Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8–11 year-old Danish children: a repeated-measures study
Bibliographic record
Abstract
BACKGROUND: Understanding fluctuations in lifestyle indicators is important to identify relevant time periods to intervene in order to promote a healthy lifestyle; however, objective assessment of multiple lifestyle indicators has never been done using a repeated-measures design. The primary aim was, therefore, to examine between-season and within-week variation in physical activity, sedentary behaviour, cardio-respiratory fitness and sleep duration among 8-11 year-old children. METHODS: A total of 1021 children from nine Danish schools were invited to participate and 834 accepted. Due to missing data, 730 children were included in the current analytical sample. An accelerometer was worn for 7 days and 8 nights during autumn, winter and spring, from which physical activity, sedentary time and sleep duration were measured. Cardio-respiratory fitness was assessed using a 10-min intermittent running test. RESULTS: The children had 5% more sedentary time, 23% less time in moderate-to-vigorous physical activity and 2% longer sleep duration during winter compared to spring and cardio-respiratory fitness was 4% higher during spring compared to autumn (P < 0.001). Sedentary time was higher and total physical activity, moderate-to-vigorous physical activity and sleep duration (boys only) were lower during weekends at all seasons (P ≤ 0.01). Intraclass correlation coefficients between seasons ranged from 0.47-0.74, leaving 45-78% to seasonal variation. CONCLUSIONS: Overall, sedentary time was higher and physical activity lower during winter and during weekends. The most accurate and unbiased estimates of physical activity came from autumn; however, the considerable intra-individual variation suggests that a single measurement may not adequately characterise children's habitual sleep and activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".