**Analytical Epidemiology Studies**

Concept

Analytical epidemiology studies (AES) are a type of research aimed at identifying the relationship between risk factors (RF) and diseases. The main characteristic of AES is that there is always a comparison group to compare the disease incidence between groups.

Applications

AES provides scientific basis for disease prevention, control and health insurance.

Classification

There are two types of analytical epidemiology studies:

• Observational studies:

• Case-control studies

• Cohort studies

• Interventional studies:

• Clinical trials

• Preventive studies

• Community studies

Observational Studies

#### Case-control studies

Example: John Snow’s cholera study

Advantages:

• Suitable for diseases with long incubation periods, rare diseases, diseases with multiple risk factors

• Can quickly identify potential risk factors

Disadvantages:

• Ineffective in rare treatments, unless the attributable risk percentage (AR%) is high

• Does not directly calculate new disease incidence

• Difficult to determine the time relationship between risk factors and disease

• There may be multiple systematic errors, selection bias and recall bias

Criteria for selecting the case group:

• Source: Hospital-based or community-based

Criteria for selecting the control group:

• Source: From hospitals, from the community or having a contrasting relationship with the case group

Case/control ratio:

• In rare diseases: ≤ 4/1

• No ideal number for all cases

Challenges in selecting the control group:

• It is often difficult to achieve an ideal so it is necessary to:

• Choose multiple control groups

• Conduct multiple studies

Criteria for selecting the case group:

• Diagnosis must be distinct to select a homogeneous case group

#### Cohort studies

Example: Doll and Hill’s study on smoking and lung cancer

Advantages:

• The time-disease relationship is clearly established

• Suitable for studying the consequences of exposure

• Allows for accurate sample size calculation, identifying multiple outcomes for a single exposure risk factor

Disadvantages:

• Time-consuming and costly

• Easy to lose track

Classification of cohort studies:

• Prospective cohort studies:

• Example: The Nurses’ Health Study (research on risk factors and chronic diseases in women)

• Retrospective cohort studies:

• Often used in occupational disease research

• Example: Lung cancer deaths and asbestos exposure by Enterline

• Retrospective and prospective cohort studies:

• Example: Consequences of Dioxin

Cohort study nested case-control study:

• Example: Identifying the relationship between blood micronutrients and cancer

Selecting the exposure group:

• Depends on:

• Feasibility

• Exposure level

• Accuracy

• Completeness of information

• Experience in tracking and collecting information

Interventional Studies

Goal: To determine the impact of exposure to an intervention factor

Classification:

• Clinical trials: Prove that new drugs are more effective than classic drugs

• Preventive studies: Evaluate methods to reduce the risk of disease

• Community studies: Suitable for changing individual lifestyles, improving health

Terminology:

• Reference population: Intended application of research results

• Experimental population: Conducting trials

Requirements for selecting an experimental population:

• Sufficient sample size

• Sufficient outcomes

• Accurate information

Blinding methods:

• No blinding, single blinding, double blinding, triple blinding (to limit subjective bias)

Early termination of clinical trials:

• When statistical evidence (biological, assumption) suggests that the combination of intervention and disease outcome is clear, and chance does not achieve

Conclusion

Analytical epidemiology studies are an important tool in identifying the relationship between risk factors and disease. Understanding the types of studies, advantages, disadvantages and techniques is the basis for effectively applying AES in disease prevention, control and improving community health.