Association Between Excess Leisure Sedentary Time and Risk of Stroke in Young Individuals
Bibliographic record
Abstract
Background and Purpose: The association between physical activity (PA) and lower risk of stroke is well established, but the relationship between leisure sedentary time and stroke is less well studied. Methods: We used 9 years of the Canadian Community Health Survey between 2000 and 2012 to create a cohort of healthy individuals without prior stroke, heart disease, or cancer. We linked to hospital records to determine subsequent hospitalization or emergency department visit for stroke until December 31, 2017. We quantified the association between self-reported leisure sedentary time (categorized as <4, 4 to <6, 6 to <8, and 8+ hours/day) and risk of stroke using Cox regression models and competing risk regression, assessing for modification by PA, age, and sex and adjusting for demographic, vascular, and social factors. Results: There were 143 180 people in our cohort and 2965 stroke events in follow-up. Median time from survey response to stroke was 5.6 years. There was a 3-way interaction between leisure sedentary time, PA, and age. The risk of stroke with 8+ hours of sedentary time was significantly elevated only among individuals <60 years of age who were in the lowest PA quartile (fully adjusted hazard ratio, 4.50 [95% CI, 1.64–12.3]). The association was significant across multiple sensitivity analyses, including adjustment for mood disorders and when accounting for the competing risk of death. Conclusions: Excess leisure sedentary time of 8+ hours/day is associated with increased risk of long-term stroke among individuals <60 years of age with low PA. These findings support efforts to enhance PA and reduce sedentary time in younger individuals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".