Development of Disordered Weight Control Behaviors and Its Progression to Eating Disorders in Canada: A Nationally Representative Microsimulation
Bibliographic record
Abstract
OBJECTIVE: Eating disorders (ED) present a significant health burden to children, adolescents, and young adults globally. Despite the importance of disordered weight control behaviors (DWCB) in ED development, little is known about the progression from DWCB to ED. METHODS: We synthesized available national surveillance and longitudinal data in Canada, as well as broader epidemiologic literature, to develop a state-transition microsimulation model to simulate the natural history of DWCB and ED for a synthetic cohort of 300,000 children. Using the calibrated model, we generated mean estimates and 95% uncertainty intervals (UI) for nationally representative point prevalence, cumulative incidence, and median time to progression of DWCB and ED from age four to 30 years, by sex assigned at birth. RESULTS: Point prevalence of DWCB peaked at age 16 years at 32.8% (UI: 24.6%-42.5%) for female and at 11.0% (UI: 6.9%-16.1%) for male individuals. By age 30 years, 67.7% (UI: 60.8%-76.9%) of female and 48.7% (UI: 38.7%-68.0%) of male individuals had ever engaged in DWCBs. Female individuals who engaged in DWCB did so for a median of 3 (UI: 2-4) cumulative years, and 22.5% (UI: 11.5%-37.9%) later developed ED. DISCUSSION: We estimated substantial DWCB engagement among young people in Canada, especially female youth, which contributed to considerable burden of ED. This is the first known study to provide nationally representative estimates of DWCB and ED outcomes in Canada that cannot be obtained directly from empirical data. The results have significant implications for prevention and early intervention among children and adolescents.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".