Using cereal to increase dietary fiber intake to the recommended level and the effect of fiber on bowel function in healthy persons consuming North American diets.
Bibliographic record
Abstract
BACKGROUND: Dietary fiber intake remains low despite increasing evidence for its health benefits, including laxation. OBJECTIVE: We aimed to assess the effects of increasing fiber intake on bowel habits and gastrointestinal tolerance in healthy persons consuming a typical Canadian or US diet. DESIGN: Under a randomized crossover design, 23 free-living participants consumed a typical Canadian or US diet (35% fat, 12 g fiber/d) and received 25.0-28.7 g fiber/d from each of 5 breakfast cereals: All-Bran (AB), Bran Buds with Corn (BBC), Bran Buds with Psyllium (BBP), BBC with viscous fiber blend (VFB), or a low-fiber control for 3 wk, with each study arm separated by a washout of >/=1 wk. Seven-day stool collections and a symptom diary were obtained during the last week of each study arm. RESULTS: All study cereals induced significant (P < 0.05) increases in fecal bulk from the control diet at 128 +/- 38 g to 199 +/- 56, 199 +/- 57, 247 +/- 87, and 197 +/- 63 g with consumption of AB, BBC, BBP, and VFB, respectively; less intestinal transit time; and significantly (P < 0.05) greater bowel movement frequency. Despite the increased activity of the bowel, a positive level of comfort was maintained. BBP was more effective than other cereals in terms of increasing fecal wet weight (P < 0.05). CONCLUSION: Water-insoluble dietary fibers (ie, AB and BBC) and their mixtures with water-soluble fibers (ie, BBP and VFB) in the form of breakfast cereals (2.5 servings/d) proved to be a practical way of increasing fiber intake to recommended levels, while maintaining a good level of tolerance.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".