The Benefits Of Community-based Walking And Running Programs For Aboriginal Peoples
Bibliographic record
Abstract
Aboriginal populations in North America currently experience increased rates of cardiovascular disease and diabetes. Lifestyle changes over the past 50 years (including significant reductions in physical activity levels) have been accompanied by increased prevalence of these chronic conditions. PURPOSE: To evaluate the effectiveness of community-based walking and running programs for improving the health of Aboriginal peoples. METHODS: We assessed self-report physical activity and direct measures of height, weight, blood pressure, lipid profile, blood glucose, and waist girth before and after three forms of 13 week physical activity interventions. The 280 Aboriginal participants self-selected either walking, learn to run, or run faster programs. RESULTS: As a population there was a high prevalence of physical inactivity (48%), overweight and obesity (via BMI; 78%), central obesity (via waist girth; 65%), and hypertension (21%). All participants experienced improvements with training, including all ages, genders and geographic locations. Over the training program, significant improvements in health measures were recorded including waist girth, systolic blood pressure, total cholesterol (TC) and physical activity. Physical activity improvements included a 34.3% increase in the prevalence of participants meeting Health Canada physical activity guidelines. There were also trends for improvements in weight, diastolic blood pressure, high density lipoprotein cholesterol (HDL) and TC:HDL ratios. Both male and female participants and all age groups experienced similar improvements in health measures and increases in physical activity with training. These improvements also extend to all three physical activity training programs as well as participants residing in rural and urban regions, all 4 regions of the province, and both on and off reserve locations. CONCLUSIONS: Within this population, significant improvements in health measures were observed over the 13 week training program. All classifications of Aboriginal participants experienced health improvements with this program.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".