Weight discrimination and eating disorder symptoms in early adolescence: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Weight discrimination is associated with adverse outcomes, including eating disorder (ED) symptoms, but few longitudinal studies have investigated this relationship in early adolescence. We examined the prospective association of weight discrimination with ED symptoms one year later in early adolescents, and the extent to which this association was moderated by body mass index (BMI) percentile and sex. METHODS: We analyzed prospective data from Year 2 (2018-2020) and Year 3 (2019-2021) of the Adolescent Brain Cognitive Development (ABCD) Study (N = 9,079). To estimate the associations between self-reported experiences of weight discrimination in Year 2 and ED symptoms in Year 3, we conducted multiple logistic and ordinal logistic regression analyses, controlling for potential covariates, including ED symptoms in Year 2. Weight discrimination was measured using the Perceived Discrimination Scale. Presence of various ED symptoms was assessed via parent report using the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5). Participant BMI percentile and sex were also investigated as potential moderators. RESULTS: Weight discrimination was prospectively associated with higher odds of worry about weight gain (adjusted odds ratio [aOR] 2.12, 95% confidence interval [CI] 1.08-4.14, p = 0.028), self-worth tied to weight (aOR 3.75, 95% CI 2.54-5.55, p < 0.001), inappropriate compensatory behaviors to prevent weight gain (aOR 2.75, 95% CI 2.02-3.74, p < 0.001), binge eating symptoms (aOR 1.72, 95% CI 1.10-2.68, p = 0.018), and distress about binge eating (aOR 2.26, 95% CI 1.33-3.85, p = 0.002) one year later. Weight discrimination was also associated with higher odds of a greater number of overall ED symptoms one year later (aOR 2.21, 95% CI 1.61-3.03, p < 0.001). A significant interaction by BMI percentile was also found: in adolescents with BMI of 5th to < 85th percentile, weight discrimination was more strongly and prospectively associated with higher odds of binge eating symptoms (aOR 3.32, 95% CI 1.27-8.68, p = 0.015) and binge eating distress (aOR 5.11, 95% CI 2.10-12.44, p < 0.001). CONCLUSIONS: Results support a prospective relationship between perceived weight discrimination and ED symptoms in early adolescents, and the differential associations based on BMI percentile highlight the need for interventions that address weight stigma across the weight spectrum.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".