1. Study Designs Hale Arık Taşyıkan, MD, MPH, Assist. Prof.
Department of Public Health
Yeditepe University

2. Types of study design Observational Interventional Descriptive
Case reports / series
Cross-sectional
Clinical Trial
Community Trial
Analytical
Cross-sectional
Case – control
Cohort

3. Objectives of Descriptive Studies
To permit evaluation of trends in health and disease and comparisons among countries and subgroups within countries; this objective includes monitoring of known diseases as well as the identification of emerging problems
To provide a basis for planning, provision, and evaluation of health services
To identify problems to be studied by analytic methods and suggest areas that may be fruitful for investigation
Yehuda Neumark / 2007 / Lecture notes

4. CROSS-SECTIONAL STUDIES

5. Cross-Sectional Study
Cross-sectional Survey
Prevalence Study
Baseline Survey

6. Gather data on exposure and diseases
Outcome +
Exposure +
Outcome -
TARGET POPULATION (UNIVERSE)
SAMPLE
Outcome +
Exposure -
Outcome -
Gather data on exposure and diseases

7. 2 * 2 table
Disease
No Disease a b c d
Exposed
Not Exposed

8. Design of a cross-sectional study
Coronary Heart Disease
Disease
No disease
Total n
Male 14 77 91
Female 10
166
176 24
243
267
R Uçku / HASAT / 2007

9. 24 P (prevalence) = 267 14 P (exposure+) = 91 10 176 P (exposure -) =
= %9.0 14 91
P (exposure+) =
=%15.4 10
176
P (exposure -) =
= %5.7

10. Design of a cross-sectional study
Coronary Heart Disease
Disease
No disease
Total n %
Male 14
15.4 77
84.6 91
100.0
Female 10
5.7
166
94.3
176 24
9.0
243
91.0
267
R Uçku / HASAT / 2007

11. Measures of Association
Question:
Is there an excess risk associated with a given exposure?
Objective:
To determine whether certain exposure is associated with a given disease/outcome
Methodology:
Cohort
Case-control/Cross-sectional

12. Odds Ratio
Odds:
A way of expressing the chance of an event, by dividing the number of individuals in a sample who experienced the event by the number who did not.
If 10 individuals out of 100 individuals develop tuberculosis, the odds of developing tuberculosis in that population is 10/90 = 0.11
Odds ratio (OR) - the ratio of the odds of an event in one group to the odds of an event in another group

13. Design of a cross-sectional study
Coronary Heart Disease
Disease
No disease
Total n
Male 14 77 91
Female 10
166
176 24
243
267
R Uçku / HASAT / 2007

14. 2 * 2 table !!!!! Disease No Disease 14 77 10 166 Exposed Not Exposed
Odds=14/10
Odds=77/166
Odds Ratio= Odds 1 / Odds 2 = 3.02

15. Advantages (Cross-sectional study)
Often most practical and feasible
Relatively inexpensive and quick
Carried out in more natural settings
Involves a sample of a dynamic population
Efficient for generating new hypotheses
Efficient for describing population characteristics
Provides outcome prevalence estimate
Repeat cross-sectional surveys are useful for assessing the impact of a service
Yehuda Neumark / 2007 / Lecture notes

16. Disadvantages (Cross-sectional study)
NOT useful for determining causal effects
NOT efficient for studying rare outcomes or those of short-duration
CANNOT provide direct estimates of risk
DIFFICULT to interpret temporality between exposure and outcome
Yehuda Neumark / 2007 / Lecture notes

17. Example:
In the 1940s, Sir Norman Gregg, an Australian ophtalmologist, observed a number of infants and young children in his ophtalmology practice who presented with an unusual form of cataract. Gregg noted that these children had been in utero during the time of a rubella outbreak. He suggested that there was an association between prenatal rubella exposure and the development of the unusual cataracts. Keep in mind that at that time there was no knowledge that a virus could be teratogenic. Thus, he proposed his hypothesis solely on the basis of observational data, the equivalent of data from ambulatory or bedside practice today.
Epidemiology, Third Edition, Leon Gordis

18. Example :
Let us suppose that Greg had observed that 90% of these infants had been in utero during the rubella outbreak. Would he have been justified in concluding that rubella was associated with the cataracts?
Comparison is an essential component of epidemiologic investigation.
Epidemiology, Third Edition, Leon Gordis

19. Objectives of Analytical Studies
To test hypotheses or detect associations
Identify factors that explain higher rates of CVD among men
Yehuda Neumark / 2007 / Lecture notes

20. CASE-CONTROL STUDIES

21. CASE – CONTROL STUDY DESIGN
Directionality of the study
Exposure +
Cases
Exposure -
Exposure +
Controls
Exposure -

22. 2 * 2 table
Disease
No Disease a b c d
Exposed
Not Exposed

23. Design of a case-control study
CHD Cases
Controls
112
176 88
224
Smoker
Non-smoker
Total
% Smoking cigarettes
56.0%
44.0%

24. Selection of Cases Sources: Hospital patients
Patients in physicians’ practices
Clinic patients
Registries of patients with certain diseases (cancer registries)
The criteria for eligibility is very important.
Incident or prevalent cases ????

25. Selection of Controls Sources: Hospitalized patients
Non-hospitalized patients living in the community
Is the level of exposure observed in the controls really the level expected in the population in which the study was carried out?

26. Matching
The process of selecting the controls so that they are similar to the cases in certain characteristics, such as age, race, gender, socioeconomic status and occupation.
Group matching
Individual matching (matched pairs)
We will not be able to ask whether cases differ from controls in the prevalence of that factor. (marital status – breast cancer)

27. Design of a case-control study
CHD Cases
Controls
112
176 88
224
Smoker
Non-smoker
Odds of being smoker =
1.27
0.79
Odds Ratio (OR) =
1.27 / 0.79 = 1.61

28. Advantages (Case-control study)
The first step when searching for a cause of an adverse health outcome
Cheaper and quicker than cohort studies
It is valuable when the disease being investigated is rare, and the disease duration is long.
Can easily study multiple exposures

29. Disadvantages (Case-control study)
Inefficient for rare exposures
Not well suited to study multiple outcomes
Time sequence of exposure and outcome can be unclear
Doesn’t provide data on absolute risk
Yehuda Neumark / 2007 / Lecture notes

30. COHORT STUDIES

31. Selection of Study Populations
Select groups on the basis of whether or not they were exposed (e.g., occupationally exposed cohorts)
Select a defined population before their exposures are identified, then seperate the population into exposed and nonexposed groups (e.g. Framingham study)

32. COHORT STUDY DESIGN Directionality of the study Exposed Not Exposed
Disease +
Disease -
Exposed
Not Exposed

33. 2 * 2 table
Disease
No Disease a b c d
Exposed
Not Exposed

34. Design of a cohort study
CHD
No CHD
Total
Incidence per 100 84
2916 87
4913
Smoker
3000
2.80%
Non-smoker
5000
1.74%

35. Examples of Cohort Studies
Example 1: The Framingham Study
A cohort study of cardiovascular disease
Was begun in 1948
Consisted of 5127 men and women who were between 30 and 62 years of age at the time of study entry and were free of cardiovascular disease at that time.

36. Examples of Cohort Studies
Example 1: The Framingham Study
Many «exposures» were defined;
Smoking
Obesity
Elevated blood pressure
Elevated cholesterol levels
Low levels of physical activity and other factors

37. Examples of Cohort Studies
Example 1: The Framingham Study
New coronary events were identified by examining the study population every 2 years and by daily surveillance of hospitalizations at the only hospital in Framingham

38. Examples of Cohort Studies
Example 2: Incidence of Breast Cancer and Progesterone Deficiency
Observation: Late age at first pregnancy increased risk of breast cancer

39. Example 2: Incidence of Breast Cancer and Progesterone Deficiency
Patients of Johns Hopkins Hospital Infertility Clinic
Hormonal
Abnormalities
No Hormonal
Abnormalities
Develop
Cancer
Do not
Develop
Cancer
Do not
1978 -

40. Relative Risk What is risk?
Probability of developing a disease over a defined period of time.
If 10 individuals out of 100 individuals free of tuberculosis at the start of the period, develop tuberculosis at the end of the period, the risk of developing tuberculosis in that population is 10/100 = 10%
Relative risk: The ratio of two incidence rates.

41. Study design- Prospective cohort
tbc
Low education
Study population
Healthy
n=10
tbc
High Education
Healthy
Beginning of the study
n=260
The direction of the study

42. Relative Risk of TB A B C D Outcome Exposure Tbc + Tbc - Low education
High Education C D
A+B
200 50
150
C+D
260 10
250
A+B+C+D
460
A+C 60
B+D 400

43. RR of tbc Probability of developing TB among low education +
Probability of developing TB among high education +
Risk of tbc among low education + = 50/200= 25%
Risk of tbc among high education = 10/260 = 3.8%
Relative risk = 25 / 3.8 = 6.5

44. Interpreting Relative Risks
RR = 1
Risk in exposed is equal to the risk in the unexposed (no association)
RR > 1
Risk in the exposed is greater than the risk in the unexposed (+ association)
RR < 1
Risk in exposed is less than the risk in the unexposed (- association)

45. Advantages (Cohort study)
Relative risk can be calculated as the measure of association
Easy to establish the temporal relationship between exposure and disease
Possible to study associations of an exposure with several diseases
It is the best design when exposure is rare and disease is frequent among exposed

46. Disadvantages (Cohort study)
Time required for the study is generally long
Expensive
Population size needed is relatively large when compared to case – control studies

47. THANK YOU