Body Composition, Nutritional Profile and Muscular Fitness Affect Bone Health in a Sample of Schoolchildren from Colombia: The Fuprecol Study
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
The objective of the present study is to investigate the relationships between body composition, nutritional profile, muscular fitness (MF) and bone health in a sample of children and adolescents from Colombia. Participants included 1118 children and adolescents (54.6% girls). Calcaneal broadband ultrasound attenuation (c-BUA) was obtained as a marker of bone health. Body composition (fat mass and lean mass) was assessed using bioelectrical impedance analysis. Furthermore height, weight, waist circumference and Tanner stage were measured and body mass index (BMI) was calculated. Standing long-jump (SLJ) and isometric handgrip dynamometry were used respectively as indicators of lower and upper body muscular fitness. A muscular index score was also computed by summing up the standardised values of both SLJ and handgrip strength. Dietary intake and degree of adherence to the Mediterranean diet were assessed by a 7-day recall questionnaire for food frequency and the Kidmed questionnaire. Poor bone health was considered using a z-score cut off of ≤−1.5 standard deviation. Once the results were adjusted for age and Tanner stage, the predisposing factors of having a c-BUA z-score ≤−1.5 standard deviation included being underweight or obese, having an unhealthy lean mass, having an unhealthy fat mass, SLJ performance, handgrip performance, and unhealthy muscular index score. In conclusion, body composition (fat mass and lean body mass) and MF both influenced bone health in a sample of children and adolescents from Colombia. Thus promoting strength adaptation and preservation in Colombian youth will help to improve bone health, an important protective factor against osteoporosis in later life.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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