Cohort Studies

Question 1

What are cohort studies suitable for measuring?

Answer 1

Incidence

Subjects are selected based on a known exposure to the factor of interest e.g.
Babies whose mothers smoked whilst pregnant.

Subjects are followed up to a specific end point and the exposure groups compared

Question 2

What is relative risk?

Answer 2

Is the measure of the incidence risk in one group, relative to the incidence risk in another (exposed vs unexposed).

Relative risk can compare likelihood between two different groups

Question 3

What is an absoloute risk ?

Answer 3

Absolute risk is risk of an individual developing a disease over a time period

Question 4

What is the equation for relative risk?

Answer 4

Question 5

What are the advantages of cohort studies ?

Answer 5

People are recruited into cohort studies regardless of their exposure or outcome status. This is one of their important strengths. People are often recruited because of their geographical area or occupation, for example, and researchers can then measure and analyse a range of exposures and outcomes.

Cohort studies should include groups that are identical EXCEPT for their exposure status. As a result, both exposed and unexposed groups should be recruited from the same source population.
Incidence (temporal relationship between exposure and outcome) is clear.

Best evidence for causality among observational studies.

Good for assessing causality, prognosis, risk factors and harm.

Important when RCT are unethical to conduct

Question 6

What are the disadvantages of cohort studies ?

Answer 6

Key exposures of interest may go hand-in-hand with confounding factors.
Long follow-up period while waiting for events or diseases to occur. Often replaced by case-control studies
Ineffective to investigate diseases with low incidence rate, outbreaks, long latency diseases (retrospective cohort or case-control studies are more suitable for this)

Attrition. If a significant number of participants are not followed up (lost, death, dropped out) then this may impact the validity of the study. Not only does it decrease the study’s power, but there may be attrition bias – a significant difference between the groups of those that did not complete the study (increasing sample size could remedy this)

Can be expensive and time-consuming, especially if a long follow-up period is chosen or the disease itself is rare or has a long latency.
Subject to bias (confounding, associations, selection, observer, etc. bias)