The effect of dairy products and non-dairy snacks on food intake, subjective appetite and cortisol levels in children: a randomized control study
Bibliographic record
Abstract
Dairy snacks are available in various physical forms and their consumption is linked to improved metabolic health. The objective of this study was to determine the effect of dairy snacks of different physical forms on short-term food intake (FI), subjective appetite, and the stress hormone, cortisol, in children. Following a repeated-measures crossover design, 40 children aged 9–14 years randomly consumed 1 of 5 isoenergetic (180 kcal) snacks per study session. These snacks included solid (potato chips, cookies, and cheese), semi-solid (Greek yogurt), and fluid (2% fat milk) snacks. FI was measured 120 min after snack consumption. Subjective appetite was measured at 0 (immediately before the snack), 15, 30, 45, 60, 90, and 120 min. Salivary cortisol (n = 18) was measured after the Greek yogurt and cookie snacks at 0, 30, 60, 90, and 120 min. FI did not differ between snacks (P = 0.15). The Greek yogurt (P < 0.0001) and cheese (P = 0.0009) snacks reduced average appetite compared with the 2% fat milk snack. Salivary cortisol levels were not affected by snack (P = 0.84). This study demonstrates that dairy snacks are as effective as other popular snacks at influencing subsequent FI. However, solid and semi-solid dairy snacks are more effective at repressing subjective appetite than a fluid dairy snack. Registered at ClinicalTrials.gov (NCT02484625). Novelty: Milk, Greek yogurt and cheese have a similar effect on short-term food intake in children as popular potato chips and cookie snacks. Solid, semi-solid and liquid snacks have a similar effect on short-term food intake in children.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".