Do people in supposed “blue zones” really have an above-average chance of living over 100 years? Despite the idea’s popularity, new Ig Nobel award-winning research has kind of killed it (pun most certainly intended). It seems past research into extreme old-age demographics has been riddled with fundamental flaws that have produced distorted conclusions.

The Ig Nobel Prize is a satirical annual award handed out scientific research that “makes people laugh, and then think”. The award first started in 1991 and is intended to celebrate the unusual and imaginative approaches some researchers adopt for their subject.

This year, Dr Saul Justin Newman at the Centre for Longitudinal Studies, UCL, won the first-ever Ig Nobel award for Demography for his work on data about the world’s oldest people. According to his findings, patterns concerning extremely old age and supercentenarians (people of 110 years of age or older) are likely the result of poor record-keeping, clerical errors, and pension fraud.

In doing so, Newman has struck a significant blow to the popular idea concerning so-called “blue zones”. These are places in the world that appear to have unusually high concentrations of extremely old people living within them. Examples of proposed blue zones include Loma Linda, in California, Okinawa in Japan, Sardinia in Italy, Nicoya in Costa Rica, and Ikaria in Greece.

The popularity of the idea that there are some places with exceptional longevity has sparked significant interest, leading to diverse efforts to understand how so many people are living so much longer than average. The overall populations within these blue zones, as well as those individuals who appear to be living into extreme old age, have been analyzed for their life patterns, social connections, biomarkers, genomic variations and so on. All of these studies are searching for the same answer: what are the secrets to long life?

But Newman believes the answer has less to do with any particular lifestyle factor, and rather more to do with dodgy data.

In his new preprint study, yet to be published in a peer-reviewed journal, Newman shows that the highest rates of achieving old age are predicted by three factors: high poverty, a lack of birth certificates, and fewer 90-year-olds.

Poverty, in this context, leads to greater pressure to commit pension fraud. At the same time, the state-specific introduction of birth certificates, Newman claims, is associated with a 69 to 82 percent decrease in the number of supercentenarian records.

This work even challenges supposedly validated cases of the world’s oldest people, including the world’s oldest man, who appears to have three different birthdays.

“Substantial error rates were recently uncovered in every ‘Blue Zone’,” Newman writes.

“In 1997, thirty thousand Italian citizens were discovered to be claiming the pension whilst dead. In 2008, 42 percent of Costa Rican 99+ year olds were revealed to have ‘mis-stated’ their age in the 2000 census and, after limited error-correction, the Nicoya Blue Zone shrunk by around 90 percent and old-age life expectancy plummeted from world-leading to ‘near the bottom of the pack’.”

In 2010, over 230,000 Japanese centenarians were found to be missing, imagined, the results of clerical errors, or actually dead.

Even an analysis of the supposed reasons for extreme longevity turned out to be pretty suspect. For instance, a diet of vegetables and sweet potatoes has been identified as a potential root of Okinawa’s blue zone inhabitants. But the Japanese government has stated that Okinawans eat the lowest number of vegetables and sweet potatoes in the country, and they have the highest body mass indexes too.

Newman has previously debunked other claims concerning extreme age. For instance, he disproved a 2016 study that suggested a defined limit to the human lifespan. Then in 2018, he debunked another paper that made the opposite claim, showing that patterns in old-age data are probably caused by errors.

The preprint, which is a version of a paper that has not yet been peer-reviewed, is available via bioRxiv.