Prevalence of metabolic alterations predictive of cardiovascular disease risk in the Québec population.
Bibliographic record
Abstract
BACKGROUND: It is well established that cardiovascular diseases (CVD) are the most important cause of morbidity and mortality in North America and in industrialized countries. Furthermore, the presence of CVD risk factors is widespread in Canada, and two-thirds of adult Canadians present at least one traditional risk factor for CVD. OBJECTIVE: To quantify the prevalence of metabolic alterations predictive of an increased risk of CVD in a representative sample of the Québec population. METHODS: A representative sample of the Québec population was obtained through the Québec Health Survey 1990. The cohort of 1844 subjects (907 men and 937 women), aged from 18 to 74 years, completed the evaluation, which consisted of interviews, validated questionnaires for personal and family history of CVD risk factors, and a physical examination. Anthropometric measurements, blood pressure, fasting plasma lipoprotein-lipid levels as well as fasting glucose and insulin concentrations were obtained. RESULTS: Thirty one per cent of the Québec population had a normal body weight defined by body mass index (BMI) less than 25 kg/m2 with a healthy metabolic profile (glycemia less than 6.1 mmol/L, total cholesterol less than 5.2 mmol/L, low density lipoprotein-cholesterol less than 3.4 mmol/L, triglycerides less than 2.3 mmol/L and high density lipoprotein-cholesterol greater than 0.90 mmol/L). On the other hand, 28% of the population was treated for known metabolic chronic diseases (CVD, diabetes, dyslipidemias and hypertension), whereas the remaining 33% of the Québec population (BMI greater than 25 kg/m2) were characterized by an altered metabolic profile predictive of an increased CVD risk. Furthermore, 75% of men and 70% of women with an altered metabolic profile presented at least two CVD risk factors. Overall, women tended to display a significantly healthier metabolic risk profile than men (P<0.05). CONCLUSIONS: According to our results, only 31% of the Québec population is nonobese without major alterations in their metabolic risk profile. Indeed, 61% of Quebecers are either characterized by chronic diseases or by an altered metabolic profile increasing their risk for the development of CVD and type 2 diabetes. Such a high prevalence should be a source of concern justifying the development of simple screening tools for early identification of the asymptomatic carriers of this cluster of metabolic abnormalities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".