Impact of physical activities, sedentarism, and sleep on depression and psychological distress-prospective findings of the Canadian longitudinal study on aging
Bibliographic record
Abstract
BACKGROUND: The interrelation of physical activity, sedentarism, and sleep concerning the onset and persistence of depression is underexplored. This study examines the joint effect of time spent in these activities on clinically relevant depressive symptoms (CRDS). It also examines the influence of history of depressive disorder and whether results extend to serious psychological distress (SPD). METHODS: Longitudinal data from the Canadian Longitudinal Study on Aging, including 25,665 middle-aged and older (45-85 years) people, were used. Self-reported questionnaires were used for time spent walking, moderate physical activity (MPA), vigorous physical activity (VPA), sitting, and sleep. CRDS and SPD were assessed with the 10-item Center for Epidemiologic Studies Depression scale and the Kessler Psychological Distress scale, respectively. Logistic regression models, adjusted for covariates, estimated the association between activities and mental health outcomes. RESULTS: At baseline, 15 % experienced CRDS, and 11 % SPD. Those with low activity patterns (high sitting levels, low levels of walking, MPA, VPA, and short sleep) were more likely to develop CRDS and to retain it than those with medium-high activity patterns. These patterns mostly also applied to SPD. Among those with history of depression, sedentary behavior and sleep were less strongly related to CRDS, but walking, MPA and VPA were equally strongly related. CONCLUSIONS: Those with low activity patterns (high levels of sitting, little time spent in physical activities) had the worst mental health outcomes, while participants with higher activity level are less likely to continue or develop CRDS and SPD. Short sleep should be targeted for both mental conditions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".