Association of active and passive smoking with adolescent asthma: a systematic review and meta-analysis

OBJECTIVE: To synthesize evidence on the association of active or passive smoking with asthma in adolescents. DATA SOURCES: A comprehensive search of Embase, PubMed, Scopus, and Web of Science were conducted from inception to January 2026. Only human studies published in English were included. STUDY SELECTION: Observational studies evaluating active or passive smoking in adolescents aged 10-19 years were eligible. Studies reporting odds ratio (OR), hazard ratio (HR), relative risk (RR), prevalence ratio (PR), incidence rate ratio (IRR), or prevalence odds ratio (POR) with 95% confidence interval (95% CI) were included. Two reviewers independently screened studies. DATA EXTRACTION: Key study characteristics, including authors, year, setting, age range, design, sample size, exposure type, asthma outcome, adjusted covariates, and effect estimates, were independently extracted and cross-verified by two reviewers, with discrepancies resolved by consensus. DATA SYNTHESIS: Seventy-seven studies met inclusion criteria, with 72 contributing to meta-analysis. Active smoking (adjusted odds ratio [aOR] = 1.16; 95% CI: 1.13-1.20), cigarette use (aOR = 1.19; 95% CI: 1.13-1.26), e-cigarette use (aOR = 1.13; 95% CI: 1.10-1.16), and passive smoking (aOR = 1.23; 95% CI: 1.17-1.29) were all significantly associated with asthma. Parental smoking conferred elevated risk (aOR = 1.85; 95% CI: 1.33-2.36), and exposure from friends showed the strongest association (aOR = 3.70; 95% CI: 1.63-5.78). CONCLUSIONS: Both active and passive smoking significantly increase asthma risk in adolescents, with both cigarette use and e‑cigarette use showing adverse associations. Friend smoking represents the most potent passive exposure. According to the GRADE assessment, the certainty of evidence for these associations was rated as very low, reflecting limitations in study design, confounder adjustment, and exposure measurement. Future studies should incorporate longitudinal designs, validated biomarkers, and standardized outcome measures to better characterize dose-response patterns and underlying mechanisms.