Attachment Style and Obesity: Disordered Eating Behaviors as a Mediator in a Community Sample of Canadian Youth
Bibliographic record
Abstract
OBJECTIVE: Obesity and overweight are associated with many negative health outcomes. Attachment style has been implicated in the development of obesity in youth. The present study examined if disordered eating behaviors mediate the relationship between attachment style and body mass index (BMI) in a large community sample of Canadian youth. METHOD: A total of 3,043 participants (1,254 males and 1,789 females, Mage = 14.20 years) completed self-report questionnaires including the Relationship Questionnaire and the Dutch Eating Behavior Questionnaire, and BMI was objectively measured. Disordered eating behaviors (restrained, emotional, and external) were examined as possible mediating mechanisms in the relationship between attachment style and BMI z-score, using a multiple mediation model using bootstrapping while controlling for socio-demographic covariates. RESULTS: Insecure attachment was significantly associated with higher BMI, and disordered eating mediated this relationship. Restrained eating was the strongest mediator of this pathway. CONCLUSION: Results suggest that it may be important to take attachment history and restrained eating into account when designing treatment and prevention strategies for obesity in youth.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".