Physical activity level and stroke risk in <scp>US</scp> population: A matched case–control study of 102,578 individuals
Bibliographic record
Abstract
BACKGROUND: Stroke has been linked to a lack of physical activity; however, the extent of the association between inactive lifestyles and stroke risk has yet to be characterized across large populations. PURPOSE: This study aimed to explore the association between activity-related behaviors and stroke incidence. METHODS: Data from 1999 to 2018 waves of the concurrent cross-sectional National Health and Nutrition Examination Survey (NHANES) were extracted. We analyzed participants characteristics and outcomes for all participants with data on whether they had a stroke or not and assessed how different forms of physical activity affect the incidence of disease. RESULTS: Of the 102,578 individuals included, 3851 had a history of stroke. A range of activity-related behaviors was protective against stroke, including engaging in moderate-intensity work over the last 30 days (OR = 0.8, 95% CI = 0.7-0.9; P = 0.001) and vigorous-intensity work activities over the last 30 days (OR = 0.6, 95% CI = 0.5-0.8; P < 0.001), and muscle-strengthening exercises (OR = 0.6, 95% CI = 0.5-0.8; P < 0.001). Conversely, more than 4 h of daily TV, video, or computer use was positively associated with the likelihood of stroke (OR = 11.7, 95% CI = 2.1-219.2; P = 0.022). CONCLUSION: Different types, frequencies, and intensities of physical activity were associated with reduced stroke incidence, implying that there is an option for everyone. Daily or every other day activities are more critical in reducing stroke than reducing sedentary behavior duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".