Effects of Infant Formula Supplemented With Prebiotics on the Gut Microbiome, Gut Environment, Growth Parameters, and Safety and Tolerance: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
CONTEXT: Prebiotics are often added to infant formulas to mimic the benefits of oligosaccharides found in human milk. OBJECTIVE: This systematic review and meta-analysis evaluated the effects of prebiotic-supplemented cow's milk-based formula on the gut microbiota, gut environment, growth parameters, and safety and tolerance in infants ≤6 months old, compared with a standard formula or human milk comparator. DATA SOURCES: Searches were performed in the PubMed, Embase, Cochrane Central Register of Controlled Trials, and ProQuest Dissertations & Theses databases. Articles were included that reported on randomized controlled trials, were published from inception until April 2024, and met prespecified inclusion and exclusion criteria. DATA EXTRACTION: Outcomes included gut microbiota (eg, diversity; taxa at phylum, family, genus and species levels), gut environment (eg, pH, secretory immunoglobulin A, fecal calprotectin, fecal metabolites), growth parameters (eg, z scores), and safety and tolerance. Fixed or random effects models were used and mean differences (MDs) with 95% CIs were calculated to assess pooled effects. Risk of bias was assessed using the Cochrane Collaboration Tool (RoB 2). DATA ANALYSIS: A total of 30 articles met inclusion criteria, with 5290 infants included. Whereas effects on Lactobacillus were inconsistent, prebiotic formula supplementation increased Bifidobacterium counts (k = 7 [MD: 0.49; 95% CI, 0.27-0.71]; I2 = 13%; P < .00001) and decreased fecal pH (k = 7 [MD: -0.39; 95% CI, -0.57 to -0.20]; I2 = 0%; P < .0001) compared with standard formula. Prebiotic formula supplementation increased total bacteria compared with human milk (MD: 0.41 [95% CI, 0.17-0.65]; I2 = 8%; P = .0006). In terms of growth parameters, weight-for-age z scores favored the prebiotic formula group compared with the human milk group (k = 2 [MD: 0.23; 95% CI, 0.04-0.42]; I2 = 7%; P = .02). CONCLUSIONS: Prebiotic supplementation in infant formula can positively alter the gut microbiota, particularly Bifidobacterium, without negative impacts on growth. Standardized, high-quality research is needed to confirm the study findings and inform guidelines for prebiotic use in infant nutrition. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42021253589.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.035 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".