Don’t Be Fooled by Big Numbers: How Relative Risk Reduction Can Be Misleading
In medical studies and pharmaceutical marketing, one of the most common ways data is manipulated—intentionally or not—is through the use of relative risk reduction instead of absolute risk reduction. It sounds technical, but this distinction is critical to understanding the real impact of treatments and interventions.
Let’s say a drug reduces the risk of a disease from 2% to 1%. That’s a 1% absolute reduction in risk—meaning only 1 out of 100 people actually benefit. But marketers will often report this as a 50% relative risk reduction, making the treatment sound far more effective than it really is.
Why does this matter? Because decisions about your health—what to take, what to avoid, what to fear—should be based on clear, contextualized data, not inflated statistics that obscure the truth. Relative risk can make small differences look huge, and it’s a tool that’s frequently used to drive fear, sell interventions, or push public health campaigns without full transparency.
Science should inform and empower—not manipulate. Always ask: What’s the absolute risk? How many people actually benefit?
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