Does Measurement Site for Visceral and Abdominal Subcutaneous Adipose Tissue Alter Associations With the Metabolic Syndrome?
Bibliographic record
Abstract
OBJECTIVE: To determine whether the associations between visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and the metabolic syndrome are altered depending on measurement site for VAT and ASAT and the definition used to identify the metabolic syndrome. RESEARCH DESIGN AND METHODS: Total VAT and ASAT volume was derived using approximately 37 contiguous computed tomography (CT) images from T10-T11 to L5-S1 in 85 men. CT images obtained at eight intervertebral locations (e.g., L4-L5, L3-L4, etc.) were used to determine the associations between partial volumes (single images) and metabolic syndrome. Metabolic syndrome was defined using the National Cholesterol Education Program (NCEP) and International Diabetes Federation (IDF) criteria. Logistic regression was used to calculate the odds ratio (OR) per SD increase in adipose tissue. RESULTS: For total and all partial volumes, VAT was more strongly associated with metabolic syndrome than ASAT independent of metabolic syndrome criteria. The OR (per SD) for NCEP metabolic syndrome was higher for total VAT volume (OR = 7.26) and for the partial volumes at T12-L1 (7.46) and L1-L2 (8.77) than those at the L4-L5 level (3.94). The OR for metabolic syndrome ( approximately 2.6) was not substantially different among the ASAT measures. A similar pattern of association was observed using the IDF metabolic syndrome criteria. CONCLUSIONS: The measurement site for VAT, but not for ASAT, has a substantial influence on the magnitude of the association with both metabolic syndrome definitions. However, because VAT remained significantly associated with metabolic syndrome regardless of measurement site, the clinical interpretation was unaltered by measurement protocol or metabolic syndrome definition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".