Body composition of 6 to 8.5 year old overweight and obese children: 12‐week follow‐up from an eating and exercise behaviour family‐centered lifestyle intervention in Quebec (Canada)
Bibliographic record
Abstract
Assessment of body fat mass using dual‐energy X‐ray absorptiometry (DXA) in obese children is scarce. The objective of this study was to examine body composition changes from baseline to 12‐wk in overweight and obese children participating in a lifestyle intervention. Overweight (n= 3) and obese (n= 11) children (mean age 7.7 ± 0.7 y) were randomized to three groups: control (Con); standard intervention (SInt); and an intense intervention (IInt) group. DXA scans were performed at baseline and 12‐wk. Although none of the results presented are statistically significant, Con appeared to gain more mass (2.0 ± 0.8 kg) vs. SInt (0.3 ± 2.5 kg) vs. IInt (0.1 ± 1.1 kg) (p=0.13). Concomitantly BMI z‐scores demonstrated minor alterations, IInt (0.0± 0.2) SInt (−0.2 ± 0.3) and (−0.1 ± 0.2) (p=0.19). By week 12, our results suggested that the SInt group had a slightly greater % fat loss (−2.4 %) vs. control (+0.5 %) vs. IInt (−1.7 %). However, the IIntr appeared to present with a greater changes in whole body bone mineral content (BMC) (46.5 g) and % trunk fat loss (FL) (−1.6%) compared to SInt (BMC: 44.4 g; % FL: −0.2) and control (BMC: 43.9 g; % FL: 0.8). These preliminary results suggest that obese children who attend a family intervention may lower fat mass and improve BMC, through adoption of weight‐bearing activity and a focus on nutrient dense foods. Our continued study will confirm these results. Funded by Dairy Farmers of Canada.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".