A Comparison of Meeting Physical Activity and Screen Time Recommendations between Canadian Youth Living in Rural and Urban Communities: A Nationally Representative Cross-Sectional Analysis
Bibliographic record
Abstract
Meeting the physical activity (PA) and recreational screen time recommendations for children and young people is associated with several health benefits. The purpose of this study was to compare the odds of meeting PA and recreational screen time recommendations between the Canadian youth living in urban versus rural communities. We analyzed nationally representative cross-sectional data collected as part of the 2017-2018 cycles of the Canadian Community Health Survey among young people aged 12-17 years. PA and screen time were self-reported. Sex-specific multivariable logistic regression models were used to estimate the odds of meeting individual and combined PA and recreational screen time recommendations by rural and urban status after adjusting for individual, socioeconomic, and seasonal covariates. The odds of meeting the PA recommendation were not statistically significantly different among males (OR = 1.01, 95% CI: 0.86-1.18) or females (OR 1.05, 95% CI: 0.99-1.11) living in urban versus rural communities. The odds of meeting the recreational screen time recommendations were statistically significantly lower among male (OR = 0.71, 95% CI: 0.65-0.77) and female (OR = 0.71, 95% CI: 0.59-0.86) youth living in urban compared to those in rural communities. The odds of meeting the combined PA and screen time recommendations were statistically significantly lower among urban males (OR = 0.75, 95% CI: 0.71-0.81) but not females (OR = 0.82, 95% CI: 0.58-1.15) than those from rural communities. These findings suggest that residential context (i.e., urban versus rural) may have a differential impact on meeting the combined PA and screen time recommendations among the male and female Canadian youth. Future research should investigate these differences using device-based measures.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".