Self‐esteem and cognitive development in the era of the childhood obesity epidemic
Bibliographic record
Abstract
Consequences of obesity for mental health and cognitive development are not established to the same degree as those for chronic diseases. This study aims to document the interrelationships between body weight, self-esteem and school performance in childhood. Height and weight measurements and self-report of self-esteem, diet quality and physical activity of 4945 grade 5 students were linked with standardized literacy test results. Structural equation models were applied to confirm hypothesized relationships between body weight, self-esteem and school performance, and revealed that body weight affected self-esteem negatively and that school performance affected self-esteem positively. Body weight did not affect school performance, and self-esteem did affect neither body weight nor school performance. Subsequent multi-level logistic regression showed that obese students, relative to normal weight students, were more likely (1.44; 95% CI: 1.12-1.84), and students with good school performance, relative to those performing poor, were less likely (0.39; 95% CI: 0.26-0.58), to have low self-esteem. Diet quality and active living had positive effects on both school performance and self-esteem. The study findings further establish obesity as a risk factor for low self-esteem and add to the rationale to promote healthy eating and active living among children and youth as this will prevent chronic diseases and improve mental health and cognitive development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".