example
• An ecologic study examines 10 individuals who
go into the sun.
• The study finds that 7 persons (70%) have
sunburned foreheads although 6 persons (60%)
wore hats.
• The expected number of sunburned foreheads
is 4 (the number who did not wear hats).
• The media report that wearing hats will not
protect you from sunburn.
What the Individual Data Show
Individual Data (cont’d)
• From the individual data, one observes
that 100% of persons (4) who did not wear
hats were sunburned.
• Among persons who wore hats (6), only

37. 50% were sunburned.
• This conclusion reverses the conclusion
from the ecologic data, i.e., that wearing
hats affords little protection from sunburn.
Ecologic Studies: Advantages
and Disadvantages
• Advantages
– Quick, simple, inexpensive
– Good approach for generating hypotheses
when a disease is of unknown etiology
• Disadvantages
– Ecological fallacy
– Imprecise measurement of exposure and
disease
Cross-Sectional Study
• Also termed prevalence study

38. • Exposure and disease measures obtained
at the individual level.
• Single period of observation
• Exposure and disease histories are
collected simultaneously.
• Both probability and non-probability
sampling is used.
Cross-Sectional Study:
Examples
• Surveys of smokeless tobacco use among
high school students
• Prevalence surveys of the number of
vasectomies performed
• Prevalence surveys of cigarette smoking
among Cambodian Americans in Long
Beach, California
Uses of Cross-Sectional
Studies

39. • Hypothesis generation
• Intervention planning
• Planning health services and
administering medical care facilities
• Estimation of the magnitude and
distribution of a health problem
• Examine trends in disease or risk factors
that can vary over time
Limitations of Cross-Sectional
Studies
• Limited usefulness for inferring disease
etiology
• Do not provide incidence data
• Cannot study low prevalence diseases
• Cannot determine temporality of exposure
and disease
Overview of Case-Control

40. Studies
• In a case-control study with two groups, one
group has the disease of interest (cases) and a
comparable group is free from the disease
(controls).
• The case-control study identifies possible
causes of disease by finding out how the two
groups differ with respect to exposure to some
factor.
Characteristics of the Case-
Control Study
• A single point of observation
• Unit of observation and the unit of analysis
are the individual
• Exposure is determined retrospectively
• Does not directly provide incidence data
• Data collection typically involves a

41. combination of both primary and
secondary sources.
Selection of Cases
• Two tasks are involved in case
selection:
–Defining a case conceptually
–Identifying a case operationally
Sources of Cases
• Need to define a case conceptually
• Ideally, identify and enroll all incident
cases in a defined population in a
specified time period
• A tumor registry or vital statistics bureau
may provide a complete listing of all cases
• Medical facilities also may be a source of
cases, but not always incident cases
Selection of Controls

42. • The ideal controls should have the same
characteristics as the cases (except for the
exposure of interest).
• If the controls were equal to the cases in all
respects other than disease and the
hypothesized risk factor, one would be in a
stronger position to ascribe differences in
disease status to the exposure of interest.
Sources of Controls
• Population-based controls--Obtain a list that
contains names and addresses of most
residents in the same geographic area as the
cases.
– A driver’s license list would include most
people between the ages of 16 and 65.
– Tax lists, voting lists, and telephone
directories
– Patients from the same hospital as the cases

43. – Relatives of cases
Measures of Association Used
in Case-Control Studies
Disease Status
Yes (Cases)
No (Controls)
Yes
A
B
E
x
p
o
s
u
re

44. S
ta
tu
s
No
C
D
A+C B+D
Odds A/C B/D
Odds Ratio AD/BC
Case-Control Studies
Sample Calculation
• On the association between chili pepper
consumption and gastric cancer risk: a

45. population-based case-control study
conducted in Mexico City
• Source: Lopez-Carillo, et al. Am J
Epidemiol. 1994;139:263-71.
Sample Calculation (cont’d)
Chili Pepper Consumption Cases of Gastric
Cancer
Controls
Yes A = 204 B = 552
No C = 9 D = 145
The OR (unadjusted for age and sex) is:
AD = (204)(145) = 5.95
BC (552)(9)
Interpretation of an Odds Ratio
(OR)
• OR = 1 implies no association.

46. • Assuming statistical significance:
– OR = 2 suggests cases were twice as
likely as controls to be exposed.
– OR<1 suggests a protective factor.
Odds Ratio (cont’d)
• An OR provides a good
approximation of risk when:
– Controls are representative of a target
population.
– Cases are representative of all cases.
– The frequency of disease in the
population is small.
Examples of Case-Control
Studies
• Young women’s cancers resulting from utero
exposure to diethylstilbestrol

47. • Green tea consumption and lung cancer
• Maternal anesthesia and development of fetal
birth defects
• Passive smoking at home and risk of acute
myocardial infarction
• Household antibiotic use and antibiotic resistant
pneumococcal infection
Advantages of Case-Control
Studies
• Tend to use smaller sample sizes than
surveys or prospective studies
• Quick and easy to complete
• Cost effective
• Useful for studies of rare diseases
Limitations of Case-Control
Studies

48. • Unclear temporal relationships between
exposures and diseases
• Use of indirect estimate of risk
• Representativeness of cases and controls
often unknown
Key Points to Remember
• Descriptive studies: cross-sectional
surveys (hypothesis generation)
• Analytic studies: ecologic, case-control,
and cohort (hypothesis testing)
Conclusion
• Study designs differ in a number of key
respects, including the unit of observation;
the unit of analysis; the timing of exposure
data in relation to occurrence of disease
endpoint; complexity; rigor; and amount of

49. resources required.