Relationships of Activity and Sugar Drink Intake on Fat Mass Development in Youths
Bibliographic record
Abstract
PURPOSE: To determine whether a significant relationship exists between fat mass (FM) development and physical activity (PA) and/or sugar-sweetened drink (SD) consumption in healthy boys and girls aged 8-19 yr. METHODS: A total of 105 males and 103 females were assessed during childhood and adolescence for a maximum of 7 yr and a median of 5 yr. Height was measured biannually. Fat-free mass (FFM) and FM were assessed annually by dual x-ray absorptiometry (DXA). PA was evaluated two to three times annually using the PAQ-C/A. Energy intake and SD were assessed using a 24-h dietary intake questionnaire also completed two to three times per year. Years from peak height velocity were used as a biological maturity age indicator. Multilevel random effects models were used to test the relationship. RESULTS: When controlling for maturation, FFM, and energy intake adjusted for SD, PA level was negatively related to FM development in males (P<0.05) but not in females (P>0.05). In contrast, there was no relationship between SD and FM development of males or females (P>0.05). There was also no interaction effect between SD and PA (P>0.05) with FM development. CONCLUSION: This finding lends support to the idea that increasing PA in male youths aids in the control of FM development. Models employed showed no relationship between SD and FM in either gender.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".