Associations of Parental Control of Feeding with Eating in the Absence of Hunger and Food Sneaking, Hiding, and Hoarding
Bibliographic record
Abstract
BACKGROUND: Overweight children as young as 5 years old exhibit disturbances in eating behaviors. METHODS: Using follow-up data from 419 participants in High Five for Kids, a randomized controlled trial of overweight children, the prevalence of (1) eating in the absence of hunger and (2) food sneaking, hiding, and hoarding was estimated and cross-sectional associations of parental control of feeding and these behaviors were examined using covariate-adjusted logistic regression models. RESULTS: At follow-up, mean [standard deviation (SD)] age of the children was 7.1 (1.2) years; 49% were female; 16% were healthy weight, 35% were overweight, and 49% were obese. On the basis of parental report, 16.5% of children were eating in the absence of hunger and 27.2% were sneaking, hiding, or hoarding food; 57.5% of parents endorsed parental control of feeding. In adjusted models, children exposed to parental control of feeding were more likely to eat in the absence of hunger [odds ratio (OR) 3.37, 95% confidence interval (CI) 1.66, 6.86], but not to sneak, hide, or hoard food (OR 1.43, 95% CI 0.87, 2.36). CONCLUSIONS: Disturbances in eating behaviors are common among overweight children. Future research should be dedicated to identifying strategies that normalize eating behaviors and prevent excess weight gain among overweight children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".