The gut microbiota of Indigenous populations in the context of dietary westernization: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Indigenous populations worldwide are undergoing dietary transitions from traditional patterns toward westernized diets, influencing gut microbiota diversity and composition, with potential implications for health. Objective This systematic review and meta-analysis aimed to compare gut microbiota diversity and composition among Indigenous populations following traditional versus westernized dietary patterns. Methods A comprehensive literature search was conducted in March 2024 and updated on February 25, 2025 across databases, including All Ovid MEDLINE®, Embase, Web of Science, CAB Abstracts, and Food Science and Technology Abstracts, along with searches of gray literature sources. Eligibility criteria included observational studies comparing gut microbiota diversity and composition between traditional and westernized diets among healthy Indigenous adults (≥16 years) without chronic diseases. Two reviewers independently performed study selection, data extraction, and risk of bias assessment using the ROBINS-E tool. Data were synthesized using random effects models, specifically applying the restricted maximum likelihood estimator to calculate between-study variance (τ 2 ). Results Of 19,836 articles identified, nine studies ( N = 657 participants) met inclusion criteria. Traditional diets tended to be associated with higher microbial diversity, although results varied across diversity metrics and studies. Shannon diversity was higher in traditional groups, but this difference was not statistically significant (standardized mean differences = 0.67; 95% CI: −0.26 to 1.60; I 2 = 92.9%). Other diversity indices (Chao1, Simpson, observed species richness) did not show clear differences between diet groups. Descriptive taxonomic analyses also revealed substantial heterogeneity across populations, reflecting the context-specificity of microbiota differences between traditional and westernized groups. Nonetheless, most westernized groups exhibited a higher Firmicutes/Bacteroidetes ratio at the phylum level and a lower Prevotella / Bacteroides ratio at the genus level. Conclusion The observed heterogeneity likely reflects methodological differences, ecological variability, and the diversity of traditional diets and varying patterns of dietary transition. Longitudinal research is needed to better understand how dietary transitions affect gut microbiota over time in Indigenous populations. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/view/CRD42024597804 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".