Associations between eating behaviours and cardiometabolic risk among adolescents in the Health Outcomes and Measures of the Environment study
Bibliographic record
Abstract
BACKGROUND: Eating behaviours are associated with childhood obesity, but their associations with cardiometabolic risk are less clear. OBJECTIVES: We evaluated cross-sectional associations between eating behaviours and cardiometabolic risk among 185 adolescents (age 12.4 ± 0.7 years; 53% female; body mass index (BMI)-z 0.72 ± 1.37) from Cincinnati, Ohio (HOME Study; enrolled 2003-2006). METHODS: Caregivers assessed adolescents' eating behaviours with the Child Eating Behaviour Questionnaire. We computed adolescents' cardiometabolic risk scores based on HOMA-IR, triglycerides to high-density lipoprotein cholesterol ratio, adiponectin to leptin ratio, systolic blood pressure, and cross-sectional area of fat inside the abdominal cavity. Using multivariable linear regression models, we estimated associations of eating behaviour subscales with cardiometabolic risk scores or individual risk components. RESULTS: Emotional overeating (ß = 1.34, 95% CI: 0.67, 2.01), food responsiveness (ß = 0.99, 95% CI: 0.41, 1.57), and emotional undereating (ß = 0.64, 95% CI: 0.08, 1.21) were associated with higher cardiometabolic risk scores. Satiety responsiveness (ß = -0.79, 95% CI: -1.59, 0.00) was associated with lower cardiometabolic risk scores. Adjusting for adolescent BMI-z at age 12 attenuated these associations, suggesting that adiposity may mediate these associations. CONCLUSION: Hedonistic eating behaviours were associated with higher cardiometabolic risk in these 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 | 0.001 | 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 | 0.000 | 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".