1. Lecture notes on epidemiological studies for undergraduates

2. Professor of epidemiology and health care
Dr Omran S Habib
Professor of epidemiology and health care
Department of Community Medicine
College of Medicine
University of Basrah
Mobile:

3. Classification of Epidemiological studies

4. 1. Observational:
a. Descriptive- observe and describe. No controls no intervention.
b. Analytical- observe (measure) and interpret. Controls are used but no intervention.

5. 2. Interventional (experimental)- Interfere, observes and analyze (interpret)
3. Evaluational: Can use combination of observational descriptive, analytical and interventional approaches. Observational descriptive studies

6. 1. Observational descriptive epidemiological studies(surveys or household surveys)
These surveys are specially designed and carried out for answering specific questions. They include different types of epidemiological studies but two main types are commonly used.

7. Cross-sectional surveys or studies.
These are based on a single observation usually carried out in a short time and characterized by :
a. They usually measure prevalence of disease
b. Based on aggregated evidence, they suggest hypotheses.
c. They are not useful for diseases of short duration. A single observation may miss cases.

8. d. Their results are difficult to interpret because of seasonal variation and cohort effect.
e. They are relatively quicker and cheaper to do compared to follow up studies.
f. They can be modified to estimate incidence of disease and to test hypotheses. A case-control design can also be made within the context of a cross-sectional study.

9. Longitudinal or follow up surveys or studies.
These are based on repeated observation of the study population over a defined period of time. They start with a base-line data provided by initial cross-sectional study.

10. a. They measure incidence of disease or related outcome.
b. Based on aggregated evidence, they suggest hypotheses.
c. They are relatively more expensive and difficult to organize.
d. They are not useful for diseases of rare occurrence.
e. The results are easier to interpret.
f. They can be useful to determine seasonal variation of disease.

11. Both cross-sectional and longitudinal studies can be population-based (household (surveys

12. 2. Observational analytical studies
Definition of basic terms
Risk: A probability that an individual will become ill or die within a specified period of time or age. It is used to denote incidence rate (risk of acquiring disease) or mortality rate (risk of dying).

13. Risk factor: It can be defined as:
a. Risk marker. An attribute or an exposure that is associated with an increased risk of disease or other specific outcome.
b. Determinant. An attribute or exposure that increases the risk of disease or other specific outcome among population groups.

14. Risk factors might be
a.. Modifiable risk factors. Changeable by intervention like body weight
d. Non-modifiable risk factors: Not changeable like gender (sex)
Relative risk or Risk Ratio (RR): is a measure of strength of association between an exposure (risk factor) and an outcome (disease).

15. Incidence rate among exposed
Relative risk (RR) =
Incidence rate among non exposed
RR =1 No association
RR >1 Positive association (Risk factor)
RR<1 Negative association (protective factor)

16. Attributable risk (AR)=
Attributable risk (AR): It refers to the fraction of the incidence rate of the disease that can be attributed to the exposure to the risk factor. It is calculated by the following formula:
Attributable risk (AR)=
IR among exposed – IR among non exposed

17. IR among exposed – IR among non exposed
% reduction = X 100
IR among exposed

18. Association (going together or opposite to each other): A statistical/ quantitative (relationship) between two or more variables. When variables tend to occur together more frequently than could be explained by chance, they are described as being associated with each other.

19. Types of statistical association
a. Non causal when the apparent association is due to confounding process, when a third factor is related both to the risk factor (the cause) and the outcome or effect (the disease).

20. b. Causal which is either:
direct (A B)
or indirect (A   B C)
The factor B is an intervening cause between the factor A and the outcome C. More than one intervening factor may exist in any causal pathway.

21. Causal association
A. Epidemiological criteria (Bradford Hill criteria):
1. Strength of association.
     2. Dose-response relationship.
     3. Time sequence.
     4. Experimental evidence.
5. Consistency.
6. Coherence/ Biological plausibility
7. Specificity.
8. Analogy

22. B. Biological criteria ( Koch's Postulates)
B. Biological criteria ( Koch's Postulates). Applicable mainly to  biological agents.
1. Agent is regularly found in the lesion of each case
2. Agent is isolated in pure culture.
3. Agent causes similar disease in experimental animals
4. Agent is recovered from lesions in experimental animal.

23. They attempt to answer the questions Why? And How?
ANALYTICAL STUDIES
They attempt to answer the questions Why? And How?
1. They test hypothesis
2. They help in determination of risk factors (causes)
3. They involve the use of comparison or control groups
4. They need sound study design and high epidemiological expertise.

24. COHORT STUDIES
A cohort is a group of individuals who share common characteristics or experience, e.g., birth cohort which represents all live births in one year.

25. In cohort studies
1. Select people who are free from the disease.
2. At least two groups are used (exposed versus non-    exposed)
3. The two groups are followed up for a period of time)
4. Events (new cases or deaths ) are recorded.
5. Results are analyzed to test the hypothesis.

26. Example
A study was carried out to ascertain the relationship of parental smoking to the risk of ARI among children aged <5 years. A total of 800 children of smoking parents and 1200 of nonsmoking parents were followed up for six months. During the follow up period, 592 of the first group and 636 of the second group developed at least one attack of ARI.

27. The analysis Tabulate the data Calculate the incidence rates
Calculate the relative risk
Calculate the attributable risk
Perform a statistical test.

28. Note: In case of multiple exposures (the disease is related to multiple risk factors) a more sophisticated analysis is carried out to determine the relative effect or contribution of each risk factor. Logistic regression analysis and stepwise multiple regression analyses are commonly used. Computerized statistical packages (such as SPSS) are available for such sophisticated analyses.

29. CASE-CONTROL STUDIES In case-control studies:
1. Both exposure and outcome or disease have occurred before the start  of the  study.
2. The study proceeds backwards from outcome to cause (retrospective).
3. Controls are used to support or refute any inference.

30.     The basic design steps
1. Selection of cases (persons with definite disease) and controls (persons definitely free from the disease at the time of the study).
2. Matching for known confounding variables (at least age and sex).
3. Measurement of past exposure in both groups.
4. Analysis and interpretation.

31. Example
To illustrate the study design, we identify a number of children who are suffering from ARI (say pneumonia). Suppose we identified 240 with ARI 380 of children matched for age and sex but free from ARI. Suppose we found that the parents of 170 cases and 200 controls were smokers.

32. The analysis and interpretation 1. Tabulation of the data
Total
Children without pneumonia
Children with pneumonia
History of smoking
370
200
170
Positive
250
180 70
Negative
620
380
240

33. 2. Calculation of the % of smokers (exposed) among parents of cases and controls.      
3. Calculation of the % of smokers among parents of controls

34. Cases exposed X Controls not exposed
4. Measurement of the strength of association between parental smoking and acute respiratory infection. This is achieved by calculating a proxy measure to the relative risk. This measure is called the Odds ratio.
Cases exposed X Controls not exposed
The Odds Ratio =
Cases not exposed X Controls exposed

35. 5. Perform a suitable statistical test to ascertain any significant association.
6. Calculation of the attributable risk
b ( r - 1)
    Attributable risk =
b ( r – 1 ) + 1

36. Where
r = Odds ratio
b = the proportion of people in the general population with the risk factor.

37. SOURCES OF CONTROLS IN ANALTICAL STUDIES
In case control studies, the main sources are:
1. The total population in a given area, on the assumption that we know the extent of exposure in the general population. Otherwise, a population-based sample of controls can be drawn. This is the best source of controls but probably difficult in logistics terms.

38. 2. Relatives and neighbours
2. Relatives and neighbours. This is useful to control for genetics and  immediate environment
3. Hospital patients other than those with the disease under study.
4. Associates of cases in place of residence, schools, place of work.

39. In cohort studies the main sources are:
1. Built in comparative cohorts as for example in studying the relationship of lung cancer to smoking, people may be categorized into subgroups of heavy smokers, moderate smokers, light smokers and nonsmokers. Thus we have four (heavy, moderate, light and non) instead of just two (smokers versus non-smokers).

40. 2. Relatives and neighbors.
3. The total population provided that the level of exposure is ascertained at population level at the start of the study.
4. Special occupational groups.

41. Questions 1. What are the main differences between case-control and cohort studies? 2. Which of these two designs fits Clinical controlled trials? 3. What types of bias might be encountered in each of these two desins?