Regional Comparisons of Associations Between Physical Activity Levels and Cardiovascular Disease: The Story of Atlantic Canada
Bibliographic record
Abstract
BACKGROUND: Physical inactivity is an important risk factor for cardiovascular disease (CVD). Atlantic Canada is a region with lower physical activity (PA) levels and poorer CVD outcomes than the rest of Canada. Yet, within-region variation is expected. This study aimed to assess the association between PA and CVD and how this relationship varied on a regional level. METHODS: This cross-sectional study used data from the Atlantic Partnership for Tomorrow's Health (PATH) Study. The cohort included 823 CVD cases and 2469 age-, sex-, and province of residence-matched controls between the ages 35 and 69. Data collected included self-reported CVD and PA levels as well as information on sociodemographic characteristics, health status, and lifestyle behaviours. Simple and multiple logistic regression were used to assess the association between PA and CVD. RESULTS: High PA levels were associated with a 26% reduction in the mean probability of CVD compared with low PA levels across the total population. Compared with high PA levels, moderate and low PA levels were associated with increased odds of CVD across all 4 provinces. However, regional variation was observed, with higher odds of CVD for low-to-moderate PA levels in Newfoundland and Labrador and New Brunswick compared with Nova Scotia and Prince Edward Island. CONCLUSIONS: Atlantic Canadians experience regional inequalities in the association between PA and CVD. Future work needs to explore underlying pathways driving these regional differences, which may be the impetus for interventions that mitigate risk and CVD burden in populations of greatest need.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".