Online “death clocks” that claim to be able to tell you how long you’ve got vary widely in their estimates of personal doomsdays… and their predictions should be taken with a pinch of salt
A UK economist plugged his own vital statistics into a variety of online clocks, and also used the UK Office for National Statistics’ (ONS) “life tables” to see whether they agreed.
The ONS approach told him he’d die aged 82, but online clocks varied between age 67 and 89, suggesting “death clocks” should carry a health warning, says John Appleby, Chief Economist at the Nuffield Trust.
Differences in the data requested, risk calculations, and methods of combining risk factors probably account for the inconsistencies between the clocks, he adds.
Mr Appleby published his findings in The BMJ, saying that knowing when you are going to die could help make life choices.
Data from the ONS period life tables estimate life expectancy at birth averaged across the three years of 2013 to 2015 to be around 79 years for boys and 83 for girls, explains Appleby.
Over the past 33 years, average life expectancy at birth for UK residents has been increasing by, on average, 13.1 weeks per year for boys and 9.5 weeks for girls.
Of course, many factors can affect life expectancy, such as genetics, lifestyle, wealth, education and employment. Being married, for example, can add over a year to life expectancy compared with being single. And one study even suggests that optimists have a 55% lower risk of early death than pessimists.
But for a more individual perspective, he says we need to adjust these figures for personal characteristics and circumstances.
Based on his sex and the current mortality for his age group, ONS life tables suggest Mr Appleby will die around May 2040, about a month after his 82nd birthday.
But plugging in a few more personal details – such as his marital status, income, and stress levels – into a random selection of online death clocks produced a range of predictions for his life expectancy from 67 to 89.
Some of the variation in predictions is due to differences in the basic life table data that the clocks use (some are based on non-UK data for example), he explains.
Differences will also arise given the particular risk calculators (prediction models) used, the number of variables included, and the way they combine variables to produce individualised forecasts.
So perhaps the only safe conclusion is that death clocks should come with a health warning, he concludes.
“Calculating the date of your demise is somewhat sobering and the results should be taken with a pinch of salt.”