Associations between weight‐related teasing and psychosomatic symptoms by weight status among school‐aged youth
Bibliographic record
Abstract
Objective Weight‐related teasing (WT) is associated with poor mental health. This study examined whether weight status moderates the relationship between WT and psychosomatic symptoms within a representative sample of school‐aged youth. Methods Data are from the Canadian 2013/2014 Health Behaviour in School‐aged Children Survey, a nationally representative sample of youth in Grades 6–10. WT, psychosomatic symptoms and body mass index (BMI) were self‐reported. Results The final sample consisted of 20,277 youth (mean age = 14.2 years; 50.2% female). The prevalence who reported being WT at least once a week was 4.6%, 8.1% and 17.3% among youth with normal weight, overweight, and obesity, respectively ( p < 0.001). There was a gradient relationship between the frequency of WT and psychosomatic symptoms ( p < 0.001). By comparison to youth that were not WT, psychosomatic symptom z ‐scores were significantly ( p < 0.05) higher in youth that were WT one to two times in the past few months (0.47, 95% CI: 0.41–0.53), two to three times per month (0.65, 0.52–0.77), about once a week (0.82, 0.71–0.93) and several times a week (0.98, 0.84–1.12). However, the WT * BMI category interaction term was not significant ( p = 0.86). Conclusions Victims of WT experienced more psychosomatic symptoms independent of BMI category; however, BMI category did not moderate the association between WT and psychosomatic symptoms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".