Beans Improve Satiety to an Effect that Is Not Significantly Different from Beef in Older Adults: A Randomized, Crossover Trial
Bibliographic record
Abstract
BACKGROUND: Beans are a candidate food for increasing satiety due to their protein and dietary fiber content. Beef is a common animal protein that can increase satiety due to its protein content, which is higher than beans but does not contain dietary fiber. Dietary guidance encourages higher intake of plant-based protein foods and warrants satiety studies that compare plant and animal protein foods, which could particularly benefit the rapidly growing population segment of older adults. OBJECTIVES: To compare the effects of 2 bean varieties and beef consumed within a breakfast tortilla on satiety, food intake, and 24-h energy intake in older adults. METHODS: ) 25.1 ± 3.25] consumed 3 breakfast tortilla test meals containing 1 serving of black beans (135 g), red kidney beans (135 g), or beef (80 g) in a randomized, crossover design. Participants rated their appetite sensations on periodic visual analogue scales, food intake was measured at an ad libitum pizza lunch meal, and 24-h energy intake was measured using weighed food records. Appetite sensation area under the curves (AUCs) were compared between treatments using repeated-measures analysis of covariance, and food intake and 24-h energy intake were compared using repeated-measures analysis of variance. RESULTS: Fullness and satisfaction were significantly increased, while hunger, desire to eat, and prospective food consumption were significantly decreased, following consumption of the black bean, red kidney bean, and beef test meals. Appetite sensation AUCs, ad libitum pizza intake, and 24-h energy intake did not significantly differ between the test meals. CONCLUSIONS: These results demonstrate that beans improve satiety to an extent that is not significantly different from beef in older adults, thereby supporting the role of beans as a nutrient-dense source of protein and dietary fiber as part of a satisfying meal for older adults. This trial was registered at clinicaltrials.gov as NCT05499819.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".