Early evaluation of the metabolic syndrome in Bucaramanga, Colombia
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome (MS) is one of the conditions that increase the risk of developing cardiovascular diseases (CVD) and type-2 diabetes in the early future if it appears during childhood or adolescence. The purpose of the study to compare the MS prevalence of MS estimated in a representative sample of school-age population in Bucaramanga, Colombia, and the MS prevalence estimated in a subsample from the same population in the adolescent stage. METHODS: An analytical cross-sectional survey (in the adolescent stage) (n=494) was carried out, nested in a population-based cohort assembled when children were of school age (n=1,282). Selection employed a bi-stage randomized sampling per neighborhoods and houses across the city. Sociodemographic and anthropometric variables, as well as cardiometabolic factors were analyzed in accordance with their distribution, and statistical significance tests were applied according to each case. MS was determined using the Adult Treatment Panel III (ATP III) and International Diabetes Federation (IDF) criteria. RESULTS: Estimated MS prevalence in school age according to the ATP III criteria was 9.5% (95% CI: 8.0-11.3%) and according to the IDF criteria it was 8.0% (95% CI: 6.6-9.7%). At the time of follow up the prevalence of MS was 13.2% and 14.8% according to the ATP III and IDF criteria, respectively. CONCLUSIONS: MS prevalence of MS increased in 4% from the school age (9.5%) to the adolescence (13.1%).
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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 | 0.000 | 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) | 0.001 | 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".