National Trends in Asthma Prevalence among Adolescents in South Korea, 2007–2023: A National Representative Serial Study
Bibliographic record
Abstract
Introduction: Although previous studies have analyzed trends in asthma prevalence among adolescents before and during the COVID-19 pandemic, research specifically investigating asthma prevalence after the pandemic is lacking. Therefore, this study aims to analyze the long-term trends and the impact of the COVID-19 pandemic on the prevalence of asthma among Korean adolescents. Methods: Data were collected from a nationwide representative study (Korean Youth Risk Behavior Web-based Survey), conducted among adolescents aged 12–18 years from 2007 to 2023. To assess the impact of the COVID-19 pandemic, data were divided into three periods: pre-pandemic (2007–2019), intra-pandemic (2020–2022), and post-pandemic (2023). The prevalence of current asthma and variations in asthma prevalence across the pre-, intra-, and post-pandemic periods were analyzed using weighted linear regression and logistic models with 95% confidence intervals (CIs). Results: A total of 1,087,236 participants (559,840 males: 51.49%) were included in the analysis from 2007 to 2023. The weighted asthma prevalence exhibited slight fluctuations prior to the pandemic, with no notable overall changes. However, a substantial decline was observed during the intra-pandemic period compared to pre-pandemic (βdiff intra- versus pre-pandemic, −0.11; 95% CI: −0.12 to −0.09), followed by a slight weakening in the post-pandemic period (βdiff post- versus intra-pandemic, 0.07; 95% CI: 0.03–0.10). This trend persisted when analyzed by sex, with males exhibiting a higher prevalence than females throughout the entire period (versus females weighted odds ratio, 1.31; 95% CI: 1.29–1.34). Additionally, prior to the pandemic, the prevalence of asthma was higher among students in grades 7–9. However, after the pandemic began, students in grades 10–12 showed higher prevalence rates than their younger counterparts. The prevalence was also higher among adolescents who were overweight or obese, smoked, lived in facilities, had low household income, consumed fast food more than five times a week, experienced high stress levels, and reported low subjective recovery from fatigue. Conclusions: This comprehensive study suggests that the prevalence of asthma among adolescents varies with age and may be affected by the COVID-19 pandemic. Additionally, it identifies key factors contributing to asthma vulnerability, highlighting the importance of developing age-specific policies and targeted interventions for these at-risk groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".