Physical activity trails in an urban setting and cardiovascular disease morbidity and mortality in Winnipeg, Manitoba, Canada: a study protocol for a natural experiment
Bibliographic record
Abstract
INTRODUCTION: Aspects of the built environment that support physical activity are associated with better population health outcomes. Few experimental data exist to support these observations. This protocol describes the study of the creation of urban trials on cardiovascular disease (CVD)-related morbidity and mortality in a large urban centre. METHODS AND ANALYSIS: Between 2008 and 2010, the city of Winnipeg, Canada, built four, paved, multiuse (eg, cycling, walking and running), two-lane trails that are 5-8 km long and span ~60 neighbourhoods. Linking a population-based health data with census and environmental data, we will perform an interrupted time series analysis to assess the impact of this natural experiment on CVD-related morbidity and mortality among individuals 30-65 years of age residing within 400-1200 m of the trail. The primary outcome of interest is a composite measure of incident major adverse CVD events (ie, CVD-related mortality, ischaemic heart disease, stroke and congestive heart failure). The secondary outcome of interest is a composite measure of incident CVD-related risk factors (ie, diabetes, hypertension and dyslipidaemia). Outcomes will be assessed quarterly in the 10 years before the intervention and 5 years following the intervention, with a 4-year interruption. We will adjust analyses for differences in age, sex, ethnicity, immigration status, income, gentrification and other aspects of the built environment (ie, greenspace, fitness/recreation centres and walkability). We will also assess trail use and trail user profiles using field data collection methods. ETHICS AND DISSEMINATION: Ethical approvals for the study have been granted by the Health Research Ethics Board at the University of Manitoba and the Health Information Privacy Committee within the Winnipeg Regional Health Authority. We have adopted an integrated knowledge translation approach. Information will be disseminated with public and government partners. TRIAL REGISTRATION NUMBER: NCT04057417.
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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 | 0.023 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".