Smoking is one of the major life-shortening factors that leads to accelerated aging and premature death. Quitting smoking increases lifespan and decreases biological age, as measured by DNA methylation. However, many smokers find it hard to quit. A new study published by scientists from Gero and Roswell Park Cancer Institute offers a way to track rejuvenating effect of smoking cessation in real time through the analysis of wearable data.
According to the article “Quantitative characterization of biological age and frailty based on locomotor activity records” published in Aging, the bioage acceleration 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. The study demonstrates that the smoking-induced aging acceleration reverts back to normal after smoking cessation: the process can be tracked by wearable device.
“It’s fascinating that the profound positive effect of lifestyle changes such as smoking cessation could be observed by analyzing 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.
The scientists applied machine learning tools to analyze 108112 health profiles made available by the National Health and Nutrition Examination Survey and the UK Biobank. These 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.”
Notably, the smoking effects on biological age could only be reverted before the first serious age-related disease manifestation. The authors of the article encourage everyone to quit smoking right away and hope that following the health improvement progress with the help of free research-based Gero Healthspan app will stimulate and support cessation process.
