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How smartphone fitness apps can predict risk of mortality

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Unknow sportswoman holds digital mobile phone checks fitness tracker results of workout or body vitals on smartwatch dressed in anorak poses outdoors uses modern devices for sport. Cropped shot
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By Mark Waghorn via SWNS

Smartphone fitness apps can predict mortality risk over the next five years, according to new research.

They open the door towards national screening for health, scientists say.

The findings are based on 100,000 participants in the UK Biobank who wore activity monitors with motion sensors for one week.

They extract information on the intensity from short bursts of activity - a daily living version of a walk test.

The team was able to successfully validate predictive models using only six minutes a day of steady walking - combined with traditional demographic characteristics.

The equivalent of gait speed calculated from this passively collected data was a predictor of five-year mortality independent of age and sex.

Lead author, said: "Mortality is the most definitive outcome, with accurate death records for five years available for the 100,000 participants who wore sensor devices.

"We analyzed this dataset to extract walking sessions during daily living, then used characteristic motions to predict mortality risk.

"Our results show passive measures with motion sensors can achieve similar accuracy to active measures of gait speed and walk pace.

"Our scalable methods offer a feasible pathway towards national screening for health risk."

The predictive models described in PLOS Digital Health used only walking intensity to simulate smartphone monitors.

Athletic man using his mobile phone.
(Mix Tape via Shutterstock)

Schatz said "I have spent a decade using cheap phones for clinical models of health status.

"These have now been tested on the largest national cohort to predict life expectancy at population scale."

Healthcare infrastructure implementation could benefit tremendously from the devices, say the US team.

Largescale population data could delineate health risks without intruding into people's daily lives.

Schatz added: "Digital health offers potential solutions if sensor devices of adequate accuracy for predictive models could be widely deployed."

The only such current devices are smartphone devices with embedded accelerometers - limiting their use when they are carried during normal activities.

Schatz said: "So measuring walking intensity is possible, but the total activity measure with 24 hour wearable devices is not."

He added: "The accuracy achieved was similar to activity monitors measuring total activity and even similar to physical measures such as gait speed during observed walks.

"Our scalable methods offer a feasible pathway towards national screening for health risk."

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