National Trends in the Prevalence of Self-Perceived Overweight Among Adolescents Between 2005 and 2022: Nationwide Representative Study
Bibliographic record
Abstract
BACKGROUND: Despite several studies on self-evaluation of health and body shape, existing research on the risk factors of self-perceived overweight is insufficient, especially during the COVID-19 pandemic. OBJECTIVE: This study aims to identify the risk factors affecting self-perceived overweight and examine how the prevalence of self-perceived overweight has changed before and during the COVID-19 pandemic. Specifically, we analyzed the impact of altered lifestyles due to COVID-19 on this phenomenon. METHODS: The data used in the study were obtained from middle and high school students who participated in the Korean Youth Risk Behavior Web-based Survey (N=1,189,586). This survey was a 2-stage stratified cluster sampling survey representative of South Korean adolescents. We grouped the survey results by year and estimated the slope in the prevalence of self-perceived overweight before and during the pandemic using weighted linear regression, as well as the prevalence tendencies of self-perceived overweight according to various risk factors. We used prevalence ratios to identify the risk factors for self-perceived overweight. In addition, we conducted comparisons of risk factors in different periods to identify their associations with the COVID-19 pandemic. RESULTS: The prevalence of self-perceived overweight was much higher than BMI-based overweight among 1,189,586 middle and high school participants (grade 7-12) from 2005 to 2022 (female participants: n=577,102, 48.51%). From 2005 to 2019 (prepandemic), the prevalence of self-perceived overweight increased (β=2.80, 95% CI 2.70-2.90), but from 2020 to 2022 (pandemic) it decreased (β=-0.53, 95% CI -0.74 to -0.33). During the pandemic, individuals with higher levels of stress or lower household economic status exhibited a more substantial decrease in the rate of self-perceived overweight. The prevalence of self-perceived overweight tended to be higher among individuals with poor academic performance, lower economic status, poorer subjective health, and a higher stress level. CONCLUSIONS: Our nationwide study, conducted over 18 years, indicated that self-perceived overweight decreased during the COVID-19 period while identifying low academic performance and economic status as risk factors. These findings suggest the need for policies and facilities to address serious dieting and body dissatisfaction resulting from self-perceived overweight by developing counseling programs for adolescents with risk factors such as lower school performance and economic status.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".