Health and Statistics: Understanding the Numbers Makes all the Difference

statisticsI wanted to share this because lately I’ve been seeing more stories about an increase in cases of flu and the media urging people to still go and get the flu shot as the answer to the problem.

I just read this article by Dr. Brownstein which very clearly explains the truth.

What I found very helpful and important to understand is the difference between relative risk and absolute risk reduction. We have to understand these numbers so that when we see reports in the media we can distinguish the truth of what they really mean.

Simply put relative risk as explained in Patient.info is:

Relative risk compares the risk in two different groups of people. For example, the groups could be smokers and non-smokers. Research  shows that smokers have a higher risk of developing heart disease compared to (relative to) non-smokers.

So, for example: If men have a 2 in 20 risk of developing a certain disease by the time they reach the age of 60 and research shows that a new treatment reduces the relative risk of getting this disease by 50%; the 50% is the relative risk reduction, and refers to the effect on the 2 not the 20. Fifty percent of 2 is 1. So this means that the relative risk is reduced from 2 in 20, to 1 in 20. If you didn’t understand that, you might think it reduced the risk from 20 to 10. If that isn’t clear – it can be very misleading.

Absolute risk is: Absolute risk of a disease is your risk of developing the disease over a period of time. We all have absolute risks of developing various diseases such as heart disease, cancer, stroke, etc. The same absolute risk can be expressed in different ways. If you have a 1 in 10 risk of developing a certain disease in your life this can also be said to be a 10% risk, or a 0.1 risk.

Using the example from Dr. Brownstein’s post on the flu vaccine, the true reduction of the flu vaccine in preventing influenza-related medical visits across all age groups is around 1%.  A 50% relative risk reduction means that the absolute risk reduction is probably around 1%.  This means that the flu shot failed in 99% who took it. So,100 people must be injected to prevent one case of the flu, leaving the other 99 unprotected. A very different picture from the one the media portrayed.

Number Needed to Treat (NNT) is another term we should be familiar with.

This is the number of people who need to take the treatment for one person to benefit from the treatment. For example, the absolute risk of developing complications from a certain disease is 4 in 20. A medicine reduces the relative risk of getting these complications by 50%. This reduces the absolute risk from 4 in 20, to 2 in 20. In percentage terms, 4 in 20 is 20%, and, 2 in 20 is 10%. Therefore, the reduction in absolute risk in taking this medicine goes from 20% to 10% – a reduction of 10%, not 50%. The NNT would be 100 divided by 10. That is, 10 people would need to take the medicine for one to benefit.

So the questions at the end of the article on Patient.info would be ones I would ask if a doctor was prescribing any medication for me.

Now when you read about another miracle drug and how supposedly effective it is, you can assess the real numbers and understand whether the benefits are worth the risks and side effects or whether there could be a safer, better course of action.

Do you always just take any statistics for the efficacy of drugs on face value or question what they really mean?

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About amusico

I am a holistic health coach and independent nutritional consultant. All my coaching plans are based on my 3-D Living program and a big part of that are the Youngevity Products and Supplements I proudly offer! Visit my website at http://www.threedimensionalvitality.com and learn more about the products and my coaching plans!
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4 Responses to Health and Statistics: Understanding the Numbers Makes all the Difference

  1. debwilson2 says:

    Wow! That is an amazing difference and very confusing. Ann, thanks for making this clear.

  2. lesleysobeck says:

    I’m in the medical profession, and even knowing this it can still be confusing to get the true meaning of the studies that are presented on various health topics. It takes a lot of brain power to get the real numbers – more than what most people are willing to put into understanding it. And by using confusing terms like this, drug companies can “tell the truth” about their products in skewed ways, which can help the marketing they want to portray. It’s very tricky!

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