Lean mass reference curves in adolescents using dual-energy x-ray absorptiometry (DXA)
Bibliographic record
Abstract
The body composition phenotype of low lean mass (LM) has been associated with metabolic disorders and impaired physical functioning in the pediatric population. Abnormalities in body composition may be identified using reference curves; however, no reference data on LM is available for Brazilian adolescents. The purpose of this study was to present reference data, including percentile curves, of whole body LM, lean mass index (LMI), appendicular lean mass (ALM), and fat mass for Southern Brazilian adolescents. This was a cross-sectional study of adolescents aged 12-17 years from a southern region in Brazil, who had body composition assessed using dual energy x-ray absorptiometry (DXA). Percentile values and reference curves employing the Lambda, Mu and Sigma method (LMS) were computed for LM, LMI (lean mass/height2), ALM and fat mass. Data on 541 adolescents (68.6% boys) was included. Sex differences in growth trajectories were observed for absolute and adjusted LM, with boys presenting greater LM quantity with advancing ages than girls (66.9% and 17.4% difference between the ages of 12 and 17 for boys and girls, respectively). The values corresponding to the lowest percentile (3rd) of LMI ranged between 10.63 to 13.93 kg/m2 in boys and 11.13 to 12.03 kg/m2 among girls aged 12-17 years. This study established the first LM, LMI, and ALM reference curves in Southern Brazilian adolescents, which can potentially be used in association with functional measures to identify LM abnormalities during growth.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".