To do this, mathematicians studied what factors life expectancy depends on, observing the health of more than 110 thousand people for 25 years.
Analysis of how the health status of more than 110 thousand people in Great Britain has changed over several decades has allowed mathematicians to create a statistical algorithm to predict the life expectancy of an arbitrary resident of the country: https://argoprep.com/blog/k8/go-math-grade-6-vs-argoprep/. The press service of the University of East Anglia writes about this.
“We recently studied the factors that affect life expectancy. Over the course of 25 years, we observed the health of more than 110,000 Britons who turned 60 between 1990 and 2000. With this data, we created an algorithm that can estimate life expectancy for 648 different risk profiles, “said Elena Kulinskaya, professor at the University of East Anglia and one of the algorithm developers.
In recent years, scientists have been actively trying to come up with a method that would help estimate the so-called biological age of a person. By this term, they call how strongly the tissues and organs of a particular individual differ in a positive or negative way in comparison with his peers. Such discrepancies can be associated with both diet and bad habits, and with genes that are associated with the aging of the human body.
For a long time, researchers believed that accurate data of this kind could not be obtained due to the fact that aging is almost not reflected in the level of gene activity and the nature of their work. In recent years, researchers have received convincing evidence that this is not the case and that a person’s biological age can be found out by analyzing the composition of his blood and processing the data using machine learning. Among them are https://argoprep.com/blog/k8/go-math-grade-7-vs-argoprep-grade-7/.
The power of big data
On the other hand, scientists have recently discovered that similar accuracy of calculations can be achieved by processing large amounts of information collected by medical and social services with neural networks or statistical algorithms. Thanks to this, it is possible to accurately calculate the biological age of a person, based on his bad habits, chronic diseases and living conditions.
Kulinskaya and her colleagues adapted this technique to solve a similar, but slightly different task – calculating how long a person will live. In this they relied on his medical history, position in society and other statistical and demographic factors.
To do this, scientists have followed how the health of over 110 thousand Britons who retired at the end of the last century changed. The data collected from these observations helped to highlight a number of patterns that link longevity to bad habits, lifestyle habits, chronic diseases and economic factors.
Based on this, scientists have created an algorithm that can predict how long a person living in Britain will live and not planning to change their place of residence and occupation. True, the latest version of this algorithm does not take into account how epidemics like COVID-19 affect typical life expectancy, but mathematicians are planning to take them into account in the near future.
Such calculations, as noted by the scientists, will be especially interesting for insurance companies and government agencies, since thanks to this it is possible to calculate how much money will be needed in order to maintain a comfortable life and health of people who have not yet reached old age.