Waist circumference is associated with liver fat in black and white adolescents
Bibliographic record
Abstract
We examined whether waist circumference (WC) is associated with liver fat in black and white adolescents. Liver fat was measured using a 3T proton magnetic resonance spectroscopy ( 1 H-MRS) in 152 overweight/obese adolescents (94 black and 58 white, body mass index (BMI) ≥85th percentile, aged 12–18 years) without liver diseases or diabetes. WC was measured at the last rib. Total and visceral adipose tissue (VAT) were measured by dual-energy X-ray absorptiometry and magnetic resonance imaging, respectively. The proportion of fatty liver (defined as liver fat ≥5.0% by 1 H-MRS) was lower (P < 0.01) in black adolescents (5.3%) compared with their white peers (24.1%). Despite similar age, BMI, WC, and total adiposity (%), black adolescents had lower (P < 0.01) VAT (59.0% vs. 81.3 cm 2 ), liver fat (1.6% vs. 3.5%), and alanine aminotransferase (17.2 vs. 22.0 IU/L) compared with their white peers. Independent of race, WC was associated with liver fat (black, r = 0.43; white, r = 0.64) in a similar magnitude to the association between VAT and liver fat (black, r = 0.44; white, r = 0.51) and these findings remained significant after controlling for age, sex, Tanner stage, and total adiposity. In blacks, WC and sex (male) were independent (P < 0.01) predictors of liver fat, explaining 17.1% and 5.6% of the variance, respectively, while in whites WC was the single best predictor, explaining 40.8% of the variance in liver fat. These findings suggest that enlarged WC is a marker of increased liver fat in overweight/obese white and black adolescents.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".