Prevalence of Overweight and Obesity among Aboriginal Populations in Canada: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Previous studies on overweight and obesity among Aboriginal peoples in Canada have been inconclusive. A systematic review was conducted on the prevalence of overweight and obesity among Canadian Aboriginal populations. Major bibliographic databases were searched for relevant studies published between January 1990 and June 2013. We reviewed 594 abstracts and included 41 studies in the meta-analyses. Using the heterogeneity test (Cochrane Q) results, the overall prevalence was estimated using fixed- or random-effects model. Non-adults (<18 yr) had a pooled prevalence of overweight and obesity at 29.8% (95%CI: 25.2-34.4) and 26.5% (95%CI: 21.8-31.3), respectively. The pooled prevalence of overweight and obesity among adults were 29.7% (95%CI: 28.2-31.2) and 36.6% (95%CI: 32.9-40.2), respectively. Adult males had higher overweight prevalence than females (34.6% vs. 26.6%), but lower obesity prevalence (31.6% vs. 40.6%). Non-adult girls had higher prevalence than boys [overweight: 27.6%; 95%CI: 22.6-32.7 vs. 24.7%; 95%CI: 19.0-30.5; obesity: 28.6%; 95%CI: 20.3-36.9 vs. 25.1%; 95%CI: 13.8-36.4]. Non-adult Inuit had the highest overweight and lowest obesity prevalence. Although adult Inuit had the lowest prevalence of overweight (28.7%; 95%CI: 27.3-30.2) and obesity (32.3%; 95%CI: 25.5-39.1), it was relatively high. This study highlights the need for nutritional intervention programs for obesity prevention among Aboriginal populations in Canada.
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.026 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".