A Brief Introduction to Epidemiology X Epidemiologic Research Designs: Cohort Studies

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A Brief Introduction to Epidemiology -
X(Epidemiologic Research DesignsCohort Studies)

• Betty C. Jung, RN, MPH, CHES

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Learning/Performance Objectives

• To develop an understanding of
• What cohort studies are
• The value of such studies
• The basic methodology
• Pros and Cons of such studies

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Introduction

• Epidemiology studies the distribution of disease
  in a number of ways.
• The two major categories of epidemiological
  studies are Observational and experimental
  studies.
• Most epidemiological studies are observational.

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Epidemiological Study Designs

• Observational Studies - examine associations
  between risk factors and outcomes (Analytical -
  determinants and risk of disease, and descriptive
  - patterns and frequency of disease)
• Intervention Studies - explore the association
  between interventions and outcomes. (Experimental
  studies or clinical trials)

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Research Designs in Analytic Epidemiology

• Ecologic Designs Cross-Sectional Study
• Case-Control Study
• Cohort Study

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Cohort Studies

• Motion Picture Studies (Paffenbarger, 1988)
• Forward looking. The most powerful of
  observational studies
• Follow groups of individuals free from disease
  through a period of time
• Quantified with relative risk/incidence
  rates/attributable risk

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Examples of Cohort Studies

• Framingham Heart Study
• Body fat distribution and 5-year risk of death in
  older women (1993) - 15-unit increase in
  waist/hip circumference was associated with 60
  greater relative risk of death. Waist/hip
  circumference ratio as a better marker than body
  mass index of risk of death in older women.
• Vasectomy and Prostate Cancer - those who had a
  vasectomy and those who did not. Increase
  relative risk of those with vasectomy - increase
  risk of prostate cancer.

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Historical Cohort Studies

• Cohort formed in the past with period of
  follow-up ending also in the past
• Used in occupational settings were population
  registers (payroll records) are available
• Example Atomic bomb blast survivors

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Value

• Gold standard for studying the association
  between a risk factor and outcome
• Useful for studying incidence, risk factors,
  natural history or prognosis
• Useful for studying multiple outcomes
• Useful for looking at multiple exposures and
  their interactions

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Cohort Study Design

• Direction of Inquiry

Time
Exposed
Disease
People Without Disease
Population
No Disease
Not Exposed
Disease
No Disease
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Cohort Study Design
Concurrent 1995
Retrospect 1975

Define Population
Non-randomizing
2005
1985
Exposed
Non-Exposed
2015
1995
Disease
Disease
No Disease
No Disease
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Methodology

• Start with persons having the presumed cause
  (antecedent or exposure). BUT free from the
  effect (disease), and then wait for them to
  develop the effect
• Comparison group - also free from disease, but
  who, also DO NOT have the presumed cause

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Methodology

• Cohort - group or aggregate of persons who have
  presume antecedent characteristics in common and
  observe the development or non-development of a
  given health outcome
• Compare to those free of the disease or health
  outcome under study. Issue being at risk of
  repeated episode (i.e., Stroke, antecedents may
  different between prestroke 1 and prestroke 2

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Cohort Study Measures

• Cumulative Incidence - new cases/at risk
  population
• Incidence Density - new cases/at risk
  person-time
• Measures of association
• Relative Risk
• Odds Ratio

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Strength of Association

• Relative Risk(Prevalence) Odds Ratio
  Strength of Association
• 0.83-1.00 1.0-1.2 None
• 0.67-0.83 1.2-1.5 Weak
• 0.33-0.67 1.5-3.0
  Moderate
• 0.10-0.33 3.0-10.00
  Strong
• lt0.01 gt10.0
  Approaching
  Infinity
• Source Handler,A, Rosenberg,D., Monahan, C.,
  Kennelly, J. (1998)
  Analytic Methods in Maternal and Child Health. p.
  69.

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Pros

• Can study situations where randomization is not
  possible
• Time sequence strengthens the inference about
  cause (temporal relationship between exposure and
  outcome)
• Only way to establish population-based incidence

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Pros

• Direct measure of incidence (risk) and prognosis
  (natural history)
• Incidence rate is not influenced by the presence
  of the effect (outcome/disease) at the beginning
  of the study
• Magnitude of a risk factors effect can be
  quantified
• Can estimate the relative contribution of
  different (multiple) causes to the occurrence of
  the effect (disease or outcome)

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Pros

• Can count the number of prevalent cases, and new
  cases, as well as the number and proportion of
  cases that can be prevented
• Information bias is decreased (i.e., selective
  recall/memory)
• Can better measure the impact of confounding

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Pros (Historical Cohort Studies)

• Easier to create the cohort
• Baseline measurements available
• Follow-up has already occurred
• Less costly and time consuming

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Cons

• Expensive
• Not good for low-incidence (rare) diseases
• Not good for chronic diseases with long latency
• Time needed to conduct these studies
• Unexpected changes to the environment can
  influence the association of disease and possible
  cause over time

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Cons

• Non-response/Migration bias loss to follow-up
  
• Selection bias zero time not defined (lead-time
  bias)
• Sampling bias
• Ascertainment/Assessment bias of outcome (can be
  reduced by blinding/masking)

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Cons

• Information bias data are different (i.e.,
  different hospitals) must to be comparable for
  exposed and unexposed
• Confounding bias
• Measurement bias - misclassification
• Analytic/Observer bias how data are analyzed
  and interpreted

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Cons (Historical Cohort Studies)

• Incomplete data sets
• No control over the quality of the measurements
  that are available
• Incomplete control of confounding

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References

• For Internet Resources on the topics covered in
  this lecture, check out my Web site
• http//www.bettycjung.net/