The Association Between Meeting Physical Activity Guidelines and Chronic Diseases Among Canadian Adults
Bibliographic record
Abstract
BACKGROUND: Physical activity is associated with a reduced risk of chronic disease. This study describes the relationship between meeting the guidelines for physical activity described in Canada's Physical Activity Guide and heart disease, type 2 diabetes, hypertension, obesity, and low levels of general health. METHODS: Leisure-time energy expenditure (LTEE) was calculated from leisure-time physical activities reported by adults who participated in the 2007 Canadian Community Health Survey. Respondents were classified as meeting the guidelines for physical activity or not, and were stratified by sex into quartiles of LTEE. Logistic regression was used to determine the odds for all conditions associated with not meeting the guidelines and by quartile of LTEE, adjusting for covariates. RESULTS: The odds of type 2 diabetes, obesity, and fair/poor health were significantly higher among those not meeting the guidelines for both sexes and for high blood pressure among women. Significantly higher odds were seen between the lowest and highest quartiles of LTEE for type 2 diabetes and high blood pressure and across all quartiles for obesity and fair/poor health for both sexes. CONCLUSIONS: Canadian adults meeting the physical activity guidelines have lower odds of chronic diseases and fair/poor health than those not meeting the guidelines.
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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 | 0.002 |
| 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) | 0.004 | 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".