Physical Activity Environments and Adherence to Health Guidelines in Postsecondary Students
Bibliographic record
Abstract
Sedentary lifestyle is one of the greatest contributors to global mortality. From a public health perspective, identifying modifiable factors that reduce sedentary is important. The objective is to examine associations between postsecondary students’ physical activity environments, including joint physical activity with parents during childhood, engagement in physical activity during adolescence, current parental physical activity, and adherence to screen time and physical activity recommendations during young adulthood. We used a community-based sample of 1,514 Canadian students, aged 17-22 years (60.8% female) enrolled during Fall 2021 and Winter 2022. Participants reported joint physical activity with parents during childhood, engagement in physical activity during adolescence, and current parental physical activity. Participants also self-reported screen time (hours/day), physical activity (minutes of moderate to vigorous intensity/week), and sociodemographic characteristics (age, sex, disability, employment status). Multivariate logistic regressions modeled associations between physical activity environments and adherence to screen time and physical activity recommendations while controlling for sociodemographic characteristics. Engagement in physical activity during adolescence showed a stronger relation with adherence to screen time and physical activity recommendations (odds ratio = 1.42, 95% CI, 1.09-1.83; odds ratio = 2.76, 95% CI, 2.11-3.60). Parental involvement in childhood physical activity was associated with adherence to screen time (odds ratio = 1.30, 95% CI, 1.03–1.64) and physical activity recommendations (odds ratio = 1.32, 95% CI, 1.03–1.68). There were no associations with current parental physical activity. Findings highlight the importance of family support for physical activity during childhood and continued activity during adolescence in promoting health.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".