Interactions between sleep, movement and other non‐movement behaviours in the pathogenesis of childhood obesity
Bibliographic record
Abstract
Research examining the health effects of physical activity, sedentary behaviour and sleep on different health outcomes has largely been conducted independently or in isolation of the other behaviours. However, the fact that time is finite (i.e. 24 h) suggests that the debate on whether or not the influence of a single behaviour is independent of another one is conceptually incorrect. Time spent in one behaviour should naturally depend on the composition of the rest of the day. Recent evidence using more appropriate analytical approaches to deal with this methodological issue shows that the combination of sleep, movement and non-movement behaviours matters and all components of the 24-h movement continuum should be targeted to enhance health and prevent childhood obesity. The objective of this review is to discuss research investigating how combinations of physical activity, sedentary behaviour and sleep are related to childhood obesity. Emerging statistical approaches (e.g. compositional data analysis) that can provide a good understanding of the best 'cocktail' of behaviours associated with lower adiposity and improved health are also discussed. Finally, future research directions are provided. Collectively, it becomes clearer that guidelines and public health interventions should target all movement behaviours synergistically to optimize health of children and youth around the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".