doi:10.5402/2012/816846 Research Article Metabolic Syndrome in Canadian Adults and Adolescents: Prevalence and Associated Dietary Intake
Bibliographic record
Abstract
Copyright © 2012 Solmaz Setayeshgar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Metabolic syndrome (MetS) includes five chronic disease risk factors which doubles the risk of CVD and increases the risk of diabetes fivefold. Objective. To determine the prevalence of MetS and its risk factors in Canadians (12–79 y) and to compare the dietary intake in Canadians with MetS and without MetS. Subjects and Methods. Cycle 1 of Canadian health measures survey, CHMS data, 2007–2009, was used. To identify MetS cases, the most recent criteria were used for adults and adolescents. Ethnical cut points for waist measurement were applied for adults. Results and Conclusion. The prevalence of MetS among 12–79 y Canadians was 18.31 % with the lowest prevalence in adolescents (3.50%). Using ethnical cut points to define abdominal obesity increased the prevalence of MetS by 0.5 % in adults. The most prevalent defining component of MetS in Canadians identified with MetS was abdominal obesity. Reduced HDL-C was equally prevalent among adolescents. Canadians with MetS consumed significantly more diet soft drinks, but less dairy products, dietary fat, and sugar-sweetened beverages compared to Canadians without MetS. Known cases of diabetes with MetS had healthier beverage choices compared to individuals without the diagnosis of diabetes, indicating adherence to nutrition recommendations. 1.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.608 | 0.279 |
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".