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1. Introduction to Study
designs
Department of Epidemiology and Biostatistics,
MUHAS.

2. Case-control
Cohort
Individuals
Intervention
Retrospective
Prospective
Descriptive
Populations
Analytical
Observational
Case-series
Cross-sectional
Correlational/ecological
Clinical trials
Epidemiological studies

3. Why do epidemiologic studies?
 How big is the problem?
 Are two factors related, (cause and effect)?

4. FELP
Introduction to Descriptive
studies

5. Case-control
Cohort
Individuals
Intervention
Retrospective
Prospective
Descriptive
Populations
Analytical
Observational
Case-series
Cross-sectional
Correlational/ecological
Clinical trials
Epidemiological studies

6. Learning Objectives
When you have completed this session you will be
able to:
 Describe the differences between and descriptive
and analytic studies
 Describe the differences between a case report and
a case series
 Describe the characteristics of an ecological study
 Describe a cross sectional study and explain its
advantages and disadvantages
 Explain the uses of the descriptive study types

7. Descriptive versus Analytical
epidemiology
Descriptive epidemiology:
• generates idea(s) or hypothesis for
associations between risk factor and
illness
Analytical epidemiology:
• uses a comparison group to
establish an association between risk
factors and illness in the two groups

8. Descriptive Studies
 The most frequent design strategy found in
the epidemiologic literature
 Used to describe the distribution of disease
by time, place, person and assoc. factors
 Describing these factors does not link them
 However we can identify unusual distributions
or correlations
 Useful for Hypothesis generation and health
planning

9. Using Descriptive Studies for
Hypothesis Formulation
 Person – “Who is getting the disease?”
Age, race, sex
 Place – “Where are the rates of disease
highest and lowest?”
 Time – “ When does the disease occur
commonly or rarely?” and “ Is the frequency
of the disease now different from the
corresponding frequency in the past?”

10. Person
Place
Time
Cases
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10
0
200
400
600
800
1000
1200
0-4 '5-14 '15-
44
'45-
64
'64+
Age Group
Descriptive Epidemiology
Who? Where? When?

11. Categories of Descriptive Studies
 Populations (correlational or ecological studies)
 Individuals
 Case reports
 Case series
 Cross-sectional surveys

12. Correlational or Ecological Studies
Based on aggregate measures of exposure and
outcome from several populations.
The population is the unit of observation available
for study.
Exposures:
- What percent of a population smokes?
- What percent of 1-year old children are
vaccinated against measles?
- What percent of a population has piped water?

13. Correlational or Ecological Studies
Outcomes:
- What percentage of a population died from MI?
- What percentage of children had measles last
year?
- What percentage of population had episodes of
diarrhea?

14. Correlational or Ecological Studies
Advantages
-Easy to do
-Use available data (“administrative” or other
aggregate data)
-Can be done in population with widely differing
characteistics
-Generate hypotheses for additional study

15. Correlational or Ecological Studies
Disadvantages
-Unable to examine data for individuals; data on
exposure and data on outcome are collected
independently
-No assurance that persons with exposure (risk
factor) of interest are the same ones with the
outcome (disease) of interest
-Association at the aggregate level may not reflect
association at the individual level - the ecologic
fallacy
-Unable to adjust for potential confounding factors.
-Poor correlation doesn’t mean no association

16. Descriptive Studies
 Populations (correlational or ecological studies)
 Individuals
 Case reports
 Case series
 Cross-sectional surveys

17. Case reports
The individual is the unit of observation
available for study.
Clinical case with “unusual” clinical picture
May suggest an etiological association

18. Case series
First case report may stimulate compilation
of additional case reports….a case series
(e.g. occurrence of Pneumocystis carinii
among a group of young, homosexual men
with no history of immune deficiency)

19. Case reports or Case series
Advantages:
Use available clinical data
Detailed individual data
Suggest need for investigation (hypothesis
generation)
Disadvantages:
May reflect experience of one person or one
clinician
No explicit comparison group

20. Descriptive Studies
 Populations (correlational or ecological studies)
 Individuals
 Case reports
 Case series
 Cross-sectional surveys

21. Design of cross-sectional study
Defined population
Exposed: Have
disease
Exposed; Do
not have
disease
Not exposed;
Have disease
Not exposed:
Do not have
disease
Gather data on exposure and disease

22. Cross Sectional Study
Exposure
Occurrence ?
Time of studyDisease
Occurrence ?
+
-
+ -
ill
exp
Selection of
population

23. Cross-sectional study
 Also known as “prevalence” study
Design
Identify research question
Specify target and accessible population
Sample the population
Measure variables of interest (usually a survey)
Thus: participants classified by exposure and disease status
at the same time. This allows identification of prevalent
cases, calculation of prevalence rates.

24. Cross-sectional surveys
 Measure variable(s) at a single time:
 prevalence studies (“snapshot”)
 useful for events/diseases when
 chronic
 common
 non-fatal
 temporal relationship cannot be established unless
exposure permanent
 If exposure unalterable, cross-sectional survey ≈
analytical study

25. Cross-sectional study
 Strengths/Advantages
 Can study entire populations or a representative
sample
 Provide estimates of prevalence of all factors
measured
 Standardized data collection tool.
 May be quick and inexpensive
 Valuable in assessing health status and health
care needs of a population
 Can be repeated to get trend data
 Help in hypothesis generation

26. Cross-sectional study
 Weaknesses/disadvantages
 Information on disease and exposure collected
simultaneously, therefore difficulty establishing
that cause antedated effect.
 Use of prevalent cases means data reflects
determinants of survival as well as etiology
 Cases may be misclassified due to changes in
exposure or poor memory of earlier exposures
 Not good for rare diseases or exposures
 Cannot measure risk
 Cant study temporal relationship

27. Data analysis and interpretation of
descriptive studies
 Cross-sectional studies and surveys are
measuring prevalence
 Well-suited for describing variables and their
distributions – Eg. Kenya Demographic and
Health Survey

28. Design of a cross-sectional study
Disease No Disease
Job A
Job B
a b
c d
Prevalence of disease in exposed (Job A) = a/a+b
Prevalence of disease in unexposed (Job B) = c/c+d

29. Presentation of Cross Sectional Data
2x2 table
Exposed
Not exposed
ill not ill
a
c
b
d
Prevalence in exposed (Pe+) = a/
(a+b)
Prevalence in non-exposed (Pe-) = c/
(c+d)
Prevalence ratio = a/(a+b) / c/(c+d)

30. Job A (hazardous)
80 healthy 80 well
100 workers
20 resp 10 ill
symptoms
Job B (non- hazardous)
95 healthy 80 well
100 workers
5 ill 10 ill
Prevalence ill job A: 20/100 = 20%
Prevalence ill job B: 5/100 = 4%
Prevalence ratio: 5
Cross-sectional surveys

31. Association Measures in Cross
Sectional Studies
Example: Corporal hygiene and trachoma
Poor Hygiene Trachoma Healthy Total
Yes 54 337 391
No 50 1 459 1 509
Total 104 1 796 1 900
Prevalence ratio = 13.8 / 3.3 = 4.2
Prevalence
13.8 %
3.3 %
% exp 51.9% 18.8%

32. Recap
Now that you have completed this session you will be
able to:
 Describe the differences between and descriptive
and analytic studies
 Describe the differences between a case report and
a case series
 Describe the characteristics of an ecological study
 Describe a cross sectional study and explain its
advantages and disadvantages
 Explain the uses of the descriptive study types

33. What is the prevalence of trachoma, and is it
associated with poor hygiene?
 Population of 1900
Poor hygiene Trachoma
Yes No
Yes 54 337
No 50 1459

34. Exercise
Calculate Prevalence of Chlamydia in this
population of STI patients.
Calculate prevalence ratio for Chlamydia
among OCP users vs. non-users.