Amount and timing of physical activity in relation to sleep quality in the general middle-aged Dutch population: A cross-sectional analysis
Bibliographic record
Abstract
To examine whether the amount and timing of moderate-to-vigorous physical activity (MVPA) was associated with sleep quality and duration in the general population. This is a cross-sectional analysis of data of a Dutch cohort collected between 2008 and 2012. Timing of physical activity (measured using an accelerometer) was categorized as performing most MVPA in morning (06:00–12:00), afternoon (12:00–18:00), evening (18:00–00:00), or even distribution of MVPA over the day (reference). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). We estimated OR with 95 % CI of a poor score on individual PSQI components and global PSQI score using logistic regression while adjusting for relevant covariates. We analyzed 736 participants, of whom 57 % women, aged 56 (6) years, BMI 26.1 (4.2) kg/m 2 ). Amount of MVPA (hours/day) was associated with lower odds of fatigue-related dysfunction during daytime (OR: 0.54 0.32–0.94), but not with global PSQI score. Participants who performed most MVPA in the morning were less likely to report sleep disturbances (OR: 0.23, 95 % CI: 0.09–0.60), compared to participants with an even distribution of. Timing of MVPA was not associated with global PSQI score nor other components and CI were large. Differences in sleep quality are unlikely to be biological mechanisms underlying the previously shown associations between timing of physical activity and metabolic health. • Moderate-vigorous physical activity is associated with daytime functioning. • Mainly, no associations of timing of moderate-vigorous activity with sleep quality. • Morning moderate-vigorous activity only was associated with fewer sleep disturbances. • As confidence intervals of our findings were wide, larger studies are needed.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".