Bidirectional Association Between E-cigarette Use and Depression: A Meta-analysis
Tuesday, December 16, 2025
Posted by: Natalia Gromov
Ji S, Chen L, Zhuang S, Wei L, Gou L, Shi C, Jia H, Chen X. Bidirectional Association Between E-cigarette Use and Depression: A Meta-analysis Nicotine Tob Res. 2025 Nov 23;27(12):2142-2151. doi: 10.1093/ntr/ntaf163. PMID: 40794808. Introduction: Previous studies have indicated a potential bidirectional association between the use of e-cigarettes (ECs) and depression. However, this hypothesis has not yet been thoroughly investigated. In this meta-analysis, the two-way relationship is examined. Aims and methods: As of November 2024, major electronic databases were searched. Two sets of pooled risk estimates were computed by employing random effects models: one for EC use predicting depression and the other for depression predicting EC use. The forms of depressive presentation included in this study are major depressive disorder, dysthymia, and general depressive symptoms. The results were presented in terms of adjusted odds ratios (ORs) along with 95% confidence intervals (CIs). Results: We identified a total of 1601 references and included 27 studies involving 1 671 773 participants. Both current EC use (OR: 1.96, 95% CI: 1.73 to 2.23) and ever EC use (OR: 1.88, 95% CI: 1.59 to 2.21) could notably forecast depression. Pooled results also indicated that depression might significantly predict current EC use (OR: 1.36, 95% CI: 1.15 to 1.61) and ever EC use (OR: 1.53, 95% CI: 1.25 to 1.88). Conclusions: EC use may be a significant predictor of depression, and depression may be a significant predictor of EC use. This highlights the need for stronger mental health warnings on e-cigarettes and the integration of EC use screening into depression assessments. Implications: Considering the bidirectional link between EC use and depression, clinical screening, public health interventions, and stricter marketing regulation are crucial to mitigate risks. Future research should focus on the mechanisms and causal pathways of e-cigarettes and depression.
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