Dose–Response Relationships of Physical Activity with Metabolic Syndrome and Cardiometabolic Risk Factors in Korean Adults
Bibliographic record
Abstract
Background: Dose–response relationships between physical activity and metabolic syndrome (MetS) by sex and age are unclear.Purpose: We examined the associations of different intensities of physical activity with MetS by sex and age group.Methods: We analyzed 17,614 (56.5% women) adults from the Korean National Health and Nutrition Examination Survey, 2016–2018. Self-reported minutes per week of activities by intensity (walking, moderate, vigorous) were categorized by dose. Associations of activity intensities with MetS and its components were analyzed using one-way ANOVA and multinomial logistic regression models.Results: There were distinct patterns of associations of moderate-to-vigorous physical activity (MVPA) and walking categories with the MetS components by sex and age groups. Walking, moderate, and vigorous activities were associated with lower odds of MetS (independent of sex, age, and other covariates) in the highest category (≥225 min/week) when compared with the lowest category (<10 min/week) by 12%, 30%, and 40%, respectively.Discussion: MVPA and walking were favorably associated with MetS, but the associations varied by sex, age, and the intensity of physical activity.Translation to Health Education Practice: Our findings would be pragmatic for health education in providing evidence on the dose–response relationship between physical activity and cardiometabolic risk factors.
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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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".