Sedentary time at school and work in Canada
Bibliographic record
Abstract
OBJECTIVES: High levels of sedentary time (ST) are associated with poor physical and mental health. Given that Canadians spend a large portion of their days at school and work, they may be important targets for reducing ST. Our objectives are to estimate the daily amount of school and work ST among Canadians, examine differences by subgroups, and determine associations with health. METHODS: Using the 2020 Canadian Community Health Survey Healthy Living Rapid Response module (N = 5242), the amount of time spent sitting while at school and work was estimated among youth (12-17 years) and adults (18-34 and 35-64 years). Differences by sociodemographics and 24-Hour Movement Guideline adherence were assessed with independent t-tests. Associations between school and work ST and health indicators were assessed using adjusted logistic regression. RESULTS: Canadian youth aged 12-17 years and adults aged 18-34 years reported an average of 4.5 and 5.2 h/day of school ST, respectively. Adults 18-34 years and 35-64 years reported an average of 3.9 and 4.0 h/day of work ST, respectively. School and work ST differed within several subgroups. Among adults 18-34 years, higher school ST was associated with a reduced odds of 'excellent/very good' mental health, whereas higher work ST was associated with a greater likelihood of reporting 'excellent/very good' general health. CONCLUSION: Canadian youth and working-age adults report an average of 4-5 h/day sedentary at school or work. This is the first study estimating school and work ST in a representative sample of Canadians and will aid in increasing awareness of setting-specific behaviours to better inform targeted interventions including addressing inequalities in ST.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".