Chwał Joanna, Zadoń Hanna, Szaflik Piotr, Dzik Radosław, Filipowska Anna, Doniec Rafał, Kostka Paweł, Michnik Robert
Department of Medical Informatics and Artificial Intelligence, Faculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, Poland.
Joint Doctoral School, Silesian University of Technology, 44-100 Gliwice, Poland.
J Clin Med. 2025 Jun 23;14(13):4459. doi: 10.3390/jcm14134459.
: Recent research highlights uncertainties surrounding the metabolic effects of nicotine in young adults, particularly among people who use e-cigarettes. While traditional smoking is known to alter body composition, the metabolic impact of using e-cigarettes remains less understood. : In this cross-sectional study, body composition (via bioelectrical impedance analysis) and lifestyle data were collected from 60 university students (mean age: 21.7 ± 1.9 years), who were classified as people who use e-cigarettes exclusively, people who smoke cigarettes exclusively, or people who have never used nicotine products. To address confounding by sex and age, inverse probability of treatment weighting (IPTW) was applied. : After adjustment, people who use e-cigarettes had significantly higher body fat percentage compared to people who have never used nicotine (β = 5.45, = 0.001), while no significant differences were found between people who smoke cigarettes and other groups. Energy drink consumption was also positively associated with body fat percentage and metabolic age. Machine learning models, particularly k-nearest neighbors, achieved moderate classification accuracy (up to 72%) in distinguishing people who use nicotine from people who have never used nicotine based on physiological and lifestyle features. : It is important to note that the majority of participants were metabolically healthy, and the observed differences occurred within a clinically normal range. While these findings suggest associations between e-cigarette use and higher adiposity in young adults, no causal inferences can be made due to the observational design. Further longitudinal studies are needed to explore the potential metabolic implications of nicotine use.
近期研究凸显了围绕尼古丁对年轻人代谢影响的不确定性,尤其是在使用电子烟的人群中。虽然传统吸烟已知会改变身体成分,但使用电子烟的代谢影响仍了解较少。
在这项横断面研究中,通过生物电阻抗分析收集了60名大学生(平均年龄:21.7±1.9岁)的身体成分和生活方式数据,这些学生被分类为仅使用电子烟的人、仅吸烟的人或从未使用过尼古丁产品的人。为了解决性别和年龄的混杂问题,应用了治疗权重的逆概率(IPTW)。
调整后,与从未使用过尼古丁的人相比,使用电子烟的人身体脂肪百分比显著更高(β=5.45,P=0.001),而吸烟者与其他组之间未发现显著差异。能量饮料消费也与身体脂肪百分比和代谢年龄呈正相关。基于生理和生活方式特征,机器学习模型,特别是k近邻算法,在区分使用尼古丁的人和从未使用过尼古丁的人方面达到了中等分类准确率(高达72%)。
需要注意的是,大多数参与者代谢健康,观察到的差异发生在临床正常范围内。虽然这些发现表明年轻人中使用电子烟与更高的肥胖程度之间存在关联,但由于观察性设计,无法做出因果推断。需要进一步的纵向研究来探索使用尼古丁的潜在代谢影响。