http://www.ted.com/talks/lang/en/gerd_gigerenzer_why_do_people_fear_the_wrong_things.html
Why do people fear the wrong things?
A new drug reduces the risk of heart attacks by 40%. Shark attacks are up by a factor of two. Drinking a liter of soda per day doubles your chance of developing cancer. These are all examples of a common way risk is presented in news articles, and can ofte
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A new drug reduces the risk of heart attacks by 40%.
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Shark attacks are up by a factor of two.
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Drinking a liter of soda per day doubles your chance of developing cancer.
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These are all examples of relative risk, a common way risk is presented in news articles.
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Risk evaluation is a complicated tangle of statistical thinking and personal preference.
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One common stumbling block is the difference between relative risks like these and what are called absolute risks.
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Risk is the likelihood that an event will occur.
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It can be expressed as either a percentage— for example, that heart attacks occur in 11% of men between the ages of 60 and 79— or as a rate— that one in two million divers along Australia’s western coast will suffer a fatal shark bite each year.
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These numbers express the absolute risk of heart attacks and shark attacks in these groups.
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Changes in risk can be expressed in relative or absolute terms.
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For example, a review in 2009 found that mammography screenings reduced the number of breast cancer deaths from five women in one thousand to four.
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The absolute risk reduction was about .1%.
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But the relative risk reduction from 5 cases of cancer mortality to four is 20%.
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Based on reports of this higher number, people overestimated the impact of screening.
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To see why the difference between the two ways of expressing risk matters, let’s consider the hypothetical example of a drug that reduces heart attack risk by 40%.
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Imagine that out of a group of 1,000 people who didn’t take the new drug, 10 would have heart attacks.
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The absolute risk is 10 out of 1,000, or 1%.
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If a similar group of 1,000 people did take the drug, the number of heart attacks would be six.
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In other words, the drug could prevent four out of ten heart attacks— a relative risk reduction of 40%.
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Meanwhile, the absolute risk only dropped from 1% to 0.6%— but the 40% relative risk decrease sounds a lot more significant.
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Surely preventing even a handful of heart attacks, or any other negative outcome, is worthwhile— isn’t it?
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Not necessarily.
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The problem is that choices that reduce some risks can put you in the path of others.
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Suppose the heart-attack drug caused cancer in one half of 1% of patients.
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In our group of 1,000 people, four heart attacks would be prevented by taking the drug, but there would be five new cases of cancer.
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The relative reduction in heart attack risk sounds substantial and the absolute risk of cancer sounds small,
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but they work out to about the same number of cases.
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In real life, everyone’s individual evaluation of risk will vary depending on their personal circumstances.
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If you know you have a family history of heart disease you might be more strongly motivated to take a medication that would lower your heart-attack risk,
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even knowing it provided only a small reduction in absolute risk.
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Sometimes, we have to decide between exposing ourselves to risks that aren’t directly comparable.
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If, for example, the heart attack drug carried a higher risk of a debilitating, but not life-threatening, side effect like migraines rather than cancer,
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our evaluation of whether that risk is worth taking might change.
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And sometimes there isn’t necessarily a correct choice: some might say even a minuscule risk of shark attack is worth avoiding,
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because all you’d miss out on is an ocean swim, while others wouldn’t even consider skipping a swim to avoid an objectively tiny risk of shark attack.
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For all these reasons, risk evaluation is tricky at baseline, and reporting on risk can be misleading, especially when it shares some numbers in absolute terms
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and others in relative terms.
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Understanding how these measures work will help you cut through some of the confusion and better evaluate risk.
