Physical fitness and body fatness are associated with mental health in Korean young adults: a cross sectional study
Bibliographic record
Abstract
Background: It has been recognized that body fatness and mental disorders have association, however very limited evidence have proved that physical fitness and mental health have association. Relationship between physical fitness and mental health in young adults has not been fully proved. The purpose of the study was to investigate the association between physical fitness, body fatness, and mental health in young adults.Methods: A total of 149 (97 males and 52 females) college students were included. Physical fitness (sit-ups, push-ups, 1 mile run/walk), and body mass index (BMI) was measured, and psychological questionnaires including life satisfaction, self-efficacy, the beck depression inventory (BDI), and adult self report (ASR) were administered. The levels of physical fitness and BMI were classified into tertile groups and were analyzed.Results: Female participants with the highest tertile of BMI had highest ASR score (p<0.05). Participants with highest level of physical fitness showed higher level of self-efficacy in both males and females (p<0.05). In both male and female, physical fitness was a significant predictor for self-efficacy (Male: β=0.35, p<0.05, Female: β =0.31, p<0.05).Conclusions: In conclusion, physical fitness and body fatness were associated with mental health. Especially, physical fitness, independent of BMI, was proved as significant indicator for mental health in young adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".