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Quitting smoking made easier with this smartphone app

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Quitting smoking made easier with this smartphone app

Looking to quit smoking, but finding it hard to follow? Fret not, a new study published in the Aging journal offers a way to track the rejuvenating effect of smoking cessation in real time by analyzing the wearable data, making it easier to quit smoking.

Smoking leads to accelerated aging and premature death and is one of the major life-shortening factors. Quitting smoking decreases biological aging (as measured by DNA methylation) and increases lifespan.

According to the study, the acceleration of biological age caused by smoking can be detected through the analysis of physical activity signals collected from wearable devices.  From this, a new AI algorithm trained to find certain patterns in intraday changes of activity level to estimate the biological age of a person has been developed.

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Also Read: New study shows smoking speeds up aging

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The study demonstrates that the smoking-induced aging acceleration reverts back to normal after smoking cessation: the process can be tracked by a wearable device.

“It’s fascinating that the profound positive effect of lifestyle changes such as smoking cessation could be observed by analyzing the physical activity of a person. A biomarker of age derived from physical activity is a cheap and convenient way to track how biological age reverts back to normal after quitting. Inspired by these findings, we created a free mobile app, Gero Healthspan, that offers real-time monitoring of bioage changes in response to lifestyle interventions. You can use it to explore how lifestyle changes such as diets, activities, and supplements affect your predicted healthy life expectancy. We hope that our research and our research-based app will help people to stop deliberately shortening their lives and help to develop healthy lifestyles”, says Peter Fedichev, founder and Chief Science Officer of Gero.

Also Read: Take measures- Smoking cessation may lead to weight gain

The research team used machine learning tools to analyze 108112 health profiles made available by the National Health and Nutrition Examination Survey and the UK Biobank. The large databases contain activity records provided by wearable devices as well as health and lifestyle information, combined with death records up to nine years following the activity monitoring.

“The patterns of locomotion are directly related to multiple aspects of health”, explains Arnold Mitnitski, Dalhousie University Research Professor, Department of Medicine. “The authors have applied a set of sophisticated mathematical methods to human locomotion data from large databases and found signatures of the aging process. By mining the locomotor activity in individuals they extracted a measure of biological age and demonstrated its strong association with remaining lifespan, healthspan of and the risks of morbidities and mortality. This is very promising research that opens the opportunity to assess health status from wearable devices (one of such products developed by Gero research team is already available as an iPhone application) and should have many practical implications to individual and public health issues.”

Effects of smoking on biological age could only be reverted before the first serious age-related disease manifestation. The study authors encourage everyone to quit smoking right away and hopes that following the health improvement process through free research-based Gero Healthspan app will support and stimulate the cessation process.

For further reference follow the link: https://doi.org/10.18632/aging.101603



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Source: With inputs from Aging

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