Comparative analysis of the diffusion trends of e-cigarette use and cigarette smoking among school students in China: a cross-sectional study

Objective To explore the influencing factors of and differences in cigarette smoking and e-cigarette use among school students in four typical cultural regions (Yangtze River Delta, Pearl River Delta, southwestern China, and northern China) of China, thus providing a data basis for formulating policies tailored to tobacco control interventions for students.

Methods  From September 2022 to March 2023, a multi-stage mixed sampling approach combining quota sampling and cluster sampling was employed to conduct a survey on risk behaviors among 2 815 students at four types of schools (secondary vocational schools, senior high schools, junior colleges, and universities) in the four typical cultural regions. Stata 16.0 was used to conduct χ² tests, multivariate logistic regression analyses, and Wald tests based on seemingly unrelated regression.

Results The prevalence rates of current e-cigarette use and current smoking among school students in the four regions were 1.7% and 5.6%, respectively. Being male (OR = 7.1), having abundant family assets (OR = 4.0), having peers (chatting for ≥ 30 min in the past month) who use e-cigarettes (OR = 3.8), and having peers who smoke cigarettes (OR = 2.5) were significantly associated with current e-cigarette use among school students. For current smoking, being male (OR = 10.4), aging 18–24 years old (OR = 1.8), and having peers who smoke cigarettes (OR = 7.4) were positively associated with current smoking among school students. Comparison of regression coefficients among different influencing factors showed that aging 18–24 years old and having peers who smoke cigarettes had stronger associations with current smoking among school students than current e-cigarette use. Conversely, having abundant family assets and having peers who use e-cigarettes had more significant associations with e-cigarette use among school students (P < 0.05). Although gender was significantly associated in both the models for e-cigarette use and cigarette smoking, the coefficients had no significant difference between the two.

Conclusions E-cigarette use is consistent with the pattern of diffusion of innovations prioritized for adoption by high socioeconomic status, and smoking is more concentrated among those aged 18–24 years old than among those aged 15–17 years old, reflecting the rising trend of e-cigarette use and the steady or declining trend of cigarette smoking among school students.