Physical activity, sedentary behaviour and sleep in Canadian children: parent-report versus direct measures and relative associations with health risk.
Bibliographic record
Abstract
BACKGROUND: The accurate measurement of time devoted to physical activity, sedentary pursuits and sleep is difficult and varies considerably between surveys. This has implications for population surveillance and understanding how these variables relate to health. METHODS: This sample of children (n = 878) was from the 2007 to 2009 Canadian Health Measures Survey. Moderate- to-vigorous physical activity (MVPA), sedentary behaviour and sleep duration were assessed using both a questionnaire and an accelerometer. This article compared parent-reported and directly measured physical activity, sedentary behaviour and sleep, and examined their associations, alone or in combination, with selected health markers in children aged 6 to 11. RESULTS: According to parent reports, the children in this study had an average of 105 minutes of MVPA, 2.5 hours of screen time and 9.7 hours of sleep per day; accelerometers recorded 63 minutes of MVPA, 7.6 hours of sedentary time and 10.1 hours of sleep per day. MVPA, measured by parent-report or accelerometry, was significantly associated with body mass index. In a regression model, directly measured MVPA and sleep were significantly associated with body mass index, and directly measured MVPA was significantly associated with waist circumference. Parent-reported screen time approached a significant association with body mass index. INTERPRETATION: Time estimates and associations with health markers varied between parent-reported and directly measured physical activity, sedentary behaviour and sleep in children. These differences are important to understand before the two measurement techniques can be used interchangeably in research and health surveillance.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".