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The balance between danger and protection: How do relative risks affect our health decisions?
In today's medical environment, the results of medical research are often explained through various statistical indicators, among which "Relative Risk" (RR) is one of the most commonly cited. Relative risk, as an indicator of hazard versus protection, can provide critical insights in clinical trials and health decision making, but if not interpreted correctly it can lead to serious misunderstandings.
Relative risk is the ratio of the chances of an outcome occurring under some exposure (such as receiving a treatment) to the chances of an outcome occurring under no exposure (such as health insurance or a placebo).
The definition and significance of relative risk
Relative risk is a statistical measure used to assess the association between an exposure (such as a treatment or risk factor) and an outcome. Conceptually, it is the ratio of the incidence of an outcome in an exposed group (e.g., patients who use a drug) to the incidence of the outcome in a non-exposed group (e.g., patients who do not use the drug). For example, if in a trial, 1.7% of patients taking a new drug develop a disease compared with 8.8% of patients taking a placebo, the relative risk would be about 0.19 (1.7/8.8), meaning that the new drug is more likely to develop a disease. Patients who received the drug had an 81% lower risk of developing the disease than those who received a placebo.
RR = 1 means the exposure has no effect on the outcome, RR < 1 means the exposure reduces the risk of the outcome, and RR > 1 means the risk increases.
Use and issues in reporting
Relative risk is often used in reports of double-blind randomized controlled trials. However, if the results are assessed solely on the basis of relative risk, without the support of other indicators such as absolute risk or risk difference, the significance of the public health impact may be misunderstood. In particular, when the underlying event rate is low, very large or small relative risks may not significantly affect the results, whereas when the event rate is high, even relative risks close to 1 may still have a significant effect.
Therefore, it is recommended to provide both absolute and relative risk data when reporting to give readers a more comprehensive understanding.
How to derive relative risk from data
In statistical analysis, relative risk can usually be obtained from a 2x2 contingency table. In the table, the data were categorized according to exposure and outcome, and the disease incidence rates for the exposed and unexposed groups were calculated. This approach helps researchers intuitively understand the association between exposure and outcome.
Comparison of relative risk and betting ratio
Although relative risk and odds ratio are often used interchangeably, there is actually a difference between the two. In the case of extremely low event rates, the bet ratio will be close to the relative risk. In practice, however, gambles are more common than in case-control studies, because relative risks cannot be directly estimated in such studies. The reason for preferring to report relative risk directly over the odds ratio is that it is intuitive, that is, relative risk makes it easier for the public to understand the effectiveness of treatment.
Application in health decision making
Relative risk is a key decision-making tool, particularly in public health and personal health management. Understanding the risks and benefits of a treatment or behavior can enable patients and health care providers to make more informed health decisions. For example, when the relative risk of a treatment suggests a reduction in disease risk, this may lead more patients to choose to receive the treatment.
If we better understood what relative risk means, could we make more informed health choices?
