Longitudinal Modeling of Adiposity in Periadolescent Greek Schoolchildren
Bibliographic record
Abstract
PURPOSE: Obesity has an etiology that is multidimensional in nature. Given the dearth of longitudinal data, we examined changes in adipose tissue (Ad) in relation to physical activity levels (PA), aerobic fitness (AF), and energy intake (EI) in Greek schoolchildren, as they progressed from age 12 to 14 yr. METHODS: This was a 2-yr and three-time-point (TP) study. Participants (N=210 (TP1); =204 (TP2); =198 (TP3)) were assessed for anthropometry, maturity status, Ad, PA, AF, and EI. Mean values were used for exploratory analyses, whereas two generalized estimating equations (GEE) models examined for longitudinal associations between the studied parameters. The first (GEE1) aimed to extract inherent associations between the dependent (Ad) and independent (PA, AF, EI) variables for the entire study period. For further evidence of association, the second analysis (GEE2) used the independent variables at TP1 and TP2 to predict the dependent variables at TP3. RESULTS: Levels of Ad in boys decreased significantly (P<0.05) from TP1 to TP3, whereas the same variable demonstrated a nonsignificant increase (P>0.05) in girls. GEE1 revealed that longitudinal changes in Ad were significantly associated only with PA (beta=-0.16; P<0.001) and AF (beta=-0.09; P<0.05) for all schoolchildren. Similarly, GEE2 revealed that the main factors (at TP1 and TP2) predicting the development of Ad (at TP3) were PA (beta=-0.14; P<0.001) followed by AF (beta=-0.10; P<0.05). CONCLUSION: With respect to data presented, we established that longitudinal changes in Ad are mainly accompanied by changes in PA and, to a lesser extent, AF levels.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".