The Eating Inventory and Body Adiposity from Leanness to Massive Obesity: a Study of 2509 Adults
Bibliographic record
Abstract
OBJECTIVE: To examine how chronic dietary restraint, disinhibition, and hunger, as assessed by the Eating Inventory, vary over a broad range of BMI values from leanness to massive obesity, in subjects with family obesity. Eating Inventory factors were also studied as a function of personal weight history. RESEARCH METHODS AND PROCEDURES: Subjects were 2509 participants in a genetic study of obesity. BMIs ranged from 15 to 87 kg/m2. Six BMI groups were formed (<27, 27 to 30, 30 to 35, 35 to 40, 40 to 45, and >45). RESULTS: Multivariate analyses showed that restraint and disinhibition were significantly associated with BMI in men, whereas only disinhibition was in women. Disinhibition scores correlated strongly with hunger scores in both genders in all BMI categories; dietary restraint tended to correlate with the other two factors positively in leaner subjects and negatively in the highest BMI categories. Highly restrained normal-weight subjects were likely to exhibit disinhibition and hunger, whereas massively obese persons with very high disinhibition scores showed high hunger but little restraint. The highest restraint scores were observed in nonobese adult women with previous obesity in childhood and/or adolescence. DISCUSSION: The factor most strongly associated with BMI in this large population was disinhibition, suggesting that obesity treatment should target behaviors associated with disinhibition, especially in individuals showing a low level of dietary restraint. High restraint scores in formerly obese normal-weight women suggest that dietary restraint may exert a beneficial influence on body weight control under conditions that deserve further investigation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".