Influence of Body Composition and Specific Anthropometric Parameters on SIBO Type
Bibliographic record
Abstract
Recent observations have shown that Small Intestinal Bacterial Overgrowth (SIBO)affects the host through various mechanisms. While both weight loss and obesity have been reported in the SIBO population due to alterations in the gut microbiome, very little is known about the influence of SIBO type on body composition. This study aimed to evaluate whether there is a link between the three types of SIBO: methane dominant (M+), hydrogen dominant (H+), and methane–hydrogen dominant (H+/M+) and specific anthropometric parameters. This observational study included 67 participants (W = 53, M = 14) with gastrointestinal symptoms and SIBO confirmed by lactulose hydrogen–methane breath tests (LHMBTs) using the QuinTron device. Participants underwent a body composition assessment by Bioelectrical Impedance Analysis (BIA) using the InBody Analyzer. In the H+/M+ group, body weight (p = 0.010), BMI (p = 0.001), body fat in kg (p = 0.009), body fat in % (p = 0.040), visceral fat (p = 0.002), and mineral bone content (p = 0.049) showed an inverse correlation with hydrogen (H2) gas production. These findings suggest that body weight, BMI, body fat, and mineral bone content may be inversely linked to the production of hydrogen and the risk of hydrogen–methane SIBO.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".