Front. Microbiol.Frontiers in MicrobiologyFront. Microbiol.1664-302XFrontiers Media S.A.10.3389/fmicb.2025.1633434MicrobiologySystematic ReviewEffects of Bifidobacterium on metabolic parameters in overweight or obesity adults: a systematic review and meta-analysisHuangJunmei*ChengHaoDepartment of Nutrition, Sanya Central Hospital (The Third People's Hospital of Hainan Province), Sanya, China
Edited by: Malgorzata Ziarno, Warsaw University of Life Sciences, Poland
Reviewed by: Francesco Pizza, ASL Napoli 2 Nord, Italy
Chang Hong, Baotou Medical College, China
So Youn An, Wonkwang University, Republic of Korea
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Objective
This study endeavors to elucidate how Bifidobacteria supplementation affects metabolic parameters among overweight or obese populations.
Methods
A systematic review and meta-analysis were carried out leveraging PubMed, Embase, Cochrane Library, and Web of Science. Merely randomized controlled trials (RCTs) were included.
Results
21 RCTs were encompassed for our final analysis. Bifidobacteria supplementation was effective in weight management for overweight or obese patients. The experimental group receiving Bifidobacteria exhibited a marked decrease in weight (WMD: −0.607 kg; 95% CI: −0.910, −0.303, I2 = 11.9%) and BMI (WMD: −0.214 kg/m2; 95% CI: −0.259, −0.169, I2 = 4.1%) in contrast to the control, although the significant effect was not noted on WC. Moreover, while Bifidobacteria supplementation led to no marked drop in FBG or HbA1c, it improved the insulin (SMD: -0.268; 95% CI: −0.470, −0.066, I2 = 5.4%). However, there were no evident variations in TC, TG, HDL-C, or LDL-C across groups.
Conclusion
Our study findings confirmed that Bifidobacteria contributes to a slight reduction in weight and BMI among the overweight or obese populations, making it a potential adjunctive approach for weight management. Furthermore, it may help regulate insulin levels, though its impact on hyperglycemia and hyperlipidemia remains limited.
Bifidobacteriaoverweight or obesityweightblood glucoseblood lipidssection-at-acceptanceMicroorganisms in Vertebrate Digestive SystemsIntroduction
As the global obesity epidemic continues to intensify, overweight and obesity have become significant public health concerns worldwide (GBD 2021 Adult BMI Collaborators, 2025). Obesity not only diminishes an individual’s quality of life but is also strongly associated with various chronic diseases, such as cardiovascular diseases, type 2 diabetes mellitus (T2DM), certain cancers, and a range of metabolic disorders (Blüher, 2019). Consequently, identifying effective interventions for the prevention and treatment of obesity has become increasingly critical.
In recent, growing attention has been directed towards the relationship between the gut microbiota and obesity (Asadi et al., 2022). The gut microbiota, an intricate ecosystem involving trillions of microorganisms, is crucial in host metabolism, immunity, as well as disease susceptibility (Geng et al., 2022). Among these microorganisms, Bifidobacteria, an important component of the gut microbiota, has garnered particular attention due to its potential health benefits (Sarita et al., 2024). Bifidobacteria are Gram-positive, anaerobic probiotics known to exert multiple positive effects on host health, including improving gut barrier function, modulating immune responses, and influencing energy metabolism (Amabebe et al., 2020). Multiple studies have demonstrated that the abundance of Bifidobacterium in the gut of obese individuals is generally lower than that in healthy populations (Leite et al., 2024; Gong et al., 2022). This dysbiosis may be associated with high-fat diets, metabolic disturbances, and chronic inflammation (Hills et al., 2019). Experimental evidence indicates that reduced Bifidobacterium abundance, accompanied by fat accumulation and inflammation, can be ameliorated by supplementation with specific Bifidobacterium strains, leading to attenuated weight gain and reduced fat deposition in obese mice (Zha et al., 2024). Furthermore, Da Silva et al. (2020) found that the proportion of Bifidobacterium in the gut microbiota of obese children was significantly lower than that of healthy counterparts. Some studies have suggested that the abundance of Bifidobacterium may be restored following bariatric surgery or dietary interventions (Seganfredo et al., 2017). The potential mechanisms may involve metabolic regulation mediated by short-chain fatty acids (SCFAs). For example, acetate and propionate can activate G-protein-coupled receptors (GPR41/GPR43), thereby suppressing lipogenesis and promoting energy utilization (Yun et al., 2024). Butyrate may stimulate the secretion of GLP-1 and PYY, reducing appetite through hormonal regulation (Horiuchi et al., 2020). In addition, SCFAs can enhance AMP-activated protein kinase (AMPK) activity, thereby facilitating fatty acid β-oxidation and promoting fat catabolism. Bifidobacterium may also influence bile acid metabolism by activating farnesoid X receptor (FXR) and TGR5, thereby improving glucose and lipid metabolism (Joyce and Gahan, 2016). Although studies have suggested that Bifidobacteria may be closely linked to weight management and glucose and lipid metabolic homeostasis in the population with excess weight or obesity, related findings show discrepancies, and a systematic evaluation and quantitative analysis are lacking. For instance, Bai et al. (2024) proved that the short-chain Bifidobacterium BBr60 markedly lowered weight, body mass index (BMI), and FBG, and modulated lipid profiles safely and effectively. In contrast, Sudha et al. (2019) found no significant changes in blood lipids or blood glucose levels. Additionally, some studies have indicated that yogurt containing Bifidobacteria does not produce significant changes in weight or BMI in overweight or obese populations.
However, the evidence remains inconsistent. Some trials have demonstrated beneficial effects of Bifidobacteria supplementation on weight, glucose, and lipid metabolism, while other studies report negligible or no benefits. To date, no comprehensive quantitative synthesis has been performed to resolve these discrepancies. Therefore, this study seeks to unveil the effects of Bifidobacteria supplementation on metabolic parameters within individuals with excess weight or obesity based on randomized controlled trials (RCTs) via systematic review and meta-analysis.
MethodsRegistration and PRISMA statement
This review complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was prospectively registered in PROSPERO (Registration No. CRD42025635324) (Page et al., 2021).
Literature searchData sources and search scope
A comprehensive literature search was performed in four online databases (PubMed, Embase, Cochrane Library, and Web of Science) to identify RCTs. The search covered the period from database inception to December 3, 2024. Keywords such as “Bifidobacterium,” “obesity,” and “overweight” were used as both subject terms and free words in the search. The search strategy is presented in Table 1. The references of prior systematic reviews were also checked for eligible RCTs.
Search strategy and results.
Pubmed
#
Query
Results
1
Overweight[MeSH Terms]
289,803
2
Obesity[MeSH Terms]
277,956
3
‘adipose tissue hyperplasia’[Title/Abstract] OR ‘adipositas’[Title/Abstract] OR ‘adiposity’[Title/Abstract] OR ‘alimentary obesity’[Title/Abstract] OR ‘body weight, excess’[Title/Abstract] OR ‘corpulency’[Title/Abstract] OR ‘fat overload syndrome’[Title/Abstract] OR ‘nutritional obesity’[Title/Abstract] OR ‘obesitas’[Title/Abstract] OR ‘obesity’[Title/Abstract] OR ‘overweight’[Title/Abstract]
406,017
4
Bifidobacterium[MeSH Terms]
7,796
5
Bifidobacterium[Title/Abstract]
14,126
6
(#1 OR #2 OR #3) AND (#4 OR #5)
873
Eligibility criteria
Inclusion criteria: (1) Adults (≥18) diagnosed by a physician with overweight (BMI 25–29.9 kg/m2) or obesity (BMI 30–34.9 kg/m2); (2) Explicit use of Bifidobacterium as an intervention; (3) A control group receiving either a placebo or another type of intervention not involving Bifidobacterium, with all other conditions equivalent to the experimental group, ensuring comparability (e.g., routine care or blank control); (4) Outcome measures including anthropometric measurements, blood glucose, or lipid laboratory result; (5) Randomized controlled trials (RCTs). Exclusion criteria: (1) Duplicates, systematic reviews, and meta-analyses; (2) Literature reviews, case reports, non-English publications, animal studies, letters to the editor, and narrative reviews; (3) Full texts were inaccessible, data could not be extracted, or the studies were ineligible.
Literature screening and data extraction
Two researchers independently filtered the literature, collected related data, and assessed study quality. EndNote was utilized during the screening process. The extracted data encompassed bibliographic information (authors, publication year, country), study characteristics (sample size, bacterial strains, study outcomes), and participant characteristics (age, BMI). Data extraction was conducted utilizing Excel. Dissents were addressed via discussion or consultation with a third researcher.
Outcome measures
The primary outcomes assessed in this meta-analysis were: weight, BMI, as well as waist circumference (WC). Secondary outcomes encompassed fasting blood glucose (FBG), glycated hemoglobin (HbA1c), insulin, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C).
Risk of bias assessment
The risk of bias was rated independently by two reviewers. Dissents were addressed after discussion or judgment of a third party. Concerning quality assessment, both reviewers used the NIH RCT Quality Assessment Tool for study quality evaluation. There were 14 items, each assessed as “Yes” or “No” based on the study’s design and implementation standards (NIH, n.d.). In case of discrepancies during the evaluation, a third researcher was consulted to ensure fairness and consistency. Studies were rated for potential bias via a scoring scale, with three distinct categories: high risk (0–5, poor), moderate risk (6–10, fair), and low risk (11–14, good).
Statistical analysis
Data analysis was enabled by Stata MP 15. Continuous data were shown in standardized mean difference (SMD) or mean difference (MD). An SMD of < 0.2 indicates a negligible difference between groups, whereas a value ranging from 0.2 to 0.49 suggests a small difference. A value between 0.5 and 0.79 represents a moderate difference, and a value ≥ 0.8 denotes a substantial difference across groups. For dichotomous data, the risk ratio (RR) and its 95% confidence interval (CI) were computed. Heterogeneity was detected via the I2 statistic and the Q-test. When the I2 value exceeded 50% and the p < 0.05, a random-effects model was applied; otherwise, a fixed-effects model was used. The robustness of our results was rated through sensitivity analyses. For meta-analyses involving over 10 studies, possible publication bias was examined utilizing funnel plots and Egger’s test. In cases of bias, the effect on the results was evaluated through the trim-and-fill approach.
ResultsLiterature search results
Based on the predefined search strategy, a preliminary search of the databases identified 4,105 articles. After screening titles and abstracts, 922 duplicate entries were excluded, resulting in 3,159 articles being discarded. The remaining 28 articles were subjected to full-text review. Four articles were excluded owing to unavailable full texts, two owing to the inability to extract data, and one due to failure to meet the inclusion criteria. Ultimately, 21 eligible RCTs were included, as shown in Figure 1.
Study screening flowchart.
Flowchart illustrating the identification of studies via databases. Records identified from Pubmed (873), Cochrane (334), Embase (1515), Web of Science (1383) total 4105. After removing 922 duplicates, 3183 records are screened. Out of 3183, 28 reports are sought for retrieval, with 4 not retrieved. Twenty-four reports are assessed for eligibility; 3 are excluded due to data extraction issues or research mismatch. Ultimately, 21 studies are included in the review.Study characteristics
The baseline characteristics of the 21 included RCTs are summarized in Table 2. Of these, 13 (Bai et al., 2024; Sudha et al., 2019; AlMalki et al., 2024; Banach and Jedut, 2020; Hadi et al., 2019; Kanazawa et al., 2021; Lauw et al., 2023; Minami et al., 2015; Sato et al., 2024; Tajabadi-Ebrahimi et al., 2017; Wu et al., 2024; Zarrati et al., 2019; Zarrati et al., 2014) were conducted in Asian countries, 6 (Hibberd et al., 2019; Kobyliak et al., 2018; Kopp et al., 2023; Majewska et al., 2020; Michael et al., 2021; Parascinet et al., 2023) in European countries, and 2 (Crovesy et al., 2021; Sergeev et al., 2020) in the United States and Brazil, respectively. The studies were published between 2014 and 2024 and collectively enrolled 1,392 participants. All studies used BMI as the indicator for overweight or obesity. According to the World Health Organization’s classification (WHO, 2024), overweight was defined as a BMI between 25 and 29.9 kg/m2, while obesity was confirmed by a BMI of 30 kg/m2 or higher. 8 studies (Bai et al., 2024; Sudha et al., 2019; Kanazawa et al., 2021; Minami et al., 2015; Wu et al., 2024; Zarrati et al., 2019; Zarrati et al., 2014; Parascinet et al., 2023) reported the use of Bifidobacterium breve, three studies (Hadi et al., 2019; Tajabadi-Ebrahimi et al., 2017; Michael et al., 2021) used Bifidobacterium longum, five studies (Sato et al., 2024; Kobyliak et al., 2018; Majewska et al., 2020; Sergeev et al., 2020; AlMalki et al., 2024) used a mixed Bifidobacterium species, two studies (Banach and Jedut, 2020; Hibberd et al., 2019) used Bifidobacterium animalis, and three studies (Lauw et al., 2023; Kopp et al., 2023; Crovesy et al., 2021) used Bifidobacterium lactis. The NIH quality assessment indicated that 11 studies (Bai et al., 2024; AlMalki et al., 2024; Sato et al., 2024; Tajabadi-Ebrahimi et al., 2017; Wu et al., 2024; Zarrati et al., 2019; Zarrati et al., 2014; Kobyliak et al., 2018; Majewska et al., 2020; Michael et al., 2021; Crovesy et al., 2021) had low risk of bias, while 10 studies (Sudha et al., 2019; Banach and Jedut, 2020; Kanazawa et al., 2021; Lauw et al., 2023; Minami et al., 2015; Hibberd et al., 2019; Kopp et al., 2023; Parascinet et al., 2023; Crovesy et al., 2021; Sergeev et al., 2020) exhibited moderate risk of bias, as detailed in Supplementary Table 1.
Characteristics of studies selected and included in the meta-analysis.
BMI, body mass index; WC, waist circumference; FBG, fasting blood glucose; HbA1c, glycated hemoglobin; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol.
Primary outcomesEffects of <italic>Bifidobacterium</italic> on weight management
Eighteen studies reported on the relationship between Bifidobacterium supplementation and weight change. Sensitivity analysis demonstrated that the study conducted by Kobyliak had a considerable impact on the overall findings, as illustrated in Supplementary Figure 1. Upon exclusion of this study, the experimental group receiving Bifidobacterium supplementation showed a significantly greater reduction in body weight compared to the control group (WMD: −0.607 kg; 95% CI: −0.910,–0.303; I2 = 11.9%), as shown in Figure 2. Funnel plot symmetry and the Egger test (p = 0.804) suggested no significant publication bias, as presented in Supplementary Figure 2.
Forest plot for weight.
Forest plot showing weighted mean differences (WMD) with 95% confidence intervals (CI) for multiple studies. Each line represents a study with its WMD, CI, and percentage weight. The overall effect is summarized at the bottom, indicated by a diamond shape. Horizontal lines show confidence intervals for each study.
19 studies explored how Bifidobacterium supplementation influences BMI. Our meta-analysis demonstrated a notably larger BMI decline in the experimental group relative to the control (WMD: −0.214 kg/m2; 95% CI: −0.259, −0.169, I2 = 4.1%) (Figure 3). Eight studies examined the impact of Bifidobacterium on WC, but the difference across groups was insignificant (WMD: −0.353 cm; 95% CI: −0.759, −0.053, I2 = 88.3%) (Figure 4). Sensitivity analyses for BMI and WC indicated robust results, as shown in Supplementary Figures 3, 4. Both the funnel plot and Egger’s test (p = 0.867) demonstrated no discernible publication bias (Supplementary Figure 5).
Forest plot for BMI.
Forest plot showing the weighted mean differences (WMD) and 95% confidence intervals (CI) for various studies, highlighting individual study results as black diamonds and their CIs as horizontal lines. The overall effect is represented by a blue diamond at the bottom, indicating a WMD of -0.21 with a CI of -0.26 to -0.17. The vertical line at zero indicates no effect. The plot weights studies based on precision, with Kobyliak (2018) having the highest weight of 69.38%. Heterogeneity is indicated by I-squared at 4.1% and p-value at 0.406.
Forest plot for waist circumference.
Forest plot from a meta-analysis shows weighted mean differences (WMD) with confidence intervals for various studies. Each study, labeled by year and author, is represented by a dot with a horizontal line. The overall effect size is depicted at the bottom with a diamond shape, indicating a WMD of -0.35 with this analysis reported to have high heterogeneity (I-squared = 88.3%).Secondary outcomesEffects of <italic>Bifidobacterium</italic> on glycemic control
Ten studies evaluated how Bifidobacterium supplementation influences FBG within the cohort with excess weight or obesity. Bifidobacterium did not markedly affect FBG (SMD: -0.143; 95% CI: −0.302, −0.016, I2 = 0.0%) (Figure 5). Our sensitivity analysis indicated robustness. Egger’s test (p = 0.215) and the funnel plot demonstrated no publication bias, as depicted in Supplementary Figures 6, 7.
Forest plot for fasting blood glucose.
Forest plot showing effect sizes from nine studies with 95% confidence intervals (CI) and percentage weights. Individual study results vary from negative to positive, with an overall standardized mean difference (SMD) of -0.14 (95% CI: -0.30, 0.02). The summary estimate is represented by a diamond. Heterogeneity is low with I-squared at 0.0% and a p-value of 0.533.
Seven studies investigated the effect of Bifidobacterium on HbA1c, demonstrating insignificant variations across groups (WMD: −0.093%; 95% CI: −0.277, −0.091, I2 = 56.4%) (Figure 6). However, regarding insulin levels, seven studies reported a notable decrease in insulin levels in the Bifidobacterium supplementation cohort (SMD: −0.268; 95% CI: −0.470, −0.066, I2 = 5.4%) (Figure 7). These findings were robust after sensitivity analysis, as presented in Supplementary Figures 8, 9.
Forest plot for glycated hemoglobin.
Forest plot showing weighted mean differences (WMD) with 95% confidence intervals for various studies on a vertical axis. Individual study points are marked with black diamonds and horizontal lines, indicating each study's results and variability. The overall effect is represented by a diamond, with a central vertical line marking zero effect. Study weights are indicated on the right, and the note mentions that weights are from random effects analysis.
Forest plot for insulin.
Forest plot showing standardized mean differences (SMD) and 95% confidence intervals for seven studies. Individual study results are plotted with horizontal lines and diamonds, with a vertical dashed line indicating no effect. Overall results are summarized at the bottom, showing a pooled SMD of -0.27 with a 95% confidence interval of -0.47 to -0.07. The heterogeneity is low (I-squared = 5.4%, p = 0.398).Effects of <italic>Bifidobacterium</italic> on lipid metabolism
To unravel how Bifidobacterium impacts lipid metabolism, our study incorporated studies evaluating TC, TG, HDL-C, and LDL-C. The effects on lipid levels were insignificant.
Specifically, eleven studies regarding TC, TG, and HDL-C suggested insignificant effects of Bifidobacterium supplementation (TC: SMD: -0.082; 95% CI: −0.235, 0.071, I2 = 41.4%; TG: SMD: -0.423; 95% CI: −0.939, 0.094, I2 = 90.2%; HDL-C: SMD: 0.060; 95% CI: −0.209, 0.328, I2 = 65.6%) (Figures 8–10). The robustness of the foregoing results was proved by utilizing sensitivity analysis. Publication bias did not exist in funnel plots and Egger’s test (Supplementary Figures 10–15).
Forest plot for total cholesterol.
Forest plot displaying standardized mean differences (SMD) with 95% confidence intervals for multiple studies: AlMalki, Bai, Hadi, Hibberd, Kanazawa, Lauw, Majewska, Parascinet, Sudha, Ebrahimi, Wu, and overall result. The overall SMD is -0.08, 95% CI (-0.24, 0.07) with I-squared at 41.4% and p-value of 0.073. Each horizontal line represents a study's effect estimate and confidence interval. The diamond at the bottom represents the overall effect estimate.
Forest plot for triglycerides.
Forest plot showing results of multiple studies. Each study, identified by author and year, has a square and horizontal line representing the standardized mean difference (SMD) and 95% confidence interval. Weights of studies vary, with an overall SMD of -0.42. The overall effect is marked by a diamond shape, with high heterogeneity noted (I-squared = 90.2%, p = 0.000).
Forest plot for high-density lipoprotein.
Forest plot displaying standardized mean differences (SMD) with 95% confidence intervals for various studies. The plot includes individual study estimates and weights such as AlMalki (2024) SMD -0.11, Wu (2024) SMD 0.42. The overall effect is shown with an SMD of 0.06. A dashed line at zero indicates no effect. Weights calculated using a random effects model, with heterogeneity I-squared 65.6% and p-value 0.001.
Eight studies examined the impact of Bifidobacterium on LDL-C and revealed no evident effect (SMD: -0.108; 95% CI: −0.379, 0.162, I2 = 52.6%) (Figure 11). Sequential exclusion of individual studies in sensitivity analyses did not markedly affect the results, as presented in Supplementary Figure 16.
Forest plot for low-density lipoprotein.
Forest plot displaying standardized mean differences (SMD) with 95% confidence intervals for eight studies from 2016 to 2024. Individual study weights and overall effect size are indicated. Weights are derived from random effects analysis. Overall effect (I-squared = 52.0%, p = 0.039).Discussion
This meta-analysis assessed the impact of Bifidobacterium supplementation on individuals with overweight or obesity. Our study on 21 RCTs proved that Bifidobacterium supplementation is effective in managing weight of the overweight or obese patients. The Bifidobacterium cohort had a prominent decline in weight and BMI, though no significant effect on WC was observed. Furthermore, supplementation with Bifidobacterium did not notably lower FBG or HbA1c but was linked to improved insulin levels. In contrast, marked differences were not found across the two groups with regard to TC, TG, HDL-C, and LDL-C. Therefore, Bifidobacterium supplementation is beneficial for overweight or obese individuals, potentially aiding in weight control and improving insulin secretion.
Probiotics, including Bifidobacterium, have been shown to help manage overweight and obesity (Geng et al., 2022). Our findings prove that Bifidobacterium supplementation lowers the weight and BMI of the population with excess weight or obesity, which aligns with previous research results (Sadeghi et al., 2024). Bifidobacterium may promote the production of SCFAs, such as acetate, propionate, and butyrate, in the gut. These SCFAs can activate the AMPK pathway in the liver, muscle, and adipose tissues. AMPK phosphorylates acetyl-CoA carboxylase (ACC), thereby inhibiting fatty acid synthesis, while simultaneously activating carnitine palmitoyltransferase-1 (CPT-1), which facilitates the mitochondrial uptake and oxidation of fatty acids, enhancing lipid catabolism (Yun et al., 2024). In overweight or obese individuals, sustained supplementation with Bifidobacterium may reduce excessive lipid absorption. Furthermore, SCFAs can activate free fatty acid receptors (FFAR2/3) on intestinal epithelial cells, stimulating the secretion of glucagon-like peptide-1 (GLP-1) and peptide YY (PYY), which suppress the release of the appetite-stimulating hormone ghrelin (Horiuchi et al., 2020). This leads to reduced food intake and subsequent caloric restriction, thereby contributing to a natural decline in BMI. Individuals with obesity often exhibit lower levels of SCFAs produced by gut microbiota; supplementation with probiotics such as Bifidobacterium can enhance SCFA production, increase satiety, and promote weight reduction. López-Moreno et al. (2020) noted marked weight and BMI drops in a cohort receiving probiotics containing Bifidobacterium in contrast to a placebo cohort. Nevertheless, this meta-analysis found no significant reduction in WC among overweight or obese individuals receiving Bifidobacterium supplementation. Ejtahed et al. (2019) demonstrated that probiotic intervention over 2–24 weeks was effective in reducing WC in overweight or obese subjects, which may be attributed to the relatively shorter intervention period (less than 12 weeks) in the present study. Additionally, there exist gender differences in probiotic effects on weight management among the overweight or obese population, with some studies noting a reduction in WC only in women (Cao et al., 2024). This may also explain the insignificant effect on WC in our findings.
Our study demonstrated that supplementation with Bifidobacterium significantly reduced insulin levels in overweight or obese individuals. This effect may be attributed to the capacity of Bifidobacterium to reshape the composition and function of the gut microbiota. In such populations, its metabolic byproducts, particularly SCFAs, may activate the gut-metabolism axis, enhance insulin signaling, reduce adipose tissue accumulation, improve insulin sensitivity, and ultimately lower the risk of obesity-related diseases (Guney-Coskun and Basaranoglu, 2024). Teo et al. (2024) also proved that probiotics containing Bifidobacterium were more effective in improving insulin levels. Although the present study supports the beneficial role of Bifidobacterium in modulating insulin levels, the differences in the results are relatively small. Further randomized controlled trials and prospective cohort studies are warranted to elucidate the role of Bifidobacterium in mitigating insulin resistance among obese populations. Furthermore, this meta-analysis found no significant changes in FBG or HbA1c levels. Barengolts et al. (2019) also reported no changes in HbA1c, FBG, or fasting insulin following consumption of Bifidobacterium-containing probiotic yogurt in the obese cohort with T2DM in comparison to traditional yogurt. This may be because Bifidobacterium’s effect on postprandial blood glucose is more prominent. Therefore, additional research is necessitated to verify the efficacy of Bifidobacterium supplementation in managing blood glucose levels in overweight or obese individuals.
This study found no significant effect of Bifidobacterium on lipid metabolism in the experimental group, suggesting that Bifidobacterium may primarily exert its effects through energy metabolism rather than lipid redistribution. Dong et al.’s meta-analysis (Dong et al., 2019) also reported insignificant disparities in TC, TG, or HDL between the intervention group (which used probiotic foods and Bifidobacterium-containing supplements) and the control group in individuals with metabolic syndrome. Additionally, other studies (Ruscica et al., 2019) have indicated that Bifidobacterium longum evidently reduces serum TC and LDL-C in the hyperlipidemic population by influencing gut microbiota composition and fecal metabolic products. This discrepancy possibly arises from differences in the specific strains of Bifidobacterium in this study, as the lipid-lowering effects of different Bifidobacterium strains may vary. Although our study showed no significant effect on these lipid parameters, interest in the role of Bifidobacterium in lipid metabolism remains strong in the academic community. High-quality RCTs are necessitated to better elucidate the efficacy of Bifidobacterium in lipid metabolism.
This study has two limitations. First, heterogeneity in the studies on Bifidobacterium may confound the results due to differences in ethnicity, sex, strain types, and dosages. Second, the lack of standardization in the units of measurement for blood glucose and lipids may introduce measurement errors. However, efforts were made in this study to minimize such effects through standardization.
Conclusion
In conclusion, this study suggests that supplementation with Bifidobacterium exerts a moderate positive effect on lowering the weight and BMI of overweight or obese people, indicating that Bifidobacterium may serve as an adjunct in weight management for these individuals. Additionally, our findings demonstrate a beneficial role of Bifidobacterium in regulating insulin levels in overweight or obese patients, though its effects on improving hyperglycemia and hyperlipidemia were limited. Future studies should focus on high-quality clinical trials that consider individual factors such as gender, fat distribution, and strain specificity. Specific Bifidobacterium strains may have superior effects, and more research is necessitated to verify the role of Bifidobacterium in managing weight, providing valuable insights into its potential applications.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2025.1633434/full#supplementary-material
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