The Effects of Oral Probiotics Supplementation in Overweight or Obese Postmenopausal Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

doi:10.21203/rs.3.rs-2222723/v1

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The Effects of Oral Probiotics Supplementation in Overweight or Obese Postmenopausal Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

https://doi.org/10.21203/rs.3.rs-2222723/v1

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published 28 Dec, 2022

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Gut microbiota has been identified as a unique endocrine organ that linked to the development of cardiovascular disease and other illnesses that deteriorated in overweight or obese postmenopausal women. The object of this systematic review and meta-analysis was to assess the effects of the oral supplementation with probiotics for overweight or obese postmenopausal women. We made a systematic search for randomized controlled trials (RCTs) from published to April 2022 in MEDLINE, EMBASE, Cochrane library, Web of science and ClinicalTrials.gov. The risks of bias in individual studies was assessed with the Cochrane risk of bias tool for randomized trials (RoB 2.0). Two reviewers independently selected studies and collected data. There were 6 studies came from 5 RCTs included in this systematic review. Compared with placebo, probiotics supplementation group had reductions in insulin (MD -4.20 IU/L (95% CI -8.11 to -0.30 IU/L), I² = 54%) and HOMA-IR (MD -1.25 (95% CI -2.49 to -0.01), I² = 50%). It also showed the improvements in body adiposity, lipid profile and inflammation, but they were non-significant. In addition to body adiposity and cardiovascular risk markers, there was one trail showed administration of probiotics also had an effect on iron metabolism. In conclusion, probiotics have a potential beneficial for glucose metabolism in overweight or obese postmenopausal women, but the number of current studies is small, the results need to be interpreted with caution and explained by more studies in the future.

Probiotics

Obese

Overweight

Postmenopausal women

Cardiovascular diseases

Obesity has become a worldwide epidemic and a public health issue. In 2016, the World Health Organization (WHO) reported that more than 1.9 billion adults were overweight, with over 650 million obese. Between 1975 and 2016, the global prevalence of obesity nearly tripled [1]. Obesity had a distinctly higher prevalence in adult women compared with adult men and children since 1975 [2]. Obesity increased risks for many diseases. Body mass index (BMI), which includes both fat mass and fat-free mass, has consistently shown to be a strong predictor of cardiovascular disease (CVD) [3]. Adults presenting with overweight (BMI ≥ 25 kg/m²) or obesity (BMI ≥ 30kg/m²) are at increased risk for CVD, including atherosclerotic cardiovascular disease, atrial fibrillation, and heart failure [4]. BMI-defined obesity worsens most of CVD risk factors, such as plasma lipid factors, inflammation factors, glucose resistance and insulin resistance factors [5, 6]. Not only overweight or obese, menopause status in women also can increase the risks of cardiovascular disease and metabolic disturbances, especially in those undergoing surgical menopause [7, 8]. Obesity also significantly disrupts iron (Fe) metabolism [9]. Overweight and obese people had significantly higher prevalence of those at very high risk of iron overload. Iron homeostasis dysregulations are linked to increased adiposity [10].

The trimethylamine/trimethylamine N-oxide pathway, the primary and secondary bile acid pathways, and the short-chain fatty acids pathway, are just a few of the pathways via which the gut microbiota, a new endocrine organ, contributes to the development of CVD [11, 12]. Gut microbiota communicates with distal organs has been demonstrated to influence phenotypes with CVD ranging from obesity, inflammation, insulin resistance, atherosclerosis, and thrombosis susceptibility [11]. Iron metabolism is related to inflammatory state. Iron homeostasis was regulated by hepcidin on the way of inhibiting intestinal iron absorption with response to interleukin 6 (IL-6) [13, 14].

Modulating the composition and metabolism of intestinal microbiota have the potential for prevention CVD or became a therapeutic target for CVD [15]. The study show foodborne microbes only can be transiently colonized in the gut [16]. Probiotics are foodborne bacteria, when consumed in sufficient quantities, provide health benefits to the host [17]. It is unclear if probiotics can create long-term alterations in gut flora [18].

High quality systematic review is necessary for evidence decision make [19, 20]. The object of this systematic review and meta-analysis was to assess the effects of the supplementation with probiotics for overweight or obese postmenopausal women.

2.1 Protocol and registration

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) [21]. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (registration No CRD 42022340882).

2.2 Data sources and search strategies

We searched five electronic databases systematically including EMBASE, MEDLINE, Cochrane library, Web of science and ClinicalTrials.gov from published up to April 2022. We controlled vocabulary was used whenever possible (eg, MeSH terms for MEDLINE). To increase the sensitivity of the search, keywords and their synonyms were utilized. Furthermore, the reference lists of the included papers were manually searched to discover other relevant trials. Supplementary table S1 presented the detail search strategies.

2.3 Eligibility criteria

Studies were included if they met the following inclusion criteria: (1) Studies had to be randomized controlled trials. (2) Studies had to involve postmenopausal women with overweight or obese (BMI ≥ 25kg/m², last menstruation ≥ 6 months). (3) Studies had to use probiotics supplementation as the intervention, through powder/capsules or added to foods. (4) Studies had to use placebo or regular food products as the control. (5) Studies required to report one or more outcomes interested in: such as body adiposity, inflammatory markers, lipid profile, glucose metabolism and iron metabolism. The exclusion criteria were: (1) studies use probiotics and other oral supplementation as intervention. (2) In the six months preceding the study, probiotics were consumed. (3) patients suffering from chronic gastrointestinal inflammation and other gastrointestinal conditions. (4) patients with heart disease, metabolic syndrome, cancer, diabetes, hypertension, thyroid disease, renal or hepatic dysfunction or autoimmune disease; (5) patients with inflammatory process. (6) studies with insufficient data.

2.4 study selection and data collection

Two reviewers (ZJ and BP) independently screened the title and abstract of study to select the paper met the eligibility criteria, then assessed the full text. Discrepancies were resolved by consensus. Two reviews (ZJ and YF) extracted the following information from each study: the name of the first author; publication year; country; the characteristics of enrolled patients; intervention measures (probiotics strain and probiotics dose); intervention duration; baseline and final values or change value of the outcomes. The primary outcomes are body adiposity and cardiovascular risk markers, the second outcome is iron metabolism.

2.5 quality assessment

The risk of bias was assessed with the Cochrane risk of bias tool for randomized trials (RoB 2.0) [22]. Two reviewers (ZJ and KG) independently assessed the risk, Discrepancies were resolved by discussion.

2.6 Statistical analysis

Effects of outcomes were assessed by mean difference (MD) with 95% confidence intervals (CIs) to express continuous variable. When the standard deviation (SD) of MD was not available, we used SD of baseline and post-intervention to estimate the SD of the mean change by the formula [23].

We conducted meta-analysis and pooled estimates using random effects model with the inverse variance method and DerSimonian-Laird method. Heterogeneity was determined with the Q test and I² (range: 0-100%) among individual studies. The heterogeneity was regarded as low if I² ≤ 25%, as moderate if I² in the range of 26–74% and as high if I² ≥ 75% [24]. We performed subgroup analysis if studies’ numbers were over 10. Publication bias for outcomes were planned by Egger’s test and funnel plots if there were more than 10 studies included in the same endpoint. All data analysis was carried out using meta packages in R (version 4.2.0).

3.1 Studies selection

Our searches resulted in 949 relevant citations, when removed duplicates, 674 remained were identified by screening of title and abstract. 643 papers were excluded for inappropriate outcome, population, probiotics intervention, publication, and study of design. 31 studies were qualified for thorough review, but 25 were excluded. The papers that were excluded after reviewing the full text are listed in Supplementary Table S2 with reason for exclusion. We added 1 more article that was found by hand search. Therefore, 6 eligible studies were identified in this meta-analysis (Fig. 1).

3.2 Description of included studies

The 6 studies came from 5 RCTs were published between 2015 and 2021 from Poland [9, 25–28] and Denmark [29]. The sample size of the trials varied from 39 [29] to 50 [9, 28] participants. All trials were parallel RCTs with single-blind [29] or double-blind [9, 25–28]. Mean BMI of participant varied from 27.5 to 36.7 kg/m² and mean age varied from 53 to 62 years at baseline. Different forms of probiotics were evaluated in the included RCTs. Two trials evaluated probiotics in capsules [25–27], three trials assessed probiotics by the maltodextrins and Maize starch as vehicle [9, 28, 29]. Two RCTs assessed both high dose and low dose probiotics supplement [9, 25]. The studies administered either one [29] or nine [9, 25–28] probiotics species. The lowest and maximum probiotic daily doses were 2.5x10⁹ CFU/day and 9.4x10¹⁰ CFU/day, respectively. The intervention duration was between 5 weeks and 12 weeks. The characteristics of the included studies are listed in Table 1.

Table 1

Characteristics of included studies
Author Year Country	Baseline characteristics (Probiotics/control)		Sample size (Probiotics /control)	Probiotics			Duration (weeks)	Control group	Main outcomes
Author Year Country	BMI (kg/m2)	Age (years)	Sample size (Probiotics /control)	Vehicle	Strains	Dose (CFU)	Duration (weeks)	Control group	Main outcomes
Brahe 2015 Demark	34.2/34.3	61.4/58.5	19/20	Maltodextrin	L. paracasei F19	9.4x10¹⁰	6	Placebo buns and maltodextrin	GLU, INS, HOMA-IR, Chol, HDL, LDL, TG, CRP, IL-6, TNF-α
Szulin’ska 2018 Poland	High dose: 36.6/36.1 Low dose: 36.0/36.1	High dose: 55.2/58.7 Low dose: 56.4/58.7	High dose: 24/23 Low dose: 24/23	Capsules	Bifidobacterium bifidum W23 Bifidobacterium lactis W51 Bifidobacterium lactis W52 Lactobacillus acidophilus W37 Lactobacillus brevis W63 Lactobacillus casei W56 Lactobacillus salivarius W24 Lactococcus lactis W19 Lactococcus lactis W58	High dose: 1x10¹⁰ Low dose: 2.5x10⁹	12	Placebo	BMI, IL-6, TNF-α
Szulin’ska 2018 Poland	High dose: 36.6/36.1 Low dose: 36.0/36.1	High dose: 55.2/58.7 Low dose: 56.4/58.7	High dose: 24/23 Low dose: 24/23	Capsules	Bifidobacterium bifidum W23 Bifidobacterium lactis W51 Bifidobacterium lactis W52 Lactobacillus acidophilus W37 Lactobacillus brevis W63 Lactobacillus casei W56 Lactobacillus salivarius W24 Lactococcus lactis W19 Lactococcus lactis W58	High dose: 1x10¹⁰ Low dose: 2.5x10⁹	12	Placebo	Chol, HDL, LDL, TG, GLU, INS, HOMA-IR, LP
SZYDŁOWSKA 2021 Poland	27.9/25.9	53.0/53.0	25/23	Capsules	Bifidobacterium bifidum W23 Bifidobacterium lactis W51 Bifidobacterium lactis W52 Lactobacillus acidophilus W37 Lactobacillus brevis W63 Lactobacillus casei W56 Lactobacillus salivarius W24 Lactococcus lactis W19 Lactococcus lactis W58	2.5x10⁹	5	Placebo	BMI

Table 1

(continued)
Majewska 2020 Poland	36.6/36.1	55.2/58.7	25/25	Corn starch and maltodextrin	Bifidobacterium bifidum W23 Bifidobacterium lactis W51 Bifidobacterium lactis W52 Lactobacillus acidophilus W37 Lactobacillus brevis W63 Lactobacillus casei W56 Lactobacillus salivarius W24 Lactococcuslactis W19 Lactococcus lactis W58	2.5x10⁹	12	Corn starch and maltodextrin	HCY, TNF-α, Chol, HDL, LDL, TG
Skrypnik 2019 Poland	High dose: 35.6/36.7 Low dose: 36.6/36.7	High dose: 56.0/60.5 Low dose: 56.9/60.5	High dose: 23/24 Low dose: 26/24	Maize starch and maltodextrins	Bifidobacterium bifidum W23 lactis W51 B. lactis W52 Lactobacillus acidophilus W37 L. brevis W63 L. casei W56 L. salivarius W24 Lactococcus lactis W19 Lc. lactis W58	High dose: 1x10¹⁰ Low dose: 2.5x10⁹	12	Maize starch and maltodextrins	CRP, Hair iron, Hair zinc, Serum iron, Serum zinc, Serum copper, HEPC, FAM

3.3 Risk of bias

The risk of bias based on the Cochrane collaboration tool for randomized trials was presented in Fig. 2. All the studies were considering good by Cochrane recommendations. It is shown that low risks were the most frequent in all domains: random sequence generation (100%), allocation concealment (100%), blinding of participants and personnel (100%), blinding of outcome assessment (100%), Incomplete outcome data (100%), selective reporting (66.7%). Two study didn’t submit protocol before and have insufficient information to evaluate [27, 28]. It may have unclear risks for unnecessary duplication and selective outcome-reporting bias [30].

3.4 Primary outcomes

Two trails reported mean changes and the SDs from baseline to post-intervention. Three trails reported outcomes as baseline and final mean values, from which mean changes were calculated. We selected 0.5 to account for variability between baseline measurements and final measurements across participants.

3.4.1 Effects of probiotics on body adiposity

Two studies (n = 119) that compared probiotics with placebo were included. The pooling data showed non-significant decrease in BMI (MD -0.34 kg/m² (95% CI -0.72 to 0.03 kg/m²), I² = 0%; Fig. 3A). Two studies (n = 144) reported body mass (MD -0.43 kg (95% CI -4.35 to 3.48 kg), I² = 0%; Fig. 3B), the meta-analysis showed non-significant difference between probiotics and control groups.

3.4.2 Effects of probiotics on lipid profile

There are three trials included in the meta-analysis compared probiotics with placebo in the change of total cholesterol, low-density lipoproteins (LDL) cholesterol, high-density lipoproteins (HDL) cholesterol and triglyceride levels. Data pooling showed that probiotics supplement resulted in a non-significant decrease in total cholesterol (MD -0.11 mmol/L (95% CI -0.32 to 0.11 mmol/L), I² = 9%; Fig. 4A); LDL (MD -0.14 mmol/L (95% CI -0.32 to 0.04 mmol/L), I² = 34%; Fig. 4C); triglyceride (MD -0.02 mmol/L (95% CI -0.15 to 0.11 mmol/L), I² = 0%; Fig. 4D). Probiotics either can’t increase the HDL level (MD -0.03 mmol/L (95% CI -0.09 to 0.03 mmol/L), I² = 0%; Fig. 4B).

3.4.3 Effects of probiotics on inflammatory biomarkers

Two studies (n = 107) reported high-sensitivity C-reactive protein (hsCRP) changes at the baseline and follow-up. The pooling data showed there isn’t a significant effect of probiotics use in reducing hsCRP level (MD 0.86 mg/L (95% CI -1.02 to 2.73 mg/L), I² = 76%; Fig. 5A). Two studies (n = 105) reported interleukin-6 (IL-6) and tumor necrosis factor α (TNF-α). Overall meta-analysis found non-significant reduction in IL-6 (MD -0.03 pg/mL (95% CI -0.23 to 0.17 pg/mL), I² = 47%; Fig. 5B) and TNF-α (MD -0.09 pg/mL (95% CI -0.24 to 0.06 pg/mL), I² = 59%; Fig. 5C) in probiotics group compared with placebo group.

3.4.4 Effects of probiotics on glucose metabolism

For the outcome about glucose metabolism, two studies (n = 105) compared probiotics with placebo. The pooling data showed non-significant decrease in glucose (MD -0.05 mmol/L (95% CI -0.36 to 0.25 mmol/L), I² = 59%; Fig. 6A). Insulin and HOMA-IR have a significant decrease in probiotics supplementation groups. Probiotics can statistically decrease insulin (MD -4.20 IU/L (95% CI -8.11 to -0.30 IU/L), I² = 54%; Fig. 6B) and HOMA-IR (MD -1.25 (95% CI -2.49 to -0.01), I² = 50%; Fig. 6C).

3.5 Second outcomes

There was only one study (n = 73) for the outcome about iron metabolism. The Fe content of hair was lower in both two dose probiotics supplementary group (high dose: 1x10¹⁰ CFU/day vs. low dose: 2.5x10⁹ CFU/day), the serum zinc (Zn) concentration became higher in the low dose group and got to lower in the high dose group compared with the baseline status. The serum erythroferrone (FAM) concentration became lower in the high dose group and serum ferritin (Fe) concentration got to higher in the low dose group compared with the baseline [9].

This systematic review assessing the effects of probiotics supplementation in overweight or obese postmenopausal women included 5 randomized trials. The meta-analysis of the trials evaluating the probiotics vs. control suggest there were obvious decreases in insulin reduction (MD = -4.20 IU/L) and HOMA-IR reduction (MD = -1.25). Other evaluated parameters, body adiposity, lipid profile, inflammatory biomarkers and glucose have shown improvements after probiotics consumption, but these improvements were not significant. Probiotics supplementary also may influence iron metabolism in obese postmenopausal female patients, it need more trails to verify.

However, to the best of our knowledge, this is the first review including only overweight or obese postmenopausal women to assess the effects of probiotics. Compare this systematic review with other studies aimed at overweight or obese adults, we can find there have some consistence with previous systematic reviews. This review showed administration of probiotics can make a reduction of BMI (MD = -0.34 kg/m²) but the reduction is not significant (p = 0.07). In previous review aimed at overweight or obese adults, including male and female, Pontes et al. [31] presented a significant decrease which was 0.24 kg/m², Wang et al.[32] shown a significant reduction of 0.3 kg/m², Borgeraas et al. [33] shown an non-significant reduction of 0.27 kg/m². This disagreement may be related to the inclusion of newest clinical trials in Pontes et al. [31], such as Hajipoor [34], Majewska [28], Michael [35], Skrypnik [9] et al. Our studies included a clinical trial published in 2021 [27] which not included in before reviews. Energy restriction is the necessary condition for BMI decrease [32], all studies designed in overweight or obese postmenopausal women weren’t accompanied with intervention restriction, this may be related to our non-significant result. Agreement with Karine’s funding [31], our study showed a reduction in serum insulin and HOMA-IR level, suggesting a possible beneficial role in the sensitivity of insulin. The effect of probiotics on glucose was not significant, it’s also consisted with previous study [31]. The potential mechanisms may be the gut microbiota is modified by probiotics supplementation and have an effect on modulating glucose metabolism [36]. Glucagon-like peptide (GLP)-1 is released by gut enteroendocrine L cells and can take direct actions on hepatocytes by activating genes involved in fatty acid β-oxidation and insulin sensitivity [36, 37]. Probiotics may influence inflammatory pathways and insulin sensitivity by modifying the gut microbiome and the concentration of plasma lipopolysaccharides [38]. There also showed the improvements in body adiposity, lipid profile and inflammatory biomarkers, but these improvements were not significant. For these factors, the number of current studies is small, and the results of meta-analysis need to be interpreted with caution and explained by more studies in the future.

There were some strengths of this systematic review. First, this was the first systematic review to evaluate the effects of probiotics in overweight or obese postmenopausal women. Second, the study included in this systematic review were recently published between 2015 to 2021. Third, all the studies were considered good by Cochrane recommendations and most outcomes showed a low or moderate level of heterogeneity. This study also had some limitations. First, the number of studies met the including criteria of is few, we had better include more clinical trials to make an evaluate about administration of probiotics in the future. Second, because of fewer than 10 studies with the same endpoint, we didn’t analysis publication bias, it’s too low to distinguish chance from real asymmetry.

This systematic review and meta-analysis suggest that the administration of probiotics have beneficial effects on glucose metabolism for overweight or obese postmenopausal women. It also included a trail show administration of probiotics may have an effect on iron metabolism. But the effects on improve body adiposity, lipid profile and inflammatory biomarkers are uncertain, it need more clinical trials to know more.

Author Contributions

Conceived and designed the experiments: Kehu Yang, Zijun.Li, Yanfei. Li, Yu Wu; Performed the data extraction: Selected the studies: Zijun.Li, Bei Pan, Mina Ma; Performed the data extraction: Zijun Li, Yanfei. Li, Minyan Yang; Analyzed the data: Zijun Li, Xiaoman Wang; Quality Appraisal: Ke Guo, Chengdong Qiao; Wrote the paper: Kehu Yang, Zijun.Li, Yanfei. Li. All authors have read and approved the manuscript.

Funding

This work was supported by the Major Project of the National Social Science Fund of China: Research on the Theoretical System, International Experience and Chinese Path of Evidence-based Social Science under Grant 19ZDA142.

Conflict of Interest

The authors declare that they have no conflict of interest.

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No competing interests reported.

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The Effects of Oral Probiotics Supplementation in Overweight or Obese Postmenopausal Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

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Abstract

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1. Introduction

2. Methods

2.1 Protocol and registration

2.2 Data sources and search strategies

2.3 Eligibility criteria

2.4 study selection and data collection

2.5 quality assessment

2.6 Statistical analysis

3. Results

3.1 Studies selection

3.2 Description of included studies

3.3 Risk of bias

3.4 Primary outcomes

3.4.1 Effects of probiotics on body adiposity

3.4.2 Effects of probiotics on lipid profile

3.4.3 Effects of probiotics on inflammatory biomarkers

3.4.4 Effects of probiotics on glucose metabolism

3.5 Second outcomes

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1