Association between Lean and Fat Mass and Indicators of Bone Health in Prepubertal Caucasian Children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<b><i>Background/Aims:</i></b> 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. <b><i>Methods:</i></b> 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 (cm<sup>2</sup>), bone mineral density (BMD, g/cm<sup>2</sup>), 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. <b><i>Results:</i></b> A 1-kg increase in lean mass was associated with 28.42 g, 19.88 cm<sup>2</sup>, and 0.007 g/cm<sup>2</sup> 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 cm<sup>2</sup>, and 0.002 g/cm<sup>2</sup> increase in whole-body BMC, bone area and BMD, respectively. <b><i>Conclusion:</i></b> Increasing lean mass in children may help optimize bone acquisition and prevent future osteoporosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it