Low Socioeconomic Status Predicts Abnormal Eating Attitudes in Latin American Female Adolescents
Bibliographic record
Abstract
The objective of this study was to study the proportion of Ecuadorian students fulfilling criteria on the Eating Attitudes Test (EAT) in relation to socioeconomic status. Seven hundred and twenty three female adolescent participants recruited from Quito, Ecuador were administered a brief questionnaire consisting of the EAT-40 as well as lifestyle questions. Mean EAT-40 score was 17.12, with 14% fulfilling criteria. Lower socioeconomic status and watching more television predicted higher scores; however BMI, age, and positive smoking status failed to correlate. The presently unvalidated Spanish version of the EAT-26 highly correlated with the validated EAT-40 (R=0.94). A higher than expected proportion of Ecuadorians are at risk for eating disorders, especially among lower socioeconomic groups. The EAT-26 should be considered for validation as a primary screening tool in Latin America.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".