Surprising mortality rate research exploited data from a cohort of as many as 100.000 participants. Individuals who for a week brought with them activity detectors equipped with sensors of movement. Not expensive smartwatches, I mean, but normal cell phones.
Gathering just 6 minutes a day of data from the walking subjects studied, the researchers were able to successfully infer predictive models of mortality risk.
What is the mortality rate
The mortality rate is the number of deaths in a given population. The higher it is, the greater the impact on the population. A high mortality rate can lead to a decrease in population size, as well as a decrease in the quality of life for those who remain.
Passive meters and unexpected effectiveness
When the research team further combined this data with traditional demographic characteristics, they found a predictor of 5-year mortality that was independent of both age and sex.
In the press release (that I link to you here), the first author Bruce Schatz from the University of Illinois showed great enthusiasm. “Our results show that passive measurements with motion sensors can achieve similar accuracy to active measurements of gait speed and pace,” says Schatz.
Our methods offer a feasible path towards national mortality rate screening and health risk analysis.
Bruce Schatz, University of Illinois
Towards widespread screening
Schatz has spent a decade using cheap phones as clinical models of health status. Despite the skepticism of many colleagues as well, this extensive test shows their validity.
Is it possible to predict mortality rate and life expectancy on a population scale in an ultra-widespread way? After all, these things are everywhere.
In the near future, having this data and the way to relate it will mean having an eye on the "dashboard" of everyone's life, and of each of us.
