Epidemiological Study Designs

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Epidemiological Study Designs - Study Blueprints

  • Foundation: Plans to study disease distribution & determinants.
  • Two Main Types:
    • Observational: Researcher observes existing patterns; no intervention.
      • Descriptive: Who, What, Where, When? (Hypothesis generating)
        • Case Report/Series
        • Ecological (population-level data)
        • Cross-sectional (prevalence at a point in time; snapshot)
      • Analytical: Why? How? (Hypothesis testing)
        • Case-Control (Odds Ratio; retrospective: outcome → exposure)
        • Cohort (Relative Risk, Incidence; prospective/retrospective: exposure → outcome)
    • Experimental (Interventional): Researcher actively manipulates exposure to assess effect.
      • Randomized Controlled Trial (RCT): Gold standard for causality; random allocation.
      • Non-Randomized Trials: Intervention, but no random allocation.

⭐ Cohort studies are best for determining incidence and the natural history of a disease.

Epidemiological Study Designs - Snapshot & Rewind

  • Observational Designs:
    • Cross-sectional (Prevalence Study):
      • "Snapshot": Assesses exposure & outcome simultaneously at one point in time.
      • Measures prevalence.
      • Uses: Health surveys, hypothesis generation.
      • Adv: Quick, inexpensive.
      • Disadv: No temporality (cannot infer causation), not for rare diseases.
      • Measure: Prevalence Ratio, Odds Ratio. Cross-sectional study design schematic
    • Case-Control (Retrospective/Trohoc Study):
      • "Rewind": Starts with outcome (Cases with disease vs. Controls without disease).
      • Looks back (retrospective) for past exposure.
      • Uses: Rare diseases, outbreak investigation. 📌 Mnemonic for selection of controls: Population-based, Hospital-based, Special group (PHS).
      • Adv: Quick, inexpensive, good for rare diseases, multiple exposures.
      • Disadv: Recall bias, selection bias, interviewer bias. Cannot calculate incidence/prevalence directly.
      • Measure: Odds Ratio ($OR = (ad) / (bc)$).

      ⭐ Odds Ratio from a case-control study can approximate Relative Risk if the disease is rare (prevalence < 10%).

Epidemiological Study Designs - Forward & Future

  • Cohort Studies (Observational): Follows groups from exposure to outcome.
    • Prospective: Present exposure → Future outcome.
      • Strengths: Establishes temporality, measures incidence, $RR = [a/(a+b)] / [c/(c+d)]$, $AR$. Good for rare exposures.
      • Weaknesses: Costly, long duration, attrition.
    • Retrospective (Historical): Past exposure (records) → Outcome.
      • Strengths: Quicker, cheaper.
      • Weaknesses: Record dependency, bias.
    • 📌 COhort = COming Outcomes.
  • Randomized Controlled Trials (RCTs) (Experimental): Intervention → Outcome.
    • Gold standard for causality. Investigator assigns exposure.
    • Key Features: Randomization, Blinding, Control.
    • Measures: Efficacy, $RR$, $AR$.
    • Strengths: ↑Internal validity, ↓bias, causal inference.
    • Weaknesses: Costly, ethical limits, ↓external validity.

⭐ RCTs provide the strongest evidence for causal relationships.

Prospective Cohort Study Diagramoka

Epidemiological Study Designs - Bias & Blunders

  • Bias: Systematic error in design, conduct, or analysis leading to erroneous association.
    • Selection Bias: Non-random subject selection.
      • Berksonian bias: Hospital-based controls differ from general population.
      • Neyman bias (Incidence-Prevalence bias): Selective survival in prevalent cases.
    • Information Bias (Measurement/Misclassification Bias): Errors in data collection/measurement.
      • Recall bias: Cases recall exposure more/less than controls (📌 common in case-control).
      • Interviewer bias: Interviewer influences responses.
  • Confounding: Distortion of exposure-disease relationship by a third variable (confounder).
    • Control: Randomization, Restriction, Matching, Stratification, Multivariate analysis.
  • Effect Modification: True difference in effect across strata of a third variable. Not a bias.

⭐ Randomization is the best method to control for unknown confounders in RCTs.

  • Bradford Hill Criteria: Guidelines for inferring causality (e.g., Strength, Consistency, Temporality, Dose-response).

High‑Yield Points - ⚡ Biggest Takeaways

  • Case-control studies: Retrospective, start with outcome, calculate Odds Ratio (OR); efficient for rare diseases.
  • Cohort studies: Prospective or retrospective, start with exposure, calculate Relative Risk (RR), Incidence; establish temporality.
  • Randomized Controlled Trials (RCTs): Gold standard for causality; use randomization, control group, blinding.
  • Cross-sectional studies: Measure prevalence (disease & exposure) at a single point in time; "snapshot".
  • Ecological studies: Use group-level data (not individual); prone to ecological fallacy.
  • Bias control: Randomization & blinding in RCTs; matching in case-control for confounders.

Practice Questions: Epidemiological Study Designs

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Which research method is most appropriate for studying the progression of a disease over time?

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Flashcards: Epidemiological Study Designs

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_____ studies are useful for measuring odds ratio (OR)

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_____ studies are useful for measuring odds ratio (OR)

Case-control

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