Influencing Factors for Cardiometabolic Risk in Korean Adolescents Based on 2010–2015 Data From the Korea National Health and Nutrition Examination Survey
Bibliographic record
Abstract
BACKGROUND: High academic stress and physical inactivity in Korean adolescents increase cardiometabolic risk factors, such as obesity, making it crucial to identify the factors influencing their risk. OBJECTIVE: Our aims were to determine differences in the prevalence of metabolic syndrome and its 5 components in Korean adolescents according to gender and to identify the influencing factors for cardiometabolic risk (individual risk factor ≥ 1). METHODS: Data related to adolescents from the Korean National Health and Nutrition Examination Survey (2010-2015) were assessed. Bivariate analyses to compare distribution and logistic regression analyses to examine the influencing factors were performed. RESULTS: Cardiometabolic risk (≥1 risk factor) was found in 33.2% and 32.6% of male and female adolescents, respectively, and metabolic syndrome (≥3 risk factors) was found in 2.0% and 2.3%, respectively. Among male adolescents, cardiometabolic risk was 1.66 times higher for the group that did not perform strength exercises ( P = .007). For female adolescents, the cardiometabolic risk was 2.44 times higher in 16- to 18-year-olds than in 12- to 15-year-olds ( P < .001) and 1.50 times higher in the non-aerobic-exercise group ( P = .030). Central obesity (waist-to-height ratio ≥ 0.47) increased cardiometabolic risk by 5.71 and 13.91 times in male and female adolescents, respectively ( P < .001). CONCLUSION: To reduce cardiometabolic risk profiles and future cardiovascular risk in Korean adolescents, school-based physical activity programs should be actively provided not only for students with central obesity but also for students who lack aerobic or strength exercises.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".