Why Eating Like a 100-Year-Old Doesn’t Mean You’ll Live to 100

It’s a cliché to report on people turning 100, or even 110, to ask them a variation of the question, “What did you do to live so long?” Inevitably, an interesting and unexpected answer emerges. Fish and chips every Friday. Drink a glass of hard liquor every day. Bacon for breakfast every morning. Wine and chocolate, writes Bradley Elliott, Senior Lecturer in Physiology, University of Westminster.

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

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

Wald argues that armor should be added to those undamaged areas on all returning aircraft, since any aircraft hit in these undamaged areas were shot down without returning to be observed. 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 who 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 journalist interviewing the lucky soul on its 100th birthday with that classic question: “To what do you attribute successful aging?”

“He smokes a pack a day,” says the newly minted centenarian. It seems obvious, but survivorship bias is everywhere in society. We can all think of that famous actor or entrepreneur who succeeded despite adversity, who worked hard, believed in themselves and one day succeeded. But we never read or hear about the countless examples of people who tried, gave it their all, and never succeeded.

It’s not a good story in the media. But this creates a bias, we hear primarily the successes, never the failures. This bias applies to our perceptions of architecture (especially large buildings from a certain period “survive”), finance (we often hear examples of people who have succeeded in risky investments, those who fail do not sell self-help books or 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 succeeded).

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 people, many of whom are faster, fitter, and stronger than I am by many of the measures we perform in the lab, despite being nearly twice my age. While we know that their lifelong exercise is associated with their unusually good health into old age, we still can’t directly say that one causes the other. Very active people may be protected against chronic diseases such as cancer, diabetes and heart disease. But these people may still be active into old age because they were not affected by cancer, diabetes or heart disease earlier in their lives.

On the contrary, there may be a third unknown factor that we have yet to identify about these people that keeps them healthy and separately keeps them exercising. To be clear, there are things that scientists like me will say in careful 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 a positive outlook on life and of course choosing the right parents and grandparents.

Correlation does not mean causation. This point is relentlessly pushed against science degree students. This is how our brain works, we see a pattern between two variables and assume they are related in some way. But often, as with survivorship bias, we don’t look at all the data and therefore find patterns where none exist.

This article was written for The Converstaion by Bradley Elliott, Senior Lecturer in Physiology, University of Westminster