Flavored Milk Consumers Drank More Milk and Had a Higher Prevalence of Meeting Calcium Recommendation Than Nonconsumers
Bibliographic record
Abstract
BACKGROUND: Some schools are removing flavored milk because of the perception that it negatively impacts children's overall diet. This study assessed the contribution of flavored milk to their diets. METHODS: Individual usual intakes (IUI) were calculated from 24-hour dietary recalls of children 2-18 years (N = 20,329) participating in National Health and Nutrition Examination Survey (NHANES) 2001-2012. IUI of >0.25 cup equivalent of flavored dairy milk defined consumers (N = 3564; 56% boys). Covariate-adjusted regression analyses using appropriate sample weights were calculated. Estimated Average Requirements (EAR) and Adequate Intakes (AI) determined the relation to dietary recommendations. Consumers were compared to nonconsumers (p ≤ .001). RESULTS: Flavored milk consumers consumed more milk. Consumers aged 2-3 years had higher mean added sugars intakes. Consumers aged between 2-3 and 9-13 years had a higher saturated fat (SFA) intake. Consumers aged 14-18 years had higher percent energy from SFA. Consumers had a lower mean percentage of children meeting AI for fiber and a higher percentage meeting the EAR for calcium. Consumers aged 4-8 and 9-13 years had a higher mean percentage of children meeting the EAR for magnesium. CONCLUSIONS: Consumption of flavored milk has the potential to increase milk consumption and reduce the percentage of children below the EAR for calcium; the percentage meeting AI for fiber was lower.
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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 | 0.000 | 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) | 0.007 | 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".