Effectiveness of programs aimed at obesity prevention among Indigenous children: A systematic review
Bibliographic record
Abstract
Given the significant health burden of childhood obesity, it is imperative that effective programs be better understood. When evaluating obesity prevention efforts, one must recognize the contextual factors which drive the disproportionate risk of obesity between populations. This systematic review sought to understand if programs aimed at obesity prevention and/or the promotion of healthy lifestyle behaviours for Indigenous children are effective. We conducted a search using Medline, EMBASE, PsychINFO, ERIC, CINAHL and iPORTAL databases from inception to August 13, 2019. We included experimental and quasi-experimental studies. The main outcomes of interest were change in anthropometrics, nutrition or physical activity. Our narrative synthesis included an assessment of study quality using the Effective Public Health Practice Project Quality assessment tool. A total of 34 studies met selection criteria. Most studies used a quasi-experimental design (n = 25) and were assessed as low to moderate quality (n = 32). Three studies showed a significant change in anthropometric measures, 14 studies demonstrated at least one significant nutrition-related behaviour or dietary-pattern change, and six studies demonstrated a significant impact on physical activity. This systematic review of programs to prevent obesity among Indigenous children finds a limited impact on anthropometric measurements. Future studies must prioritize Indigenous knowledge and ways of knowing to lead all phases of development, implementation, and evaluation of programs.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".