A breif introduction to analytical study designs and case control study in detail. Will be useful for lectures.

1. ANALYTICAL STUDY
DESIGNS
CASE CONTROL STUDY

2. LEARNING
OBJECTIVES
To develop an understanding of……….
➔ What case-control studies are??
➔ The value of such studies
➔ The basic methodology
➔ Pros and Cons of such studies

3. Lesson plan:
Target group: Third year BDS students
LO Content Method Time Media
1 Study designs introduction Explanation 5 min Slide 5– 6
2 Analytical study design Explanation 5 min Slide 7 - 10
3 Case control study design
Explanation 10 min Slide 11 - 18
4 Matching Explanation 5 min Slide 19 -21
5 Odds ratio Explanation 10 min Slide 22 - 24
6 Bias in case control Explanation 10 min Slide 25 - 27
7 Pro and cons of case control Explanation 5 min Slide 27 - 28

4. CONTENTS
 STUDY DESIGNS – RECAP
 ANALYTICAL STUDY DESIGNS
 INTRODUCTION TO CASE CONTROL STUDY
 DESIGN OF A CASE CONTROL STUDY
 ELEMENTS OF A CASE CONTROL STUDY
 MATCHING
 ODDS RATIO – CALCULATION AND INTERPRETATION
 PROS AND CONS OF CASE CONTROL STUDY
 SUMMARY

5. STUDY DESIGNS - RECAP

6. Epidemiological Study Cycle
DESCRIPTIVE STUDY
• Ca Lung increasing  mostly smokers
• Death rates higher in populations with higher per
capita cigarette consumption
Ochsner,
1939
CASE CONTROL STUDY • Ca Lung patients and non patients
Clarifies if it was smokers who contributed to high Ca
Lung
Doll, 1947-
52
COHORT STUDY • Follows a cohort of smokers and non smokers
without Ca Lung
•Smokers develop Ca Lung more frequently
INTERVENTIONAL TRIAL
(RCT) •Proves hypothesis conclusively
•Gives inputs regarding other factors, control measures.
Hypothesis:
Smoking causes
Ca Lung
Hill, 1951-61

7. Analytical studies
History of medicine has always been fascinated in discovering the
causes of the disease and the ways in which these could be modified.
CAUSES OF DISEASE
EVENT, CONDITION, CHARACTERISTIC
OR COMBINATION OF FACTORS
DISEASE
EXPOSURE
SEVERAL
OBSERVATIONS
HAVE TO BE MADE
ANALYTICAL
EPIDEMIOLOGY

8. Analytical studies
 Investigator does not assign the exposure
 Makes careful measurement of patterns of exposure and
disease in populations
 Comparison group
 Make inferences about exposure and disease

9. RESEARCH DESIGNS IN
ANALYTICAL STUDIES
COHORT
STUDY
CROSS
SECTIONAL
STUDY
CASE
CONTROL
STUDY

10. CASE CONTROL COHORT STUDIES
RETROSPECTIVE
Ca Lung patients and non patients
Clarifies if it was smokers who
contributed to high Ca Lung
PROSPECTIVE
Follows a cohort of smokers and non
smokers without Ca Lung
Smokers develop Ca Lung more frequently

11. Case-Control Studies
The observational epidemiologic study of persons with the
disease (or other outcome variable) of interest and a suitable
control (comparison/ reference) group of persons without
the disease.
(Dictionary of Epidemiology: 3rd ed; John M Last. 2000)

12. Case-Control Studies
A case control study involves two populations – cases and controls and
has three distinct features :
 Both exposure and outcome have occurred before the
start of the study.
 The study proceeds backwards from effect to cause.
 It uses a control or comparison group to support or refute
an inference.
(Park’s Textbook of Preventive and Social Medicine – 20th ed; K. Park. 2009)

13. Design of case‐control study
Objective: Test association between cigarette smoking and lung cancer
(Doll and Hill, 1952)
EXPOSED
NON
EXPOSED
EXPOSED
NON
EXPOSED
CASES
(with lung cancer)
CONTROL
Non – cancer patients
Exposure
odds
Exposure
odds
O
D
D
S
R
A
T
I
O
EXPOSED
SMOKER
NON
EXPOSED
NON
SMOKER
OUTCOME
TIME
EXPOSURE

14. ELEMENTS OF A
CASE CONTROL STUDY
1. SELECTION OF CASES
2. SELECTION OF CONTROLS
3. INFORMATION ON EXPOSURE
4. ANALYSIS

15. Selection of cases
• All people in source population who develop the disease of interest
Sample of cases
Independent of the exposure under study
• Clear definition of outcome studied
• Prevalent vs. incident cases
Prevalent cases may be related more to survival with disease
than to development of disease.

16. Sources of cases
• Hospital/clinic based cases
Easier to find
May represent severe cases
• Population based (cancer registry)
- not biased by factors drawing a patient to a
particular hospital

17. Selection of controls
• Represent the distribution of exposure in the
source population of cases
-Selected from the same source population that gives rise to the cases
• Selected independently of their exposure status

18. SELECTION OF
CONTROLS
Population based
• Sampling of the general population
Health care facility based
• Patients with other diseases
Case‐based
• Friends, Neighbourhood

19. MATCHING
Defined as
“ the process by which we select controls in such a way
that they are similar to cases with regard to certain pertinent
selected variable which are known to influence the outcome of
disease and which if not adequately for comparability could distort
or confound the result ”

20. TYPES OF MATCHING
Type 1
Group Matching: assigning cases to subcategories based
on their characteristics like age occupation, etc. and then
establishing appropriate controls.
Type 2
Pair matching: It is finding a control for particular case as
closely resembling as possible except for disease under
study.

21. Selecting good data on exposure
1.Objectively
• Reproducibility of exposure measurement
2. Accurately
• Information reflecting as closely as possible the effect of exposure
3.Precisely
• Quality management in exposure measurement

22. Presentation of the data of a
case‐control study in a 2 x 2 table

23. ODDS RATIO

24. INTERPRETING ODDS RATIO
• OR = 1
-Odds of exposure among cases and controls are same
-Exposure is not associated with disease
• OR > 1
-Odds of exposure among cases are higher than controls
-Exposure is positively associated with disease
• OR < 1
- Odds of exposure among cases are lower than controls
- Exposure is negatively associated with disease

25. Bias in case control studies
BIAS – is a systematic error in design, conduct or analysis of
a study which leads us to an erroneous conclusion.
1.Bias in selection of cases
- selection bias or diagnostic bias
2.Bias in investigating controls.
- recall bias, the controls are less likely to recall exposure variables
than the cases.
-The interview/tests/investigation etc may lack depth in controls
whereas the cases are thoroughly worked up

26. 3. CONFOUNDING BIAS
(distortion of study effect with another effect because of variables
EXTRANEOUS to the exposure affecting the prediction of the disease)
When the disease has multiple risk factors which are related to each other
SOLUTION – MATCHING BETWEEN CASES AND CONTROLS

27. 4. Problems due to over matching :
- This is where a potential confounder ( religion in substance abuse)
is matched among cases and controls. The study thus loses the
power of proving an obvious association.
5.Bias in analysis
- the presence of a confounder is mostly identified at the time of
analysis.
- It is due to non- uniform distribution of confounders.
Solution – Stratification ( limit the size of study and no of confounding
factors)

28. STRENGHTS
 Good for examining rare outcomes or outcomes
with long latency
 Relatively quick to conduct, inexpensive
 Requires comparatively few subjects
 Multiple exposures or risk factors can be
examined.

29. WEAKNESSES
Susceptible to recall bias
Selection of an appropriate comparison group may
be difficult
Rates of disease in exposed and unexposed
individuals cannot be determined

30. SUMMARY
STUDY DESIGNS
• DESIGN
• ELEMENTS
• MATCHING
• ODDS RATIO
• BIAS
• STRENGTHS &
WEAKNESSES
OBSERVATIONAL EXPERIMENTAL
ANALYTICAL DESCRIPTIVE
CASE CONTROL COHORT CROSS SECTIONAL

31. REFERENCES
1) Soben Peter. Essentials of Public Health Dentistry. 5th ed. New Delhi: Arya
Publising House; 2013.
2)Park, Park’s Textbook of Preventive &Social Medicine, 22nd Edition, Jabalpur:
Banarsidas Bhanot,2013.

32. THANK
YOU!