Prevalence of metabolic syndrome in the Canadian adult population
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome refers to a constellation of conditions that increases a person's risk of diabetes and cardiovascular disease. We describe the prevalence of metabolic syndrome and its components in relation to sociodemographic factors in the Canadian adult population. METHODS: We used data from cycle 1 of the Canadian Health Measures Survey, a cross-sectional survey of a representative sample of the population. We included data for respondents aged 18 years and older for whom fasting blood samples were available; pregnant women were excluded. We calculated weighted estimates of the prevalence of metabolic syndrome and its components in relation to age, sex, education level and income. RESULTS: The estimated prevalence of metabolic syndrome was 19.1%. Age was the strongest predictor of the syndrome: 17.0% of participants 18-39 years old had metabolic syndrome, as compared with 39.0% of those 70-79 years. Abdominal obesity was the most common component of the syndrome (35.0%) and was more prevalent among women than among men (40.0% v. 29.1%; p=0.013). Men were more likely than women to have an elevated fasting glucose level (18.9% v. 13.6%; p=0.025) and hypertriglyceridemia (29.0% v. 20.0%; p=0.012). The prevalence of metabolic syndrome was higher among people in households with lower education and income levels. INTERPRETATION: About one in five Canadian adults had metabolic syndrome. People at increased risk were those in households with lower education and income levels. The burden of abdominal obesity, low HDL (high-density lipoprotein) cholesterol and hypertriglyceridemia among young people was especially of concern, because the risk of cardiovascular disease increases with age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".