Nutrient Intake Patterns in Preschool Children from Inner City Day-Care Centers
Bibliographic record
Abstract
An elevated body mass index (BMI) early in childhood is known as a predictor for adult obesity and obesity related comorbidities.Three year old obese children have exhibited inflammatory biomarkers linked to chronic diseases, so childhood obesity prevention efforts should start during early years of life.The current study, conducted in the U.S., collected 24 hour nutrient intake through dietary records and compared body weight and intake patterns of children from two daycare centers differing in racial and income levels.Anthropometric and dietary measures were obtained from 74 caregivers (CG) and their children.Each child's food intake at preschool was observed and recorded by direct observation by graduate students.The home food intake was recorded by the CG.Fifty one CG returned all the dietary records and completed the study.Both center and at home records were combined together to produce the daily nutrient intake data.The mean BMI percentile for both boys and girls were in the healthy BMI range, although a higher percent of girls had BMI greater than 85 percentile.All macronutrients were significantly higher than the Dietary Recommended Intake (DRI) or estimated average requirement (EAR).Children from low income families consumed more protein, total fat, saturated fat, higher percentage of energy from saturated fat and had higher sodium intake.Elevated intake of fat and protein may predispose children to weight gain.Nutrition education to teach CG, especially those with low income, to reduce energy density in meals is warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".