Sedentary behavior, physical activity, and mental health in older adults: An isotemporal substitution model
Bibliographic record
Abstract
INTRODUCTION: Regular moderate-to-vigorous physical activity (MVPA) is associated with improved mental health, but the evidence for the effect of reducing sedentary behavior (SB) or increasing light PA (LPA) in older adults is lacking. Using isotemporal substitution (IS) models, the aim of this paper was to investigate the effect of substituting SB with LPA or MVPA on associations with mental health in older adults. METHODS: Data from 1360 older adults (mean age 75.18 years) in four countries were utilized. PA and SB was measured using ActiGraph wGT3X-BT + accelerometers worn for 7 days. Self-rated mental health was measured using the Hospital and Anxiety Depression Scale (HADS). IS models estimated cross-sectional associations when 30 minutes of one behavior was substituted with another. Models were adjusted for age, sex, marital status, and educational attainment. RESULTS: Substituting 30 minutes of SB with LPA (β -.37; 95% CI -0.42, -0.32) or MVPA (β -.14; 95% CI -0.21, -0.07) and substituting LPA with MVPA (β -.11; 95% CI -0.18, -0.04) were associated with improvements in anxiety. However, substituting 30 minutes of SB with LPA (β .55; 95% CI 0.49, 0.62) was associated with increased depression. CONCLUSION: Replacing 30 minutes of SB with LPA or MVPA was associated with improved anxiety symptoms in older adults. Greater benefits were observed when shifting SB and LPA to MVPA.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".