Risk Ratio (Relative Risk)

Risk, or absolute risk, is simply the probability of an outcome: the number of people with the event divided by the total in that group. The risk ratio (RR), also called relative risk, divides the risk in the treated or exposed group by the risk in the control group. It answers a natural question: how many times as likely is the outcome with the exposure? An RR of 1 means the two risks are equal, so there is no effect. An RR below 1 means the treatment or exposure lowers risk and is protective; for example RR 0.7 means a 30% lower risk. An RR above 1 means it raises risk; RR 1.5 means a 50% higher risk. A closely related figure, the relative risk reduction (RRR), equals 1 minus RR and expresses the proportional drop, so an RR of 0.7 is a 30% relative risk reduction. The risk ratio comes naturally from studies that follow groups forward and can measure risk directly, namely cohort studies and randomized controlled trials. It cannot be computed validly from a case-control study, where investigators fix how many cases and controls to enroll, so true risk is not measurable; those studies use the odds ratio instead. Always report an RR with a confidence interval, and if the interval includes 1 the effect is not statistically significant. A crucial caution: relative measures can mislead about real-world impact. An RR of 2.0 sounds alarming, but if the baseline risk is 1 in 100,000, doubling it is still tiny. Relative risk tells you only the proportional change; you need the absolute risk and the number needed to treat (later lessons) to judge how much it actually matters to a patient. The professional habit is to report relative and absolute measures together.