Study design and data source

This study is a secondary analysis of cross-sectional data from the Korea Youth Risk Behavior Web-based Survey (KYRBS), conducted annually from 2022 to 2024 by the Korea Disease Control and Prevention Agency (KDCA). The KYRBS employs a stratified, multistage, cluster sampling design to obtain a nationally representative sample of middle and high school students in South Korea. Data are collected via anonymous, self-administered online questionnaires, ensuring confidentiality and minimizing reporting bias. The overall student response rate for the KYRBS during 2022–2024 was approximately 92.2%⁹.

Study population

The analytic sample included 159383 students in grades 7–12 who provided complete information on tobacco use, asthma diagnosis, and relevant covariates. Participants with missing or inconsistent responses for key variables were excluded from the analysis. Sampling weights were applied to account for the complex survey design and generate estimates representative of the national adolescent population.

Measures

Tobacco use patterns

Current use of CCs, ECs, and HTPs was defined as any use within the past 30 days. Participants were categorized into eight mutually exclusive groups: non-users; CC-only; EC-only; HTP-only; CC+EC; CC+HTP; EC+HTP; and CC+EC+HTP¹⁰.

Asthma prevalence

Asthma was defined as a self-reported physician diagnosis within the past 12 months.

Covariates

Models adjusted for sex, grade, household income, academic performance, alcohol use, physical activity, breakfast habits, perceived stress, and secondhand smoke exposure at home. Breakfast habits were included as a proxy for overall health-related behaviors, which have been previously associated with respiratory and allergic outcomes in adolescents.

Statistical analysis

All analyses accounted for the complex sampling design of the Korea Youth Risk Behavior Survey (KYRBS), including stratification, clustering, and survey weights, using the Complex Samples module in IBM SPSS Statistics for Windows, version 25.0¹⁵. Descriptive statistics were used to summarize demographic characteristics, tobacco use patterns, and asthma prevalence. Chi-squared tests were conducted to assess bivariate associations between tobacco use categories and asthma status.

Multivariable logistic regression models were fitted to adjusted associations between tobacco use patterns and asthma prevalence, with non-users serving as the reference group. Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) are reported. All multivariable models were adjusted for sex, grade, household income, academic performance, alcohol use, physical activity, breakfast habits, perceived stress, and exposure to secondhand smoke at home. Interaction terms between tobacco product types were examined but excluded from the final models because they were not statistically significant. Model fit was assessed using the Hosmer–Lemeshow goodness-of-fit test, and multicollinearity was evaluated using variance inflation factors (VIF), with all values <2.5. Statistical significance was defined as p<0.05.

Although prevalence ratios can be estimated using alternative approaches such as robust Poisson regression, we applied multivariable logistic regression to ensure analytic consistency with prior KYRBS-based studies and comparability with existing literature. Given that odds ratios may overestimate prevalence ratios when the outcome is not rare, findings were interpreted primarily in terms of the direction and relative strength of associations rather than precise effect magnitude.

Figure 1

Adjusted odds ratio for asthma by tobacco use pattern

Validity and reliability

The KYRBS employs standardized survey instruments that have been previously validated and shown to have acceptable reliability among Korean adolescents. In a national test–retest reliability study of the KYRBS questionnaire, core self-reported health behavior items, including tobacco use and physician-diagnosed asthma, demonstrated moderate to high reliability, with kappa ≥0.41 and several items with kappa ≥0.81¹⁶. The design and methodology of the KYRBS, including its complex sampling procedures and nationally representative framework, have been described in detail elsewhere¹⁷. Data collection follows rigorous protocols, including pilot testing, data quality monitoring, and standardized training for survey administrators, which support the external validity and generalizability of the findings.

This secondary analysis of publicly available, anonymized data was reviewed by the Institutional Review Board of the Ministry of Health and Welfare and was granted exemption from full ethical review (IRB No.: P01-202507-01-030).

Demographic and behavioral characteristics

Table 1 summarizes the demographic characteristics, tobacco use patterns, alcohol consumption, and asthma prevalence of the study population. Among the 159383 adolescents included in the analysis, the overall prevalence of physician-diagnosed asthma within the past 12 months was 1.7%.

The sample comprised 51.5% boys and 48.5% girls, in grades 7–12. Academic performance was reported as high by 39.3% of participants, middle by 28.6%, and low by 32.1%. Household economic status was categorized as high in 45.3% of adolescents, middle in 43.9%, and low in 10.8%. With respect to tobacco use behavior, 95.0% of participants reported no use of tobacco products. Exclusive use of combustible cigarettes (CCs), electronic cigarettes (ECs), and heated tobacco products (HTPs) was reported by 1.4%, 0.5%, and 0.1% of adolescents, respectively. Dual use of ECs and HTPs accounted for 1.0% of the sample, and 1.3% reported concurrent use of all three tobacco products. In addition, 13.3% of students reported current alcohol consumption.

Association between tobacco use and asthma

As shown in Table 2, significant differences in asthma prevalence were observed according to sex, grade, household economic status, perceived stress, breakfast skipping, physical activity, tobacco use behavior, exposure to secondhand smoke at home, and alcohol consumption (all p<0.001). Asthma prevalence was higher among boys than girls and was more common among adolescents from low-income households compared with those from high-income households. Adolescents reporting perceived stress, skipping breakfast, exposure to secondhand smoke at home, or current alcohol consumption showed a higher prevalence of asthma. Marked differences in asthma prevalence were also observed across tobacco use categories, with higher proportions of asthma among adolescents reporting use of ECs and HTPs, particularly among those using multiple tobacco products.

Multivariable logistic regression analysis

Results of the multivariable logistic regression analyses are presented in Table 3. After adjustment for sex, grade, household economic status, perceived stress, breakfast skipping, physical activity, tobacco use behavior, exposure to secondhand smoke at home, and alcohol use, tobacco use patterns were strongly associated with asthma prevalence.

Compared with non-users, the adjusted odds ratios (AORs) for asthma were 1.34 (95% CI: 1.28–1.39) for CC-only users, 4.34 (95% CI: 4.17–4.51) for EC-only users, and 9.16 (95% CI: 8.63–9.72) for HTP-only users. Dual use of ECs and HTPs was associated with the highest odds of asthma (AOR=13.72; 95% CI: 13.25–14.22), while triple use of CCs, ECs, and HTPs was also associated with elevated odds (AOR=5.15; 95 % CI : 5.02–5.28).

In addition to tobacco use behavior, exposure to secondhand smoke at home (AOR=1.49; 95% CI: 1.47–1.51), current alcohol consumption (AOR=1.16; 95% CI: 1.14–1.18), perceived stress (AOR=1.06; 95% CI: 1.04–1.07), and physical activity (AOR=1.16; 95% CI: 1.14–1.18) were associated with higher odds of asthma.

These results indicate a graded association between patterns of tobacco product use and asthma prevalence among Korean adolescents. In particular, concurrent use of ECs and HTPs was associated with higher odds of asthma compared with single-product use. This pattern suggests a potential cumulative burden associated with exposure to multiple aerosol-generating products, rather than a statistically defined interaction effect. These findings underscore the substantial respiratory health burden associated with emerging tobacco products and secondhand smoke exposure among youth.

Limitations

Several limitations of this study should be acknowledged. First, the cross-sectional design precludes causal inference regarding the observed associations between tobacco product use and asthma. Second, both asthma status and tobacco use were assessed using self-reported measures, which may be subject to misclassification bias due to recall error or social desirability, potentially leading to non-differential misclassification. Third, although we adjusted for a wide range of sociodemographic, behavioral, and environmental factors, residual confounding by unmeasured variables – such as intensity and duration of tobacco use, nicotine dependence, or prior combustible cigarette use – cannot be excluded. In addition, the findings may not be fully generalizable to adolescents who are not enrolled in school or to settings with different cultural and regulatory contexts. Finally, reverse causality cannot be ruled out with this cross-sectional design. Despite these limitations, the present study provides large-scale, nationally representative evidence of an association between emerging tobacco product use and asthma prevalence among adolescents, underscoring the importance of continued surveillance and youth-focused tobacco control and prevention efforts.