NCCMT - URE - What’s the Risk? Understanding Absolute and Relative Risk Reduction

Studies on the effectiveness of public health interventions can present the results in different ways knowing how to interpret those results will not only help you understand how effective an intervention is but also how meaningful it will be to your population when the outcome is defined as the presence or absence of an event the outcome is often reported as an event rate also known as absolute risk absolute risk is the percentage of people with the outcome within a group in studies evaluating the effectiveness of an intervention the absolute risk is calculated for both the intervention and control groups and then compared let's look at a hypothetical example a study evaluating the effectiveness of an intervention to reduce fractures among older adults compares the number of people with fractures and those exposed to the intervention to those not exposed let's say 300 seniors are randomly allocated to an intervention group and another 300 to a control group which receives no intervention 90 seniors in the control group experience a fracture their absolute risk for a fracture is calculated by dividing 90 by 300 which equals 0.30 we can show this number as a percentage by multiplying by 100 which gives us an absolute risk for a fracture of 30% among those in the control group we can also say that the baseline risk for a fracture among those in the control group is 30% because the absolute risk is equivalent to baseline risk for those not exposed to an intervention given the intervention and control groups are randomly allocated we know that baseline risk for a fracture in the intervention group is also around 30% however after exposure to the intervention 54 seniors report fractures we calculate absolute risk for a fracture in the intervention group by dividing 54 by 300 which equals 0.18 so those in the intervention group have an absolute risk for a fracture of 18% following the intervention because the risk for is lower following the intervention we can determine the absolute risk reduction or a RR we calculate this by subtracting the absolute risk of those exposed to the intervention from those not exposed so 30% minus 18% gives us an absolute risk reduction of 12% which means the intervention lowered the risk of a fracture by 12 percent while the ARR gives us some indication of the impact of an intervention it doesn't tell us the whole story from our example we know that the intervention lowers the risk for a fracture by 12% but how much risk for a fracture remains among those exposed to the intervention we need to calculate the relative risk to answer this question the relative risk takes into account the baseline risk for the outcome among those in the intervention group compared to those in the control group to calculate relative risk we divide the absolute risk of the intervention group by the absolute risk of the control group so from our example 18% divided by 30% equals zero point six zero this tells us that the risk for a fracture among those in the intervention group is 60 percent of the risk in the control group now that we know how much risk for a fracture remains after exposure to the intervention we can calculate how much the risk for a fracture is reduced among those in the intervention group this is referred to as the relative risk reduction or RRR for short the RRR is calculated by subtracting the relative risk percentage from 100% from our example we subtract the remaining risk of 60% from 100 which gives us 40 percent and means the intervention reduces the relative risk for a fracture by 40 percent among those exposed to the intervention these three statistics present the effect of an intervention in different ways all provide useful information and together give a more complete understanding of an interventions in let's summarize what we know so far about the intervention first we know that the baseline risk for a fracture in both groups is 30% we know that the absolute risk in the control group is also 30% and that the intervention reduces the risk for a fracture by 12 percent in addition we know that the intervention reduces the relative risk for a fracture by 40 percent among those in the intervention group compared to no intervention so far we've considered a situation where the baseline risk for a fracture is 30% but what happens if the baseline risk is lower let's say another study is conducted where the baseline risk for a fracture is only 10% this means the absolute risk for a fracture in the control group is also 10% if the groups are randomly allocated we can assume that the baseline risk in the intervention group is also about 10% let's assume the intervention has the same effect as it did in the first study so the relative risk reduction is 40% therefore following the intervention the intervention groups risk for a fracture will be 40% of 10% which means the absolute risk in the intervention group will be 6% to calculate the absolute risk reduction we subtract the absolute risk of 6% in the intervention group from the absolute risk of 10% in the control group which is 4% in our second study when the baseline risk for a fracture is 10% and the relative risk remains the same at 40% the absolute risk reduction for a fracture is only 4% let's recap in the first study the baseline risk for a fracture is 30% the absolute risk reduction is 12% and the relative risk reduction is 40% in the second study even though the relative risk reduction stays the same at 40% when the baseline risk drops to 10% the ARR decreases to 4% these two examples illustrate how baseline risk for an outcome influences the absolute risk reduction even though the relative risk reduction remains the same that's why it is important to consider the baseline risk in your population prior to implementing an intervention if it's lower in your population than in those studied then you can expect the absolute risk reduction to be less than that reported in published studies the opposite is true when the baseline risk is higher being able to calculate these statistics yourself will help you make more informed decisions almost all published studies provide the number of participants experiencing the outcome in both the intervention and control groups along with the total number of participants in each group which is all you need to do your own calculations with a little practice you will become more confident in using these statistics to inform decisions about public health interventions for more on calculating and interpreting relative risk check out our video relative risk it's easy to calculate and interpret for more on the evidence informed decision-making process check out our video evidence and form decision making a guiding framework for Public Health you

Channel: The NCCMT

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Keywords: NCCMT, Stats, Statistical Terms, Statistics, Evidence-Informed Public Health, Public Health, Evidence-Informed Practice, Research Evidence, Understanding Research, Nursing, Dobbins, Maureen Dobbins, EIDM, Relative Risk, Relative risk reduction, Absolute risk, Absolute risk reduction, National Collaborating Centre, baseline risk

Id: QPXXTE8N4PY

Length: 8min 24sec (504 seconds)

Published: Tue May 10 2016