Why you shouldn’t take nutritional advice from people who have lived over 100 years

Inevitably, some interesting and unexpected answer stands out. Fish and chips every Friday. Drink a glass of strong liquor every day. Bacon for breakfast every morning. Wine and chocolate

While it’s popular news, this is a relatively meaningless question that doesn’t help us understand why certain people have lived so long. Let me try to explain why through beautiful buildings, fighter pilots and statistics.

In World War II, Allied statisticians were applying their skills to minimize the number of bombers shot down by enemy fire. By studying the damage patterns of bombers returning from action, the most frequently damaged parts of the planes could be mapped so that heavy and expensive armor could be added to those areas.

Simple enough, right? Then comes the statistician Abraham Wald who defends the exact opposite point. The planes they are studying are all the ones that came back from combat with heavy damage, but what about the ones that didn’t?

Wald argues that shielding should be added to those places that are not damaged on all returning aircraft, since any aircraft that hit these undamaged areas were shot down, never to be brought back under control.

survival bias

This phenomenon is known as survivorship bias, or the cognitive and statistical bias introduced by counting only those who are around to count but ignoring those who did not survive.

You can take these examples to the absurd. Imagine a group of 100 people, all of whom have smoked all their lives. As a group, smokers would die earlier from cancer, lung disease or heart disease, but one or two might defy the odds and live to be 100. Now imagine the intrepid reporter interviewing the lucky soul on his 100th birthday with this classic question: To what do you attribute your successful aging?

Smoke a pack a day, says the newly minted centenarian.

It seems obvious, but survival bias is everywhere in society. We can all think of that famous actor or businessman who succeeded despite adversity, who worked hard, believed in themselves and one day made it. But we never read or hear about the countless examples of people who tried, gave it their all, and never succeeded.

Not a good media story. But this creates a bias, we listen mainly to the successes, never the failures. This bias applies to our perceptions of architecture (large buildings from a certain period mostly survive), to finance (we often hear examples of people who have succeeded in risky investments, those who fail don’t sell books or self-help plans), and career plans (if you work hard and drop out of college now, you can be a successful athlete like me, say those who have).

I work with a variety of older people and often include extreme people who have lived to extreme ages. We are currently studying people over 65 who have maintained unusually high levels of exercise into old age and have maintained excellent health.

They are phenomenal examples of older humans, many of whom are faster, fitter, and stronger than I am by many of the measurements we take in the lab, despite being almost twice my age.

Although we know that their lifelong exercise is associated with their unusually good health into old age, we still cannot directly say that one causes the other. It could be that very active people are protected against chronic diseases such as cancer, diabetes and heart disease. But it could also be that these people are still active in old age because they have not been affected by cancer, diabetes or heart disease earlier in their lives.

Conversely, there could be some unknown third factor that we haven’t yet identified about these people that keeps them healthy and separately keeps them exercising.

Just to be clear, there are things that scientists like me will say in carefully worded scientific language that will probably help you live longer. Being very physically active, not eating too much and not smoking are all on this list, along with having a positive overall outlook on life and of course choosing the right parents and grandparents.

Correlation does not equal causation. This point relentlessly confronts students of science degrees. It’s how our brain works, we see a pattern between two variables and assume they are related in some way. But often, as in survivorship bias, we’re not looking at all the data, and so we find patterns where there aren’t any.

(Author Bradley Elliott is Senior Lecturer in Physiology at the University of Westminster)

This article is republished from The Conversation under a Creative Commons license. Read the original article.