Examining the effectiveness of a community-based physical activity intervention on health-related physical fitness in Indigenous adults
Bibliographic record
Abstract
Background: Improving the health and well-being of Indigenous peoples is a priority in Canada. A high prevalence of chronic diseases (such as cardiovascular disease, type 2 diabetes and obesity) has been reported among Indigenous communities. Despite the growing awareness of the health disparities faced by Indigenous communities compared to the general population, limited research exists on how to improve the cardio-metabolic health of Indigenous communities in culturally appropriate ways. Physical activity and fitness is well known to be of benefit for health. Objective: To evaluate the effectiveness of a community-based walking and running physical activity program on improving health-related physical fitness and other risk factors for cardiovascular disease and type 2 diabetes. Methods: Six Indigenous communities participating in the program hosted a health screening. A total of 87 adults of varying ages (44.6 ± 14.9 yr), health status and previous physical activity levels were included in this study. A trained Indigenous community member delivered weekly running and walking sessions. Aerobic fitness, muscular strength, body composition, blood pressure, total cholesterol, high density lipoprotein cholesterol, glucose, glycosylated haemoglobin and physical activity behaviour were assessed pre-and post-training. Results: Improvements in cardiorespiratory fitness and muscular strength were observed after the program. Health-related outcomes including waist circumference and blood pressure were reduced. Conclusion: A community-based physical activity program, led by an Indigenous community member, was effective at improving the cardio-metabolic health of Indigenous adults. Future research should consider modelling the design and implementation of this physical activity program when working with Indigenous communities to reduce cardio-metabolic diseases.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".