E-cigarettes and health: segmentation of risk awareness with latent class analysis

Electronic cigarette (e-cig) use, especially among young people, has become widespread. The aim of this study was to use Latent Class Analysis (LCA) to identify and categorize distinct groups of individuals based on their awareness of the health risks and characteristics of e-cigs. We administered a questionnaire to 83 participants, with an average age of 27.22 years, that included 83 questions on different aspects of e-cigs, including composition, health effects and risk perceptions. Only 23 questions were considered suitable for analysis. We found that the probability of belonging to the ‘Low awareness’ class is higher than the ‘High awareness’ class. We observed that there is a distinction between subjects with Low and High awareness about the risks of e-cigs, this is observed as the response probability of the ‘High Awareness’ class is greater than that of the ‘Low Awareness’ class. Among those who were surveyed, only 55.4% had a high awareness of the risks of e-cigs