Measurement site of visceral adipose tissue and prediction of metabolic syndrome in youth
Bibliographic record
Abstract
OBJECTIVE: It is unknown whether measurement site of visceral adipose tissue (VAT) influences the relationship between VAT and associated health risk in youth and if so, whether ethnic differences exist in this relationship. We examined the influence of the measurement site of VAT on the relationships between VAT and metabolic syndrome (MetS) in African-American (AA) and American-White (AW) youth. SUBJECTS: Healthy AA (n = 54) and AW (n = 54) children and adolescents (age: 8-18 yr; BMI: 15.3-42.5 kg/m(2)). MEASUREMENTS: VAT mass was derived using a series of five transverse images measured by magnetic resonance imaging, extending from 5 cm below to 15 cm above L4-L5. MetS was defined using a modified IDF criteria. RESULTS: In AA, VAT measure at 5 cm above L4-L5 (R(2) = 0.93) was most strongly (p < 0.05) correlated with VAT mass and was a significantly (p < 0.05) stronger correlate as compared to L4-L5 (R(2) = 0.84). In AW, VAT measures at 5 cm (R(2) = 0.93) and 10 cm (R(2) = 0.93) above L4-L5 were most strongly (p < 0.05) correlated with VAT mass; however, these were not stronger correlates as compared to L4-L5 (R(2) = 0.91). In AW, all VAT measures were significantly (p < 0.05) associated with an increased odds ratio (OR) for prevalent MetS, wherein the VAT mass [OR = 5.32(1.9-15.0)] and VAT at L4-L5[OR = 5.99(1.9-18.4)] were most strongly associated with MetS. In contrast, only VAT at 10 cm above L4-L5 [OR = 4.39 (1.1-18.1)] was significantly (p < 0.05) associated with MetS in AA. CONCLUSION: In AA and AW youth, the measurement site for VAT has impact on the estimation of total VAT and the magnitude of the association with obesity-related health risks.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".