If case–control studies look backward from outcome to exposure, cohort studies begin with exposure and move forward in time to observe outcome.
This chapter explores the structure and analytic power of cohort designs.
A cohort study identifies groups based on exposure status and follows them prospectively - or retrospectively through existing records - to measure incidence of disease.
Cohort studies are particularly valuable for:
Establishing temporal sequence
Calculating incidence directly
Studying multiple outcomes from a single exposure
Investigating rare exposures
Key methodological considerations include:
Selection of exposed and unexposed groups
Minimising loss to follow-up
Controlling confounding
Measuring exposure accurately
Calculating relative risk and attributable risk
Unlike case–control studies, cohort designs allow direct estimation of risk and rate.
Prospective cohorts offer precision and clarity but can be expensive and time-consuming. Retrospective cohorts leverage existing data but depend on data quality.
The chapter also discusses classic long-term cohort studies that reshaped public health understanding of chronic disease risk.
Cohort studies provide one of the strongest observational designs for causal inference - short of randomised trials.
They allow epidemiology to observe disease emergence in real time.
Key Takeaways
Cohort studies begin with exposure classification.
They allow direct calculation of incidence and relative risk.
Establish temporal relationship between exposure and outcome.
Useful for studying multiple outcomes.
Particularly suited for rare exposures.
Loss to follow-up threatens validity.
Prospective and retrospective designs differ in cost and control.
Strong observational evidence for causality.
