Mental Health, Wellness, and Childhood Overweight/Obesity
Bibliographic record
Abstract
Childhood obesity is a growing concern, and while progress has been made to understand the association between multiple biological factors (i.e., genetics, nutrition, exercise etc.), little is known about the relationship between mental health and childhood obesity. In this paper, we offer a review of current evidence about the association between mental health and childhood obesity. A systematic literature search of peer-reviewed, English-language studies published between January 2000 and January 2011 was undertaken and resulted in 759 unique records, of which 345 full-text articles were retrieved and 131 articles were included. A theoretical model is proposed to organize the paper and reflect the current state of the literature and includes psychological factors (i.e., depression and anxiety, self-esteem, body dissatisfaction, eating disordered symptoms, and emotional problems); psychosocial mediating variables (i.e., weight-based teasing and concern about weight and shape), and wellness factors (i.e., quality of life and resiliency/protective factors). We conclude with a number of recommendations to support the creation of solutions to the rise in childhood obesity rates that do not further marginalize overweight and obese children and youth and that can potentially improve the well-being of all children and youth regardless of their weight status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".