Home Environment Characteristics and BMI Z-Score Among Saudi Preschool Children: A Feasibility Study
Bibliographic record
Abstract
Objective: To assess feasibility of using preschools in Saudi Arabia as a source for collecting nutrition-related data; To examine associations among home environment characteristics and child BMI z-score (BMIz). Methods: Fifty-three (3-5 years old) children and their mothers were recruited from two preschools in Jeddah, Saudi Arabia. Mothers completed a self-administered questionnaire. Child anthropometry was completed using standardized procedures. BMIz was calculated using the WHO growth standards and reference data. Associations between child and home environment variables were tested using Pearson correlation, t-tests and ANOVA. Results: Participation rate in the middle-to high-income preschool was higher compared to the low- to middle-income preschool (27.3% vs. 17.4%, respectively). Increase in child age and maternal BMI were associated with lower maternal playtime with the child (r= -0.31, p= 0.02, and r= -0.38, p= 0.006, respectively). Increase in child age was also associated with lower paternal playtime with the child (r= -0.26, p= 0.05). Paternal playtime with the child was positively associated with both paternal involvement in feeding (r= 0.30, p= 0.03) and regular family mealtimes (r= 0.26, p=0.05). There was a trend of positive association between paternal involvement in feeding and higher child BMIz (r= 0.26, p=0.08). Mean child BMIz was lower when mothers had ³ a college education vs. not (p= 0.04). Greater child screen time was associated with fewer family mealtimes (p= 0.01). Conclusion: Increasing awareness is needed in order to improve feasibility of studies conducted in Saudi preschools; Future work is needed to further establish the associations of home environment characteristics and child obesity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".