Mediating role of disordered eating in the relationship between screen time and BMI in adolescents: longitudinal findings from the Research on Eating and Adolescent Lifestyles (REAL) study
Bibliographic record
Abstract
OBJECTIVE: This study investigated whether the duration and type of screen time (ST) (TV viewing, recreational computer use, video gaming) is longitudinally associated with z-BMI and if these relationships are mediated by disordered eating (emotional, restrained). DESIGN: At baseline, participants were n 1197 (T1; 60 % female) adolescents (mean age = 13·51 years) who completed surveys over 2 years. ST was assessed by a self-reported measure created by the investigative team, while emotional and restrained eating was measured by the Dutch Eating Behaviour Questionnaire (DEB-Q). Height and weight were objectively measured to quantify z-BMI. SETTING: Thirty-one public and two private schools from the region of Ottawa, Canada. PARTICIPANTS: Students in grades 7-12. RESULTS: Parallel multiple mediation analyses revealed that more time spent watching TV at baseline is associated with higher z-BMI at T3 (total effect; B = 0·19, se = 0·07, P = 0·01, 95 % CI 0·05, 0·34), but no relationships were observed for total ST exposure or other types of ST and z-BMI. Disordered eating did not mediate the positive association between baseline TV viewing and z-BMI at T3. CONCLUSIONS: TV viewing was longitudinally associated with higher z-BMI in a community-based sample of adolescents, but disordered eating behaviours did not mediate this relationship. However, other non-pathological eating behaviours may mediate the association between ST and obesity and warrant further investigation. Finding suggests that targeting reduction in youth's TV viewing may be an effective component in the prevention of childhood obesity.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 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".