Whole-Body MRI and Ethnic Differences in Adipose Tissue and Skeletal Muscle Distribution in Overweight Black and White Adolescent Boys
Bibliographic record
Abstract
It is unclear whether ethnic differences exist in adipose tissue (AT) and skeletal muscle (SM) distribution in black and white youth. Investigation into the pattern of AT and SM distribution in black versus white youth may provide insight into the previously reported health disparities between these ethnicities. Therefore, we examined total and regional AT and SM in overweight black and white boys. The study sample included overweight black (n = 19) and white (n = 21) boys (11-18 yr, BMI ≥ 85th) whose body composition was evaluated using whole-body MRI. Despite similar age, Tanner stage, and BMI, black boys had significantly (P < .05) less visceral AT than white boys and more (P < .05) total and lower-body subcutaneous AT (SAT) in both absolute (kg) and relative (%) terms. There was a main effect (P < .05) of ethnicity on the relationship between total and regional AT, such that for a given amount of total body AT (kg), black boys had a greater (P < .05) lower-body SAT and less visceral AT than their white peers. For a given amount of total SM, black boys had more (P < .05) SM in the thigh. Compared with overweight white boys, overweight black boys have less visceral fat, more subcutaneous fat, and more thigh skeletal muscle.
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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 | 0.000 |
| 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) | 0.002 | 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".