Impact of a Probiotic-Fiber Blend on Body Weight, Metabolic Regulation, and Digestive Function in Obese Adults: A Randomized, Placebo-Controlled, Multicentric Trial
Bibliographic record
Abstract
INTRODUCTION: Obesity is closely associated with metabolic syndrome, a cluster of conditions including abdominal obesity, high triglycerides, low high-density lipoprotein (HDL) cholesterol, elevated blood pressure, and impaired glucose metabolism. Emerging research suggests that gut dysbiosis, an imbalance in gut microbiota, plays a key role in metabolic syndrome, influencing insulin resistance, inflammation, and lipid metabolism. The gut microbiome has gained attention for its impact on energy balance, fat storage, and metabolic regulation. This randomized, double-blind, placebo-controlled, multicentric clinical study evaluated the efficacy and safety of probiotic-fiber blend formulation in obese adults. METHODS: Obese adults (body mass index (BMI) 30-<40 kg/m², aged 30-45; male: 46.15%, female: 53.85%) were randomly assigned to receive either the probiotic-fiber blend formulation or a placebo for 90 days, along with lifestyle counseling. Primary outcomes included body weight, BMI, waist/hip circumference, and body fat percentage. Secondary outcomes assessed biochemical parameters, digestive health, quality of life, perceived stress, and metabolic syndrome severity Z (MetS-Z) score. One hundred four participants completed the study. RESULTS: The probiotic-fiber blend formulation (n = 53) demonstrated statistically significant (p < 0.001) improvements compared to placebo (n = 51), including reductions in body weight (12.01%), BMI (12.14%), waist circumference (9.64%), and hip circumference (9.63%) compared to placebo. Additionally, statistically significant reductions were observed in the MetS-Z score (54.02%), triglycerides (25.75%), and perceived stress (37.62%), along with a notable increase in HDL levels (16.55%). Significant improvements in digestive health and quality of life were also recorded, reinforcing the probiotic-fiber blend efficacy. CONCLUSION: The findings provide robust evidence that the probiotic-fiber blend effectively improves anthropometric and biochemical markers in obesity. These results underscore the therapeutic potential of gut microbiome modulation in metabolic health. Further research should explore long-term effects, mechanistic pathways, and broader clinical applications.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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) | 0.005 | 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".