Combinations of physical activity, sedentary behaviour and sleep: relationships with health indicators in school-aged children and youth
Bibliographic record
Abstract
The purpose of this systematic review was to determine how combinations of physical activity (PA), sedentary behaviour (SB), and sleep were associated with important health indicators in children and youth aged 5-17 years. Online databases (MEDLINE, EMBASE, SPORTdiscus, CINAHL, and PsycINFO) were searched for relevant studies examining the relationship between time spent engaging in different combinations of PA, SB, and sleep with the following health indicators: adiposity, cardiometabolic biomarkers, physical fitness, emotional regulation/psychological distress, behavioural conduct/pro-social behaviour, cognition, quality of life/well-being, injuries, bone density, motor skill development, and self-esteem. PA had to be objectively measured, while sleep and SB could be objectively or subjectively measured. The quality of research evidence and risk of bias for each health indicator and for each individual study was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. A total of 13 cross-sectional studies and a single prospective cohort study reporting data from 36 560 individual participants met the inclusion criteria. Children and youth with a combination of high PA/high sleep/low SB had more desirable measures of adiposity and cardiometabolic health compared with those with a combination of low PA/low sleep/high SB. Health benefits were also observed for those with a combination of high PA/high sleep (cardiometabolic health and adiposity) or high PA/low SB (cardiometabolic health, adiposity and fitness), compared with low PA/low sleep or low PA/high SB. Of the 3 movement behaviours, PA (especially moderate- to vigorous-intensity PA) was most consistently associated with desirable health indicators. Given the lack of randomized trials, the overall quality of the available evidence was low.
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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".