classification of epidemiological methods, descriptive epidemiology.
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Classification of Epidemiological Methods & Descriptive Epidemiology
Park's Textbook of Preventive and Social Medicine
CLASSIFICATION OF EPIDEMIOLOGICAL METHODS
Epidemiological studies are broadly classified into two major categories:
A. Observational Studies
The investigator does not intervene - natural exposure is simply observed.
- Descriptive Studies
- Case reports / case series
- Ecological (correlational) studies
- Cross-sectional surveys
- Analytical Studies (test hypotheses formulated by descriptive studies)
- Case-Control Studies (retrospective): Start from disease, look backward to exposure
- Cohort Studies (prospective): Start from exposure, follow forward to disease outcome
B. Experimental (Interventional) Studies
The investigator controls exposure or intervention.
- Randomized Controlled Trials (RCTs) - clinical trials
- Field trials
- Community trials
The fundamental distinction: observational studies observe the allocation of exposures; experimental studies assign them. Analytical studies focus on individuals, whereas descriptive studies examine populations.
DESCRIPTIVE EPIDEMIOLOGY
Definition
The primary objective of descriptive epidemiology is to describe the occurrence and distribution of disease (or health-related events or characteristics within populations) by time, place and person, and to identify those characteristics associated with the presence or absence of disease in individuals.
Descriptive studies are usually the first phase of an epidemiological investigation. They ask:
- When is the disease occurring? - Time distribution
- Where is it occurring? - Place distribution
- Who is getting the disease? - Person distribution
Procedures in Descriptive Studies (Table 8, Park)
| Step | Procedure |
|---|---|
| 1 | Defining the population to be studied |
| 2 | Defining the disease under study |
| 3 | Describing the disease by: time, place, person |
| 4 | Measurement of disease |
| 5 | Comparing with known indices |
| 6 | Formulation of an aetiological hypothesis |
Characteristics Examined in Descriptive Studies (Table 9, Park)
| Time | Place | Person |
|---|---|---|
| Year, season, month, week | Climatic zones, country, region | Age, sex, marital state |
| Day, hour of onset | Urban/rural, local community | Occupation, social status, education |
| Duration | Towns, cities, institutions | Birth order, family size, height, weight, blood pressure, personal habits |
Note: This grouping by time/place/person is an initial separation of variables - NOT a classification of causal factors.
1. TIME DISTRIBUTION
Disease occurrence can be described by week, month, year, day of week, hour of onset, etc. Time analysis asks whether the disease is seasonal, periodic, or following a secular trend.
Three Kinds of Time Fluctuations:
I. Short-term Fluctuations
Best known example: Epidemic - "the occurrence in a community or region of cases of an illness or other health-related events clearly in excess of normal expectancy."
Types of Epidemics:
A. Common-Source Epidemics
- (a) Point-source (single exposure): Exposure is brief and essentially simultaneous. All cases develop within one incubation period. Epidemic curve rises and falls rapidly, no secondary waves (e.g., food poisoning outbreak). The "median incubation period" is the time for 50% of cases to occur after exposure.
- (b) Continuous/repeated exposure: Prolonged or intermittent exposure from the same source - no explosive rise. Example: contaminated well, nationally distributed vaccine.
B. Propagated Epidemics
- Person-to-person spread. The epidemic curve shows successive waves, each higher than the last, at intervals of one incubation period.
C. Mixed Epidemics
- Elements of both common-source and propagated spread.
The epidemic curve:
- Suggests a time relationship with exposure to a suspected source
- Indicates a cyclical or seasonal pattern of a particular infection
- Helps distinguish common-source vs. propagated spread
II. Periodic Fluctuations
- Seasonal fluctuations (e.g., influenza in winter) and cyclical changes (e.g., measles peaks every 2-3 years)
III. Long-term (Secular) Trends
- Changes over years or decades (e.g., decline of tuberculosis mortality before antibiotics)
2. PLACE DISTRIBUTION
Geographic analysis provides important clues about disease causation. Geographic variation may be classified as:
- a. International variations - e.g., gastric cancer very common in Japan but rare in USA; breast cancer highest in Western countries, lowest in Japan
- b. National variations - e.g., distribution of endemic goitre, fluorosis, leprosy varies within India
- c. Rural-urban variations
- d. Local distributions
Migrant Studies are a special tool - they help distinguish genetic vs. environmental factors:
- If migrant disease rates resemble the country of adoption → environmental explanation likely
- If migrant rates resemble the country of origin → genetic factors likely
Example: Japanese immigrants to the USA developed colon cancer rates resembling Americans over generations, suggesting an environmental/dietary cause.
3. PERSON DISTRIBUTION
Disease is characterized by defining who develops it, using host factors:
- (a) Age: Most strongly related to disease. Examples: measles in childhood, cancer in middle age, atherosclerosis in old age.
- (b) Sex: Some diseases differ markedly by sex (e.g., gout more in males; lupus more in females).
- (c) Occupation: Certain jobs confer specific disease risks (asbestosis, coal worker's pneumoconiosis).
- (d) Marital status
- (e) Social class / education
- (f) Personal habits: Smoking, diet, alcohol use
- (g) Blood pressure, blood cholesterol
6. Formulation of an Aetiological Hypothesis
By studying time-place-person distributions, descriptive epidemiology generates hypotheses for testing. A well-formed hypothesis should specify:
- The population to whom it applies
- The specific cause being considered
- The expected outcome (disease)
- The dose-response relationship
- The time-response relationship
Example: Rather than "cigarette smoking causes lung cancer" (incomplete), a proper hypothesis is: "The smoking of 30-40 cigarettes per day causes lung cancer in 10% of smokers after 20 years of exposure."
Uses of Descriptive Epidemiology
- Provide data on the magnitude of disease load (morbidity, mortality rates) in the community
- Provide clues to disease aetiology and help formulate aetiological hypotheses
- Provide background data for planning, organizing, and evaluating preventive and curative services
- Contribute to research by describing variations in disease occurrence by time, place, and person
- Once completed, hypotheses formulated can be tested using analytical epidemiology
Relationship Between Descriptive and Analytical Epidemiology
| Feature | Descriptive | Analytical |
|---|---|---|
| Unit of study | Population | Individual |
| Aim | Formulate hypothesis | Test hypothesis |
| Variables | Time, place, person | Exposure vs. disease |
| Study types | Surveys, ecological studies | Case-control, cohort |
| Direction | No direction (cross-sectional) | Retrospective or prospective |
- Park's Textbook of Preventive and Social Medicine, pp. 81-85
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