CoChat
Sign Up
Cited by 299Probiotics and Fermented FoodsGut microbiota and healthLiver Disease Diagnosis and Treatment

Impact of bacterial probiotics on obesity, diabetes and non-alcoholic fatty liver disease related variables: a systematic review and meta-analysis of randomised controlled trials

Open access
Koutnikova, Hana, Genser, Bernd, Monteiro-Sepulveda, Milena, Faurie, Jean-Michel, Rizkalla, Salwa, Schrezenmeir, Jürgen, Clément, Karine·2019·BMJ Open
DOI 10.1136/bmjopen-2017-017995PMC PMC6475231
Open this paper in CoChat — free accountOpen PDF

Abstract

Objective: To systematically review the effect of oral intake of bacterial probiotics on 15 variables related to obesity, diabetes and non-alcoholic fatty liver disease. Design: Systematic review and meta-analysis. Data sources: Medline, EMBASE and COCHRANE from 1990 to June 2018. Eligibility criteria: Randomised controlled trials (≥14 days) excluding hypercholesterolaemia, alcoholic liver disease, polycystic ovary syndrome and children <3 years. Results: One hundred and five articles met inclusion criteria, representing 6826 subjects. In overweight but not obese subjects, probiotics induced improvements in: body weight (k=25 trials, d=−0.94 kg mean difference, 95% CI −1.17 to −0.70, I²=0.0%), body mass index (k=32, d=−0.55 kg/m², 95% CI −0.86 to −0.23, I²=91.9%), waist circumference (k=13, d=−1.31 cm, 95% CI −1.79 to −0.83, I²=14.5%), body fat mass (k=11, d=−0.96 kg, 95% CI −1.21 to −0.71, I²=0.0%) and visceral adipose tissue mass (k=5, d=−6.30 cm², 95% CI −9.05 to −3.56, I²=0.0%). In type 2 diabetics, probiotics reduced fasting glucose (k=19, d=−0.66 mmol/L, 95% CI −1.00 to −0.31, I²=27.7%), glycated haemoglobin (k=13, d=−0.28 pp, 95% CI −0.46 to −0.11, I²=54.1%), insulin (k=13, d=−1.66 mU/L, 95% CI −2.70 to −0.61, I²=37.8%) and homeostatic model of insulin resistance (k=10, d=−1.05 pp, 95% CI −1.48 to −0.61, I²=18.2%). In subjects with fatty liver diseases, probiotics reduced alanine (k=12, d=−10.2 U/L, 95% CI −14.3 to −6.0, I²=93.50%) and aspartate aminotransferases (k=10, d=−9.9 U/L, 95% CI −14.1 to -5.8, I²=96.1%). These improvements were mostly observed with bifidobacteria ( Bifidobacterium breve , B. longum ), Streptococcus salivarius subsp . thermophilus and lactobacilli ( Lactobacillus acidophilus , L. casei , L. delbrueckii ) containing mixtures and influenced by trials conducted in one country. Conclusions: The intake of probiotics resulted in minor but consistent improvements in several metabolic risk factors in subjects with metabolic diseases. Trial registration number: CRD42016033273.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/bmjopen-2017-017995

Cites

142 of 142 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Therapies targeted against the gut microbiota improve metabolic function in humans.

    “Therapies targeted against the gut microbiota have been shown to improve the metabolic function in humans [2, 3]”

    From Dietary lipids, gut microbiota and lipid metabolism (2019) · cites this paper as [3]

  • A meta-analysis showed that B. breve, B. longum, S. thermophilus, L. acidophilus, L. delbrueckii, and L. casei can positively impact anthropometric results and metabolic risk factors, such as fasting glucose, in subjects with metabolic diseases.

    “In another meta-analysis study, it was shown that the probiotic strains B. breve, B. longum, S. thermophilus, L. acidophilus, L. delbrueckii, and L. casei can have a positive impact on anthropometric results and also on the metabolic risk factors (e.g., fasting glucose in individual glucose or insulin) in subjects with metabolic diseases [141].”

    From The Potential Impact of Probiotics on Human Health: An Update on Their Health-Promoting Properties (2024) · cites this paper as [141]

  • Probiotic strains from specific taxa (Bifidobacterium breve, B. longum, Streptococcus thermophilus, Lactobacillus acidophilus, L. delbrueckii, and Lacticaseibacillus casei) may positively impact anthropometric outcomes and metabolic risk factors such as fasting glucose or insulin in individuals with metabolic diseases.

    “Interestingly, a meta-analysis showed that probiotic strains from specific taxa (Bifidobacterium breve, B. longum Streptococcus thermophilus Lactobacillus acidophilus, L. delbrueckii, and Lacticaseibacillus casei) may positively impact anthropometric outcomes and metabolic risk factors such as fasting glucose or insulin in individuals with metabolic diseases (Koutnikova et al., 2019).”

    From Viral Infections, the Microbiome, and Probiotics (2021) · cites this paper as Koutnikova et al., 2019

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

4 retracted

Flagged first, then by citations

2 of the 144 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. [138]Rajkumar H, Kumar M, Das N, et al Effect of probiotic lactobacillus salivarius ubl s22 and prebiotic fructo-oligosaccharide on serum lipids, inflammatory markers, insulin sensitivity, and gut bacteria in healthy young volunteers: a randomized controlled single-blind pilot study. J Cardiovasc Pharmacol Ther 2015; 20: 289– 98. 10.1177/1074248414555004 25331262 · DOI · Paper page

Cited by

Sorted by citations

Related

Authors
Koutnikova, H., Genser, B., Monteiro-Sepulveda, M., Faurie, J.-M., Rizkalla, S., Schrezenmeir, J., & Clément, K.
Affiliations
  • Danone Nutricia Research, Palaiseau, France
  • University of Mannheim (DE)
  • Assistance Publique – Hôpitaux de Paris (FR)
  • Danone (France) (FR)
  • Johannes Gutenberg University Mainz (DE)
  • Inserm (FR)
Corresponding author
Clément, Karine
ORCID
Venue
BMJ Open
Publisher
BMJ
Published
2019-03
Volume
9
Issue
3
Pages
e017995
ISSN
2044-6055 (ISSN-L)
DOI
10.1136/bmjopen-2017-017995
PMC
PMC6475231
OpenAlex
W2925399545
Cited by
299
References
144
Citations by year
2026: 22 · 2025: 31 · 2024: 52 · 2023: 39 · 2022: 53 · 2021: 45 · 2020: 45 · 2019: 11 · 2018: 1
FWCI
3.47
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • BMJ Open (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
  • HighWire Press Open Archive (submittedVersion)
Funders
Danone Research
Topics
  • Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Epidemiology › Liver Disease Diagnosis and Treatment
Keywords
probiotics, obesity, type 2 diabetes, non-alcoholic fatty liver disease, overweight, body weight, body mass index, waist circumference, visceral adipose tissue, fasting blood glucose, HbA1c, insulin resistance, insulin sensitivity, gut microbiota, intestinal barrier, intestinal permeability
MeSH terms
Diabetes Mellitus, Humans, Obesity, Randomized Controlled Trials as Topic, Treatment Outcome, Dietary Supplements, Probiotics, Non-alcoholic Fatty Liver Disease

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review