Association between Lean and Fat Mass and Indicators of Bone Health in Prepubertal Caucasian Children
Bibliographic record
Abstract
BACKGROUND/AIMS: Childhood and adolescence are critical periods for bone growth. The independent association between lean and fat mass and indicators of bone health in children is not yet known. We aim to examine the association between each of lean and fat mass and indicators of bone health in 8- to 10-year-old prepubertal Caucasian children. METHODS: We present a cross-sectional analysis of baseline data from the QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort which study the natural history of obesity. Study participants (n = 483) included prepubertal children aged 8-10 years and their biological parents. Whole-body bone mineral content (BMC, g), bone area (cm²), bone mineral density (BMD, g/cm²), lean mass (kg), and fat mass (kg) were measured by dual-energy X-ray absorptiometry. Data analyses include multiple linear regressions adjusted for potential confounding variables. RESULTS: A 1-kg increase in lean mass was associated with 28.42 g, 19.88 cm², and 0.007 g/cm² increase in whole-body BMC, bone area and BMD respectively. A 1-kg increase in fat mass was associated with 9.32 g, 8.02 cm², and 0.002 g/cm² increase in whole-body BMC, bone area and BMD, respectively. CONCLUSION: Increasing lean mass in children may help optimize bone acquisition and prevent future osteoporosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".