Changes in systolic blood pressure, postprandial glucose, and gut microbial composition following mango consumption in individuals with overweight and obesity
Bibliographic record
Abstract
This study aimed to explore the impact of daily mango consumption (Mangifera indica) on cardiometabolic health and gut microbiota in individuals with overweight and obesity. Changes in cardiometabolic variables, gut microbiota diversity and composition, physical activity habits, and dietary intakes were assessed in 8 males and 19 females with overweight and obesity who consumed 280 g/day of mango pulp for 8 weeks. There were no significant changes in body weight, waist circumference, or plasma lipid levels. However, after consuming mangos for 8 weeks, participants showed a 3.5% reduction in systolic blood pressure (–4 ± 6 mm Hg, p = 0.011) as well as a 10.5% reduction in 2-hour plasma glucose concentration after a 75-g oral glucose tolerance test (–0.58 ± 1.03 mmol/L, p = 0.008). These beneficial cardiometabolic outcomes were accompanied with enhanced gut microbiota diversity and with changes in the abundance of specific gut bacterial species. Mango consumption may have beneficial effects on both blood pressure and glucose homeostasis in individuals with overweight and obesity. Further studies are warranted to determine the impact of long-term and regular mango intake on cardiometabolic risk factors of individuals with overweight and obesity, and the potential mechanisms linking gut microbial changes to those health benefits. This study was registered with clinicaltrials.gov as NCT03825276. Novelty: A 3.5% reduction in systolic blood pressure is noted after consuming mangos for 8 weeks. A 10.5% reduction in 2-hour plasma glucose concentration of an oral glucose tolerance test is observed after consuming mangos for 8 weeks. Mango consumption for 8 weeks may enhance gut microbial diversity and abundance of specific bacterial species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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".