A Behavioral Genetic Model of the Mechanisms Underlying the Link Between Obesity and Symptoms of ADHD
Bibliographic record
Abstract
Objective: The ADHD–obesity link has been suggested to result from a shared underlying basis of suboptimal dopamine (DA); however, this theory conflicts evidence that an amplified DA signal increases the risk for overeating and weight gain. A model was tested in which ADHD symptoms, predicted by hypodopaminergic functioning in the prefrontal cortex, in combination with an enhanced appetitive drive, predict hedonic eating and, in turn, higher body mass index (BMI). Method: DRD2 and DRD4 markers were genotyped. The model was tested using structural equation modeling in a nonclinical sample ( N = 421 adults). Results: The model was a good fit to the data. Controlling for education, all parameter estimates were significant, except for the DRD4-ADHD symptom pathway. The significant indirect effect indicates that overeating mediated the ADHD symptoms–BMI association. Conclusion: Results support the hypothesis that overeating and elevated DA in the ventral striatum—representative of a greater reward response—contribute to the ADHD symptom–obesity relationship.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".