Association between Parents’ Perceptions of Preschool Children’s Weight, Feeding Practices and Children’s Dietary Patterns: A Cross-Sectional Study in China
Bibliographic record
Abstract
Parental perception of children's weight may influence parents' feeding practices, and in turn, child dietary intake and weight status; however, there is limited evidence generated for preschoolers. The aim of this cross-sectional study was to investigate associations between Chinese parents' perceptions of child weight, feeding practices and preschoolers' dietary patterns. Participants (1616 parent-child pairs) were recruited from six kindergartens in Hunan, China. Parents' misperception, concern, and dissatisfaction on child weight were collected through a self-administered caregiver questionnaire. Parental feeding practices and children's dietary intake were, respectively, assessed using the Child Feeding Questionnaire and a Food Frequency Questionnaire. Linear regression models were applied to analyze associations between parental weight perceptions, feeding practices, and preschooler's dietary patterns. Associations between parents' weight perceptions and dietary patterns were significant only among underweight children. Regardless of child weight status, parental weight underestimation and preference for a heavier child were positively associated with pressure-to-eat. Parental weight concern was positively associated with restriction in normal weight child, but this was not found in other weight groups. In conclusion, Parents' misperception, concern, and dissatisfaction about child weight are associated with parents' feeding practices and may influence preschoolers' dietary quality, but the relationships vary by children's actual weight status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".