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1. Introduction to Case Control
Studies
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Malimu MSc.Epidemiology PhD. Candi.
Department of Epidemiology and Biostatistics,
MUHAS./KIU

2. Learning Objectives
When you have completed this session you will be able to:
 Describe the characteristics of a case control study
 List the type of bias most likely to affect a case control study
 List the conditions under which a case control study is an appropriate
choice to address a research question
 Define the term “control group” and list the characteristics of a good
control group
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3. 3
Case-control
Cohort
Individuals
Intervention
Retrospective
Prospective
Descriptive
Populations
Analytical
Observational
Case-series
Cross-sectional
Ecologic
Clinical trials
Epidemiological studies

4. Intro to Case-control studies
 Case-control studies provide insight on the aetiology of many
condition
 Prone for bias in selecting cases/controls, eliciting exposure
status and sophisticated nature of its analysis
 Hallmark of a professional epidemiologist
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5. 5
Disease
No disease
Exposure
?
?
Retrospective Nature
Case-Control Study
(Case)
(Control)

6. Design of a Case-control Study

7. Variants of case-control design
 Case- control study (Classical)
 Case-cohort studies
 Case-only studies
 Case-crossover studies
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8. Major Steps in case-control study
 Define and select cases
 Select controls
 Ascertain exposures
 Compare exposure in cases and
controls
 proportions/odds ratios ....
 Test any differences for statistical
significance
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9. Observation
 Start with cases
 Are any observed exposures higher
than expected ?
 To find this out we need a comparison
group
 This group are known as controls
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10. Selection of cases
 Cases should be selected independent of the exposure
 Not necessarily represent all people with the disease but
controls should be from the same population as the cases
 Incident cases better than prevalent cases
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11. Who is the Right Control?
 As similar to a case as possible but without the disease in
question
 Selected from the same population or study base as cases
 Must have the same opportunity for exposure as a case
 Must be subject to the same inclusion and exclusion criteria
 No one control group is optimal for all situations

12. Examples of Controls
 Population control
 Neighbourhood
 Hospitals /clinic based-control
 Friends
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13. General Population Controls
 Advantages
 Exposure in the control estimate that of the population
 Direct calculation of risk
 Inferences are easy
 Include health people
 Disadvantages
 Cost
 Sampling frame
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14. Neighborhood Controls
 Advantages:
 Inexpensive,efficient
 Matched for potentially confounding variables
 Disadvantages
 Exposure related to neighborhood
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15. Hospital Controls
 Advantages:
 Convenient
 Easily identified
 More likely to comply, interviewed and tested
 Same selection procedure as cases
 Disadvantages:
-Not source population for the cases (Berksons bias)
-May have diagnosis interfering with outcome
-Generalizability problems
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16. Friend Controls
 Advantages
 Convenient
 Include health and cooperative people
 Disadvantages
 Friends may share same exposure (over-matching)
-Overlapping of friendships
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17. Number of controls
 Availability
 Ratio controls / cases
 Trade-off: cost vs. power
 Decision based on power calculation
 More than one control group?
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18. Biases in Case-control studies
 Selection biases
 Cases selection –external validity
 Controls selection-internal validity
 Measurement biases
 Observer bias-favour cases
 Recall bias-cases remembers more
 Information bias –equal collection methods
 Confounders
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19. Matching in Case –control studies
 It is a strategy for controlling potential confounders.
 Each case is matched with a control in a number of variables E.g. Age, sex, education…
 Advantages
 Help to control un-measurable confounders eg. Genetic-using siblings
 Eliminate the need to list all possible controls
 Increase precision of odds ratio
by weakening the assoc. btwn confounder and outcome
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20. Comparison of cases and control
 Comparison of occurrence of disease/event is made between
the exposed and unexposed
 Odds ratio (OR) is the measure of effect
 OR= odds of exposure among the cases
odds of exposure among the controls
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21. Cases Controls
Exposed a b
Not exposed c d
Total a + c b + d
Odds ratio = (a/c)/ (b/d) = a x d
b x c
Distribution of cases and controls according to exposure
in a case control study

22. 22
Oral Myocardial
contraceptives Infarction Controls
Yes 693 320
No 307 680
Total 1000 1000
Odds ratio = 693 x680 = 4.79
320 x 307
Distribution of myocardial infarction cases and controls
by oral contraceptive use

23. Odds Ratio: Interpretation
 OR > 1 - the risk of disease in the exposed
group is greater than the risk in the unexposed
group
 OR = 1 - the risk of disease is the same in the
exposed and unexposed (no association)
 OR < 1 - the risk of disease in the exposed
group is less than the risk in the unexposed

24. Advantages of Case Control Studies
 Rare diseases
 Multiple exposures
 Diseases with long latent periods
 Small sample size
 Low cost
 Secondary data analysis possible
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25. Disadvantages of Case-control Studies
 Limited to one outcome variable
 Selective survival effect
 Selection of controls difficult
 Not suitable for rare exposures
 Nonrepresenativeness of cases (Berkson’s
fallacy)!!!!
 Problems with recall (information bias)
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