Cross-sectional association between 24-hour movement guidelines and depressive symptoms in Chinese university students
Bibliographic record
Abstract
Background The world’s first 24-h movement guidelines for adults were released on 15 October 2020 in Canada, though evidence of their associations with health indicators in young adults is sparse. This study aimed to report the prevalence of meeting the 24-h movement guidelines and associations with depressive symptoms in a sample of Chinese university students. Methods Cross-sectional data from 1,793 Chinese university students (mean age = 20.7 years, 63.6% female) were used. Sociodemographic information, movement behaviors (physical activity, sedentary behavior, and sleep duration), and depressive symptoms were collected using a self-reported questionnaire. Results The prevalence of meeting the 24-h movement guidelines was 27.8% in Chinese university students. Logistic regression results show that compared to those who met the 24-h movement guidelines, odds ratio (OR) for depressive symptoms in those who met fewer recommendations contained in the 24-h movement guidelines were significantly higher (OR for none = 3.4, 95% CI [2.1–5.5], p < 0.001; OR for one = 2.7, 95% CI [2.0–3.8], p < 0.001; OR for two = 1.5, 95% CI [1.1–2.1], p = 0.013). Conclusion The prevalence of meeting the 24-h movement guidelines in Chinese university students was relatively low and should be enhanced through multiple strategies. Meeting the 24-h movement guidelines was associated with lower risk for depression in Chinese young adults. It is suggested that moving more, sitting less and sleeping well in this population may reduce the occurrence of depression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".