Epidemiological study designs Flashcards
What is descriptive epidiomology ?
Descriptive Epidemiology:
Definition: Focuses on describing the distribution of diseases by time, place, and person.
Purpose: Identifies patterns and trends to generate hypotheses.
Key Elements:
Time: Seasonal trends, outbreaks (e.g., flu peaks in winter).
Place: Geographic variations (e.g., malaria in tropical regions).
Person: Age, sex, occupation (e.g., older populations at higher risk of chronic diseases).
What is analytical Epidemiology ?
Definition: Tests hypotheses about relationships between risk factors and disease outcomes.
Purpose: Determines causation.
Key Tools: Cohort studies, case-control studies, randomized controlled trials.
What is a cause and explain the difference between a direct and indirect cause ?
Cause: A factor that directly influences the occurrence of a disease or health outcome.
Direct Cause: Immediately responsible (e.g., virus causing an infection).
Indirect Cause: Contributes to the likelihood (e.g., poor sanitation leading to cholera).
What are the causal criteria (Bradford Hill Criteria) ?
Strength of Association: Strong associations (e.g., smoking and lung cancer) are more likely to be causal.
Consistency: Findings are reproducible in different studies and populations.
Specificity: A specific cause leads to a specific effect (e.g., asbestos exposure and mesothelioma).
Temporality: Cause precedes effect (e.g., obesity before diabetes).
Biological Gradient: Dose-response relationship (e.g., higher smoking rates = greater cancer risk).
Plausibility: Biological mechanism supports the relationship.
Coherence: Consistent with existing knowledge.
Experiment: Causation can be confirmed via intervention (e.g., drug trials).
Analogy: Similar cause-effect relationships exist.
What are causal pies ?
Definition: Causal pies are a model illustrating that multiple factors contribute to disease causation. They show that:
Diseases result from the interaction of several component causes.
A sufficient cause is the complete pie, which leads to the disease.
Each slice of the pie is a component cause.
What are the key concepts of the causal pie ?
Necessary Cause: A factor present in every sufficient cause (e.g., Mycobacterium tuberculosis for tuberculosis).
Component Causes: Factors that together complete the causal pathway (e.g., smoking, air pollution, genetic predisposition for lung cancer).
Public Health Implication: Addressing any component can prevent disease even if others are present.
What are the different types of observational studies ?
Cross-Sectional Studies:
Description: Snapshot of exposure and disease at a single point in time.
Strengths: Quick, cost-effective, good for prevalence.
Limitations: No causation; cannot establish temporality.
Example: Survey on smoking and respiratory symptoms.
Cohort Studies:
Description: Follows a group over time to study exposure and outcomes.
Strengths: Establishes temporality, calculates incidence.
Limitations: Time-consuming, expensive, loss to follow-up.
Example: Framingham Heart Study.
Case-Control Studies:
Description: Compares individuals with a disease (cases) to those without (controls) based on past exposures.
Strengths: Efficient for rare diseases, cheaper than cohort studies.
Limitations: Recall bias, cannot calculate incidence.
Example: Studying asbestos exposure in mesothelioma patients
What are the different types of experimental studies ?
Randomized Controlled Trials (RCTs):
Description: Participants are randomly assigned to intervention or control groups.
Strengths: High validity, establishes causation.
Limitations: Ethical concerns, expensive, limited generalizability.
Example: Testing a new vaccine.
Quasi-Experimental Studies:
Description: Non-randomized interventions.
Strengths: Useful when randomization is impractical.
Limitations: Susceptible to bias, weaker causation evidence.
Example: Evaluating a public health campaign’s impact on smoking rates.
Describe ecological studies:
Description: Compares population-level data, not individuals.
Strengths: Useful for studying broad trends.
Limitations: Ecological fallacy, no causation.
Example: Studying the relationship between air pollution and asthma prevalence across cities.
