THE RELATIONSHIP BETWEEN PHYSICAL ACTIVITY AND SUGAR-SWEETENED DRINK INTAKE ON YOUTHS?? FAT MASS DEVELOPMENT
Bibliographic record
Abstract
Various factors, including low levels of physical activity (PA), and high consumption levels of sugar-sweetened drinks (SD), have been implicated in the general increase of fat mass (FM) levels seen in today's youth. PURPOSE To determine if a significant relationship exists between FM and PA or SD, in boys and girls, using longitudinal analysis. METHODS 105 boys and 103 girls were assessed repeatedly during childhood and adolescence, for a maximum of 7 years. Height and weight were measured annually, as was FM estimated by dual X-ray absorptiometry (DXA). PA was evaluated bi-annually using a physical activity questionnaire for children (PAQ-C - 1 low, 5 high), and SD was assessed using a 24-hour dietary intake questionnaire completed 1–4 times/year. Years from peak height velocity were used as a biological age indicator. Random effects models were used to analyze the data, subsequent to log linearization of the FM variable since it did not initially meet the assumption of normal distribution. RESULTS In the constructed model, controlling for height, weight and maturation, at an α-level of 0.05 an interaction effect between SD and PA was tested for but not found to be significant (p > 0.05). After removal of the interaction term from the model, SD was found to have no significant relationship (p > 0.05) with FM of boys or girls. In contrast, PA level was found to have a significant relationship with FM (p < 0.05); in both boys and girls as PA level increased the FM decreased (Boys: −0.049 SEE 0.015 PAQ-C score, Girls: −0.022 SEE 0.09 PAQ-C score). CONCLUSION The longitudinal models employed revealed a significant negative relationship between level of PA and FM in youth, after controlling for maturational status, height, and weight. This finding lends support, and possible confirmation, to proponents of increasing PA in youth to control FM. Regarding SD and FM, the models employed showed no relationship. Future investigation with more complex models, accounting for more covariates, may be warranted in this area.
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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 | 0.002 |
| 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 | 0.001 |
| 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".