Factor Analysis of Cardiovascular Risk Clustering in Pediatric Metabolic Syndrome: CASPIAN Study
Bibliographic record
Abstract
AIMS: To assess the results of factor analysis of coronary artery disease risk factors in a large national representative sample of children, and to compare its results on the variables measured between those with or without metabolic syndrome (MetS). METHODS: This cross-sectional multicenter population survey was conducted on 4,811 nationally representative school students aged 6-18 years. MetS was defined based on criteria analogous to the Adult Treatment Panel III. Factor analysis by principle components analysis and Varimax rotation was carried out to cluster risk factors. RESULTS: MetS was present in 14.1% of subjects (n = 678). From the nine variables assessed, factor analysis of the z scores of variables show that in all age groups, three similar factors were loaded: lipids, adiposity, and blood pressure, that accounted for 87.4-90.8% of the variance. Three factors were loaded in those with MetS (cholesterol/TG, metabolic/adiposity, and blood pressure) (65.9% of variance); and four factors (cholesterol, metabolic, adiposity, and blood pressure) were loaded among those without the MetS (75.6% of variance). We did not find a central feature that underlies all three factors among children with the MetS; however, waist circumference was the only variable that was loaded for two factors. CONCLUSION: These findings support a change in the concept of MetS from that of a single entity to one that represents several distinct but intercorrelated entities. An approach to assessing risk clustering from early life, and longitudinal studies that would elucidate how these various risk domains interact over time are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".