The effects of chicory inulin-type fructans supplementation on weight management outcomes: systematic review, meta-analysis, and meta-regression of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Excess body weight and adiposity can adversely affect metabolic health. Prebiotics such as inulin-type fructans (ITFs) from chicory root are known to modulate gut microbiota and may improve body weight regulation. OBJECTIVES: This study aimed to assess evidence for chicory ITF supplementation to support weight management. METHODS: Eligible articles (initial search to 2021, updated to February 2023) were searched from EMBASE, MEDLINE (PubMed), and Cochrane Library. Data on primary (body weight) and secondary outcomes [body mass index (BMI), total fat mass, body fat percentage, and waist circumference] were extracted by 2 reviewers independently. Random-effects model using inverse-variance method was used. Subgroup analysis (health status and ITF type) and meta-regression (dose and duration) were evaluated. RESULTS: : 75%), all other outcomes had negligible to moderate heterogeneity. Significant reduction in body weight, BMI, and waist circumference was evident irrespective of participants' health status. There was minimal evidence that dose, duration, or type of ITF influenced the magnitude of reductions in outcomes. CONCLUSIONS: Chicory ITF supplementation may benefit weight management by reducing body weight, BMI, fat mass, waist circumference, and, to a certain extent, body fat percentage. This systematic review with meta-analysis was registered at PROSPERO as CRD42020184908.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.042 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".