Observational study is divided into descriptive and analytical studies. Non-experimental Observational because there is no individual intervention Treatment and exposures occur in a “non-controlled” environment Individuals can be observed prospectively or retrospectively COHORT STUDY- an “observational” design comparing individuals with a known risk factor or exposure with others without the risk factor or exposure. looking for a difference in the risk (incidence) of a disease over time. best observational design data usually collected prospectively (some retrospective) CASE CONTROL - EFFECT TO CAUSE Retrospective When disease is rare .

1. ANALYTICAL STUDY
DESIGNS
- Dr. ARYASREE L.

2. Overview
1. Cohort study
2. Case control study

4. Observational Studies
•Non-experimental
•Observational because there is no individual
intervention
•Treatment and exposures occur in a “non-
controlled” environment
•Individuals can be observed prospectively or
retrospectively

5. Figure 9-3 Selection of study groups in experimental and observational
epidemiologic studies.

6. Basic Questions in Analytic Epidemiology
Look to link exposure and disease
1. What is the exposure?
2. Who are the exposed?
3. What are the potential health effects?
4. What approach will you take to study
the relationship between exposure and
effect?

7. COHORT STUDY

8. Cohort Studies
 an “observational” design comparing
individuals with a known risk factor or exposure
with others without the risk factor or exposure.
looking for a difference in the risk (incidence)
of a disease over time.
best observational design
data usually collected prospectively (some
retrospective)

9. Figure 9-4 Design of a cohort study beginning with exposed and nonexposed groups.
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Design of cohort study

10. Figure 9-5 Design of a cohort study beginning with a defined population.
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11. Time
Study begins here
Study
Population
Free of
Disease
Factor
Present
Factor
Absent
Disease
No disease
Disease
No disease
Present
Future

12. •Prospective Study - looks forward, looks
to the future, examines future events,
follows a condition, concern or disease
into the future
time
Study begins here

13. •Retrospective Study - “to look back”,
looks back in time to study events that
have already occurred
time
Study begins here

14. Figure 9-7 Time frame for a hypothetical retrospective cohort study begun in 2008.
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15. Figure 9-8 Time frames for a hypothetical prospective cohort study and a hypothetical retrospective cohort study begun in 2008.
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16. The Framingham study

17. Aniline dyes and urinary bladder cancer

18. Elements of cohort study
1. Selection of study populations
2. Gathering baseline information
3. Follow up
4. Analysis

19. 1. Selection of study population
• General population
• Special exposure cohorts

20. 2. Gathering baseline information
• Valid assessment of exposure status
• Exclude who are having disease of interest
• Data on other risk factors

21. 3. Choice of comparison group
• Internal comparison group
• External comparison group

22. 4. Follow up
• Uniform and complete follow up
• Complete assessment of exposures and outcomes
• Standardized diagnosis of outcomes

23. Presentation of the data in a cohort study in a 2x2
table

24. Relative Risk
• The relative risk can be defined as the probability of an
event (developing a disease) occurring in exposed people
compared with the probability of the event in unexposed
people, or as the ratio of these two probabilities.
• RR= Risk in exposed
• Risk in unexposed

26. Interpreting relative risk of a disease
If RR =1 Risk in exposed equal to risk in
unexposed(no association)
If RR >1 Risk in exposed greater than risk in
unexposed(positive association;possibly
causal)
If RR < 1 Risk in exposed less than risk in
unexposed (negative association;
possibly protective)

27. Cohort study strengths and weaknesses
Strengths weaknesses
Allows calculation of incidence Long calendar time
Examine multiple outcomes for a given
exposure
Not good for rare diseases
Clarity of temporal sequence Not good for diseases with a long latency
Good for investigating rare exposures Differential loss to follow up can
introduce bias

28. Case control

29. Elements of case control study
1. Selection of cases
2. Selection of controls
3. Information on exposure
4. Analysis

30. 1. Selection of cases
• All people in source population who develop the disease of
interest
• Clear definition of outcome studied
• Prevalent vs incident cases

31. Sources of cases
• Hospital /clinic based cases
• Population based

32. 2. Selection of controls
• Population based
• Health care facility based
• Case based

33. 3. Collecting good data on exposure
• Objectively – reproducibility of exposure measurement
• Accurately – information reflecting as closely as possible the
effect of exposure
• Precisely – Quality management in exposure measurement

34. Presentation of the data of a case control study in
a 2x2 table

35. Odds ratio
• An odds ratio (OR) is a measure of association between an
exposure and an outcome.
• The OR represents the odds that an outcome will occur given
a particular exposure, compared to the odds of the outcome
occurring in the absence of that exposure.

37. 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

38. Case control study strengths and weaknesses
STRENGTHS WEAKNESSES
Good for rare outcomes Susceptible to recall bias
Relatively quick to conduct Selection of an appropriate comparison
group may be difficult
Requires comparatively few subjects Rates of disease in exposed and
unexposed individuals cannot be
determined
Multiple exposures or risk factors can be
examined

39. Example 1
Thyroid hormones, namely triiodothyronine (Free T3), thyroxine (Free
T4) and thyroid stimulating hormone (TSH) were evaluated at the time
of diagnosis of preeclampsia in 82 pregnant women and equal number
of matched controls. (Kumar et al.)
Case Control

40. Example 2
46,112 never users of oral contraception and women 819,175 ever users
were followed for 39 years to ascertain mortality risk. (Hannaford et al.)
Cohort

41. Example 3
275 women attending the antenatal clinic at Kilifi district hospital,
Kenya, were recruited in November 1993 and tested for malaria in order
to calculate the prevalence. (Shulman et al.)
Cross-Sectional

42. Example 4
270 wards randomised to 3 groups of 90 each for women to receive
weekly a single oral supplement of placebo, vitamin A or â carotene for
over 3.5 years and followed to determine pregnancy-related mortality.
(West et al.)
Clinical Trial

43. Example 5
A survey among second trimester pregnant women 18-44 took place
between April 2003 and November 2003 to determine the prevalence of
anemia and hookworm. (Larocque et al.)
Cross-Sectional

44. Example 6
431 women were enrolled in a study within 21 days of conception and
monitored throughout pregnancy to determine caffeine exposure and
pregnancy outcome. (Mills et al.)
Cohort

45. References
1. BCBR lecture 6
2. Gordis epidemiology Edition 6
3. National library of medicine

46. THANKYOU