Dataset Information

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

ABSTRACT: There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study we demonstrate for the first time that smoking status can be predicted using blood biochemistry and cell count results andthe recent advances in artificial intelligence (AI). By employing age-prediction models developed using supervised deep learning techniques, we found that smokers exhibited higher aging rates than nonsmokers, regardless of their cholesterol ratios and fasting glucose levels. We further used those models to quantify the acceleration of biological aging due to tobacco use. Female smokers were predicted to be twice as old as their chronological age compared to nonsmokers, whereas male smokers were predicted to be one and a half times as old as their chronological age compared to nonsmokers. Our findings suggest that deep learning analysis of routine blood tests could complement or even replace the current error-prone method of self-reporting of smoking status and could be expanded to assess the effect of other lifestyle and environmental factors on aging.

SUBMITTER: Mamoshina P

PROVIDER: S-EPMC6333803 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

Mamoshina Polina P Kochetov Kirill K Cortese Franco F Kovalchuk Anna A Aliper Alexander A Putin Evgeny E Scheibye-Knudsen Morten M Cantor Charles R CR Skjodt Neil M NM Kovalchuk Olga O Zhavoronkov Alex A

Scientific reports 20190115 1

There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study we demonstrate for the first time that smoking status can be predicted using blood biochemistry and cell count results andthe recent advances in artificial intelligence (AI). By employing age-prediction models developed using supervised deep learning ...[more]

PMID: 30644411

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Project description:IntroductionSmoking remains a major health risk factor and China is the world's largest consumer of tobacco. Smoke-free policies in public places are a powerful weapon in tobacco control. Therefore, the aim of this study was to assess the association between smoke-free policies in public places and smoking cessation among smokers in China from 2012 to 2020.MethodsIn this study, we assessed the impact of smoke-free public places policies on smoking cessation situation among smokers aged 16 years and older. We do this by conducting a difference-in-differences analysis using data from the China Family Panel Study (CFPS) 2012-2020.FindingsBy 2020, about 60.2% of the cities were covered by partial smoke-free policies and about 38.5% by comprehensive smoke-free policies. Based on the results of the study, we found that the medium-term effect model (Model 2, 2012:2016; Model 3, 2012:2018) of the impact of partial smoke-free policies on smoking cessation was not statistically significant using 2012 as the study baseline; the short-term effect model (Model 1; 2012:2014; P< .01) and the long-term effect model (Model 4; 2012:2020; P< .05) were statistically significant; the effect of a comprehensive smoke-free policy on smoking cessation (Model 5; 2012:2020; P<.05) was statistically significant.ConclusionChina's existing comprehensive smoke-free policies have had a modest impact on smoking cessation among the smoking population, and a strong, comprehensive national smoke-free law is urgently needed to achieve greater public health outcomes.ImplicationsSmoke-free policies are an important intervention to influence smoking behavior. This study demonstrates that comprehensive smoke-free policies in public places in China can effectively influence smoking behavior and show long-term trends in smoke-free behavior, while also reflecting the need to promote comprehensive smoke-free policies. This study provides a basis for the implementation of comprehensive smokefree policies into law and also provides a basis for policy makers.

Dataset Information

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

Publications

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

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