Effects of a high protein diet with and without a multi‐strain probiotic and prebiotic on microbiota and gastrointestinal wellness in older women: a randomized, double‐blind, placebo‐controlled crossover study
Bibliographic record
Abstract
Protein intake exceeding requirements may benefit physiological processes and reduce the risk of sarcopenia in older adults. However, high protein, animal‐based diets may produce undesirable perturbations in microbiota resulting in inflammatory conditions. With declining diversity of colonic microbiota among older adults, prebiotics and probiotics may confer benefits in this cohort. The aim of this research was to examine the effects of a high protein (animal and plant protein) diet on microbiota profile and digestive health in healthy older adults, and the potential mitigating role of a prebiotic, multi‐strain probiotic or synbiotic. A double‐blind, crossover, placebo‐controlled feeding trial was conducted. Healthy older women (n=26; 73.7±5.6 y) were randomized to an 18‐week crossover study design consisting of 4 interventions: i) high protein diet (2.0–2.5 g/kg/d), ii) high protein diet with a multi‐strain probiotic (2×10 10 CFU/d), iii.) high protein diet with inulin, and iv) high protein diet with symbiotic (inulin + probiotic). Each 14‐d intervention period consisted of the same eucaloric, high‐protein diet separated by 14‐day washout periods. Gastrointestinal health, including stool frequency and weekly gastrointestinal symptoms measured by Gastrointestinal Symptom Rating Scale (GSRS) were evaluated. Stools were collected during baseline, intervention and washout periods, and qPCR (polymerase chain reaction) and 16S rRNA gene sequencing was conducted. The results showed no phyla level changes, whereas high intra‐individual variations in genera and significant changes in operational taxonomic units (OTUs) were observed with treatments. Stool frequency was not different among periods. The high protein diet with interventions significantly increased GSRS scores of abdominal pain and indigestion syndromes, but not reflux, constipation and diarrhea syndrome, compared to baseline. The results of this study provide evidence that, contrary to the possible negative effects of a high protein, animal‐based diet, a high mixed protein diet did not have profound changes on microbiota in older women, a group that may benefit from the physiological benefits of higher protein intake. Support or Funding Information Lallemand Health Solutions; University of Florida
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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) | 0.005 | 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) | 0.004 | 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".