Post-prandial glucose and insulin responses of hummus alone or combined with a carbohydrate food: a dose–response study
Bibliographic record
Abstract
OBJECTIVES: Pulses are low glycemic index (GI) foods and have been associated with reduced risk of heart disease, diabetes and some cancers. However the blood glucose and insulin responses of hummus, a food containing chickpea, have not been thoroughly tested. METHODS: Ten healthy subjects each consumed 11 breakfast study meals in randomized order over a period of 15 weeks. Hummus was consumed alone at three doses (2.7 g, 10.8 g and 25 g available carbohydrate [avCHO] portions) and with 50 g avCHO from white bread at three doses (2.7 g, 5.4 g and 10.8 g avCHO portions). The responses elicited by hummus alone were compared with 25 g avCHO portions of white bread, while those after hummus plus white bread were compared with 50 g avCHO from white bread. Plasma glucose and serum insulin responses were monitored over two hours and the GI and insulin index (II) calculated using standard methodology. RESULTS: The GI and II of hummus were 15 ± 3 and 52 ± 13, respectively, and were significantly lower than white bread (P < 0.05). The glucose and insulin incremental area under the curve (IAUC) for hummus alone were significantly lower than white bread except for insulin IAUC of hummus 25 g avCHO. The peak rise of blood glucose and insulin after hummus were significantly lower than after white bread. Glucose and insulin IAUC after adding hummus to bread did not differ significantly from white bread alone. However the blood glucose 45 min after adding 25 g avCHO from hummus to white bread was significantly lower while at 120 min it was significantly higher than after white bread alone. CONCLUSIONS: This study demonstrated that, similar to chickpeas, hummus has a very low GI and II. Postprandial glucose responses were 4 times less than that of white bread and did not compromise insulin levels.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".