Effect of dairy and nondairy snacks on postprandial blood glucose regulation in 9–14-year-old children
Bibliographic record
Abstract
In adults, dairy consumption improves short-term blood glucose regulation. It is unknown if these short-term benefits extend to children of different weight statuses. The objective of this study was to investigate the effect of a dairy and nondairy snack in both normal-weight (NW) and overweight/obese (OW/OB) children on blood glucose regulation and food intake (FI). In a repeated-measures crossover design, 11 NW and 7 OW/OB children (age: 9–14 years), consumed, in random order, a dairy (Greek yogurt, 198.9 g, 171 kcal, 0 g fat, 17 g protein) or nondairy (mini sandwich-type cookies, 37.5 g, 175 kcal, 7.5 g fat, 1.3 g protein) snack containing 25 g of available carbohydrates. Ad libitum FI was measured 120 min after snack consumption. Blood glucose, insulin, C-peptide, and glucagon-like peptide-1 (GLP-1) were measured at 0 min (before the snack), and at 30, 60, 90, and 120 min after snack consumption. Insulin secretion was calculated from deconvolution of C-peptide. Hepatic insulin extraction was calculated as C-peptide divided by insulin. FI did not differ between snacks (P = 0.55). Mean blood glucose was lower (P < 0.001) and insulin higher (P < 0.0001) in the 120 min after consuming the dairy snack. C-Peptide concentrations (P = 0.75) and insulin secretion (P = 0.37) were not different between snacks. The increase in insulin was explained by reduced hepatic insulin extraction (P < 0.01). Consumption of the dairy snack also increased mean GLP-1 concentrations (P < 0.001). In conclusion, consumption of a dairy snack by NW and OW/OB children results in reduced postprandial blood glucose concentrations and elevated circulating insulin compared with a nondairy snack possibly because of delayed hepatic insulin extraction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".