Growth Mixture Modeling of Adolescent Body Mass Index Development: Longitudinal Patterns of Internalizing Symptoms and Physical Activity
Bibliographic record
Abstract
Growth mixture modeling was used to identify different trajectories of body mass index (BMI) among adolescents ages 10-15 from a national sample. Three distinct classes were found for both boys and girls: "normative" (90.9% and 89.7%), "high increasing" (6.3% and 7.4%), and "decreasing" (2.8% and 2.9%). Multinomial logistic regression identified family income as predictive of class membership for boys and pubertal status and being rural as predictive for girls. Parent-reported health was a common predictor across gender. Growth curves of internalizing symptoms and physical activity were modeled to explore trends across classes. Findings highlight complexities in the relations between BMI, internalizing symptoms, and physical activity in this developmental period.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".