The association of ready to eat cereal (RTEC) at breakfast with diet quality and adiposity in African‐American (AA) and Hispanic‐American (HA) children 1 to 18 years: Results from NHANES, 1999–2002
Bibliographic record
Abstract
The aim of this study was to examine the association of an RTEC breakfast with diet quality and weight of AA (n=2377) and HA (n=3236) 1 to 18 y in NHANES, 1999–2002. Three breakfast groups were: skippers, RTEC, and other breakfast (OB); age groups were 1–5, 6–12, 13–18 y. Mean adequacy ratio (MAR) score was the average percentage of the Estimated Average Requirement obtained from 24 hour recall intake of vitamins A, E, C, B1, B2, B6, B12; niacin; folate; phosphorus; magnesium; iron; and zinc. MAR and weight measures (mean±SE) of breakfast groups were compared using SUDAAN. Age was related to skipping and type of breakfast: for 1–5 v. 6–12 v. 13–18y, 7.4% v.16.9% v.36.8% of AA, and 4.9% v. 8.9% v. 28.3% of HA skipped; 45% v. 38% v. 19.4% of AA, and 40.5% v. 33.9% v. 22.1% of HA ate RTEC. MAR for AA was highest in RTEC (97.3 [1–5], 94.7 [6–12], 92.1 [13–18y]) (p<0.05). For HA 1–5y, MAR was higher for RTEC (97.2±0.2) than OB (95.7±0.4), but not skippers (92.8±2.1); in HA 6–12y, MAR of RTEC (95.4±0.6) was higher than skippers (84.9±1.3); in HA 13–18y MAR of RTEC (91.1±0.5) was highest (p<0.05). In AA and HA 2–18y there were no differences in z‐score of BMI‐for age; in AA 2–18y only waist circumference (cm) was lowest in RTEC (66.5±0.3) v skippers (68.7±0.7) or OB (68.2±0.4). There were ethnic differences in breakfast consumption patterns, and adiposity of 2–18y AA and HA; diet quality improved with RTEC in both groups. Support: USDA & Kellogg's.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".