What Relative Risk Measures in a Cohort Study
Relative risk (RR) measures the ratio of the probability of disease occurring in the exposed group compared to the unexposed group—it directly compares the risk of heart disease between those with a bad diet versus those with a good diet. 1, 2
Definition and Interpretation
Relative risk is calculated as the ratio of disease risk in the exposed group divided by the risk in the unexposed group 3. In your cohort study example:
- RR compares the incidence of cardiac disease in the bad diet group to the incidence in the good diet group 2
- It tells you how many times more (or less) likely the exposed group is to develop the outcome compared to the reference group 4
- An RR of 2.0 would mean the bad diet group has twice the risk of cardiac disease compared to the good diet group 1
Why This Matters for Your Question
Looking at your answer choices:
- Option C is the correct answer: RR measures the probability (risk) of having heart disease based on diet exposure 2, 3
- Option A is incorrect—that describes odds, not relative risk 5
- Option B is incomplete—RR requires comparison between groups, not just risk in the exposed group alone 4
Key Distinction from Odds Ratio
Relative risk is the preferred measure in cohort studies because it directly calculates actual risk ratios, whereas odds ratios (OR) are typically used in case-control studies 5, 2. The OR approximates RR only when the outcome is rare (<10% incidence), but when outcomes are common (≥10%), the OR will exaggerate the true relative risk 5. In cohort studies examining diet and cardiac disease, where outcomes may exceed 10%, reporting RR provides a more intuitive and accurate measure of association 5, 4.
Clinical Application
RR provides the most clinically meaningful interpretation because it reflects how people naturally think about risk 4. When adjusted for confounders (age, smoking, cholesterol, etc.), the adjusted RR removes the influence of extraneous variables and provides a valid estimation of the true association between diet and cardiac disease 2. For example, studies examining C-reactive protein and coronary disease showed RR values ranging from 1.65 to 2.44 depending on adjustment for conventional risk factors, demonstrating how confounders affect the magnitude of association 1.