Beneficial effects of the probiotics and synbiotics supplementation on anthropometric indices and body composition in adults: A systematic review and meta‐analysis

Studies have suggested that probiotics and synbiotics can improve body weight and composition. However, randomized controlled trials (RCTs) demonstrated mixed results. Hence, we performed a systematic review and meta‐analysis to evaluate the effectiveness of probiotics and synbiotics on body weight and composition in adults. We searched PubMed/Medline, Ovid/Medline, Scopus, ISI Web of Science, and Cochrane library up to April 2023 using related keywords. We included all RCTs investigating the effectiveness of probiotics and/or synbiotics supplementation on anthropometric indices and body composition among adults. Random‐effects models were applied for performing meta‐analyses. In addition, we conducted subgroup analyses and meta‐regression to explore the non‐linear and linear relationship between the length of follow‐up and the changes in each outcome. We included a total of 200 trials with 12,603 participants in the present meta‐analysis. Probiotics or synbiotics intake led to a significant decrease in body weight (weighted mean difference [WMD]: −0.91 kg; 95% CI: −1.08, −0.75; p < 0.001), body mass index (BMI) (WMD: −0.28 kg/m2; 95% CI: −0.36, −0.21; p < 0.001), waist circumference (WC) (WMD: −1.14 cm; 95% CI: −1.42, −0.87; p < 0.001), waist‐to‐hip ratio (WHR) (WMD: −0.01; 95% CI: −0.01, −0.00; p < 0.001), fat mass (FM) (WMD: −0.92 kg; 95% CI: −1.05, −0.79; p < 0.001), and percentage of body fat (%BF) (WMD: −0.68%; 95% CI: −0.94, −0.42; p < 0.001) compared to controls. There was no difference in fat‐free mass (FFM) and lean body mass (LBM). Subgroup analyses indicated that probiotics or synbiotics administered as food or supplement resulted in significant changes in anthropometric indices and body composition. However, compared to controls, FM and %BF values were only reduced after probiotic consumption. Our results showed that probiotics or synbiotics have beneficial effects on body weight, central obesity, and body composition in adults and could be useful as an add on to weight loss products and medications.


| INTRODUCTION
Obesity is a significant public health threat, which contributes to the increased mortality from non-communicable diseases (NCDs), including atherosclerotic cardiovascular diseases, type 2 diabetes (T2DM), hypertension, and certain types of cancer. 1 The prevalence of obesity has nearly been tripled since 1970s with two-thirds of the Australian and US population being currently either overweight or obese. 2,3It is projected that there will be one billion adults with obesity by 2025, which is a fifth of the world population. 4,5Apart from its health and economic impact at the individual level, obesity crisis places an enormous socioeconomic burden on healthcare resources. 6Although improving eating behaviors, increasing physical activity, and pharmacological therapies are well-established interventions for weight loss and its maintenance, 7 not all people with obesity can adhere to these lifestyle modifications.Although we have some effective medications for weight loss, many of these have significant contraindications and side effects and cannot be used in all patients.Hence, there is a need to develop a new approach of the obesity management.
There are large and complex microbial communities in the human colon, referred to as gut microbiota (GM), living in a close relationship with the host. 8,9The GM contributes to a vast array of the host's metabolic and signaling pathways, such as energy extraction from food and regulating multiple pathways between organs such as the gut, liver, and muscle. 10,11It is also possible for GM to affect the host's eating behavior by altering their appetite and hormone levels. 12In addition, the GM produces several enzymes not encoded by the human genome, contributing to carbohydrates and lipids degradation, polyphenols and vitamin synthesis, and generating fermentation products, such as short-chain fatty acids (SCFAs). 8,13,146][17][18] Furthermore, the GM has considerable proteolytic abilities, converting ingested dietary protein into shorter peptides and amino acids. 19,20ticeably, the interaction between the host and the GM affects body composition and anthropometric measurements such as body weight (BW), body mass index (BMI), and fat mass (FM). 21,22Modifying intestinal microbiota might open up new possibilities for the obesity management.One main mechanism through which the metabolic activity or the GM composition may be altered is by direct delivery of desirable exogenous microorganisms 23,24 in the forms of "probiotic" and "synbiotic."Probiotics are defined as live microorganisms with putative health-promoting potencies when applied to the body in adequate amounts. 25The combination of probiotics and prebiotics (nondigestible fibers that aid bacteria growth) are synergistic and are referred to as a synbiotic. 26Several clinical trials administering probiotics or synbiotics to adults investigated their effects on anthropometric indices and body composition with inconsistently positive results.

| METHODS
The Preferred Reporting Items for Systematic Review and Metaanalysis (PRISMA) checklist was followed in the completion of this systematic review and meta-analysis. 50,51

| Data sources and searches
We did a comprehensive literature search across online databases (PubMed/Medline, Ovid/Medline, Scopus, ISI Web of Science, and Cochrane library) in order to find interrelated studies on probiotics and/or synbiotics supplementation in adults.We also did supplementary search with investigating all the citations related to the included studies and running search across the databases from June 2022 to April 2023.The full search strategy and the search terms used are described in Table S1.There was no applied restriction to publication date or original printed language over the search process.Bibliographies of the relevant studies or systematic reviews identified through the search strategy were screened for additional studies.If the required data for meta-analysis were not reported in the manuscript, corresponding author was contacted to provide data.

| Study selection and eligibility criteria
All citations were included in the EndNote screening software, and subsequently, duplicates were excluded from further evaluation in the present study.Two independent researchers (S.S. and K.N.) assessed the title and abstract of all articles found in the initial search.Any disagreement related to the eligibility of the RCTs was resolved by discussion with a third reviewer (O.A.).The Population, Intervention, Comparison, Outcomes, and Study (PICOS) design framework was used to determine the eligibility of articles, as outlined in Table S2.Exclusion criteria were determined as follows: (1) studies were performed on children, pregnant women, or animals; (2) investigations with the combination of probiotics or synbiotics with other supplements as compared with controls; (3) studies with lack of appropriate control groups; (4) investigations that had insufficient data regarding the studied endpoints in both intervention and control groups.Additionally, unpublished studies, reviews, gray literature, conference abstracts, letters to editor, case-control studies, and case reports were not included.

| Quality assessment
The quality of studies was assessed by two independent researchers (S.S. and K.N.) using the Cochrane Risk of Bias Tool for clinical trials. 52The quality assessment consists of seven criteria, including (1) random sequence generation, (2) allocation concealment, (3) selective outcome reporting, (4) blinding of participants and personnel, (5) detection bias (blinding of evaluators), (6) incomplete outcome data, and (7) other probable sources of biases.These domains were classified as low or high risk for bias or unclear.The overall risk of bias of individual studies was regarded as low (low risk for bias for all items), moderate (unclear risk of bias for ≥1 key domains), or high (high risk of bias for ≥1 key domains) (Table S3).

| Data synthesis and meta-analysis
Weighted mean differences (WMDs) and SDs of anthropometric measurements (body weight, BMI, WC, and WHR) and body composition indicators (FM, %BF, FFM, and LBM) from both intervention and control groups were extracted and applied to get the overall effect sizes, determining by the random-effects model approach. 53The net changes were estimated with the following formula: (mean at the end of follow up in the treatment group-mean at the baseline in the treatment group) and (mean at the end of follow up in the control group-mean at the baseline in the control group).SDs of the mean differences between groups were calculated using the following formula: SD = square root ([SD pre-intervention) 2 + (SD post-intervention) 2 À (2R Â SD preintervention Â SD post-intervention]). 54 In addition, by using the relevant formulas, we converted standard errors (SEs), 95% confidence intervals (CIs), and interquartile ranges (IQRs) to SDs. 55 Next, a random-effects model, which incorporates between-study variations, was utilized to determine the overall body composition effect size.Heterogeneity was determined by the I 2 statistic and Cochrane's Q-test.The Q-test's I 2 value >50% or p < 0.05 was characterized as significant between-study heterogeneity. 56,57Subgroup analyses were carried out based on the predefined criteria, including duration of follow-up (≥12/<12 weeks), type of intervention (probiotic/synbiotic), gender of participants (both/female/male), participants' baseline BMI level (normal/ overweight/obese), and intervention form (food/supplement) to find probable sources of heterogeneity.Due to the inconsistency between dosages of intervention, non-linear dose-response and meta-regression analyses were executed to determine the potential non-linear and linear effects of probiotics or synbiotics duration (week) on each outcome.
Furthermore, sensitivity analysis was done to determine the individual study effect on the overall estimation of effect. 58The possibility of publication bias was evaluated by the formal Egger's test.The meta-analysis was carried out using Stata (Version 14.0, Stata Corp, College Station, TX).The p-value <0.05 was considered as statistical significance.

| Data extraction
Two researchers independently (S.S. and K.N.) extracted the following data from eligible full-text articles: the name of the first author, publication year, study design, country of origin, overall sample size coupled with separated one in intervention and control groups, participants' age, comorbidities, and BMI, the type, dose, duration, and form of the intervention, and mean or median with standard deviations, SEs, 95% CIs, or IQRs of anthropometric and body composition changes for both intervention and control groups at pre-and post-intervention.In case of reporting each outcome in different units, we converted them to the most frequently used unit.

| Certainty assessment
The overall certainty of evidence across studies was evaluated according to grading of recommendations assessment, development, and evaluation (GRADE) guidelines working group (gradeworkinggroup.org). 59ch outcome was graded in accordance with the risk of bias, inconsistency (heterogeneity), indirectness, and imprecision, rating high, moderate, low, or very low. 59| RESULTS

| Study selection
The PRISMA flow diagram of the literature search and study selection for the present systematic review and meta-analysis is demonstrated in Figure S1.The primary search resulted in 1064 records.Of these, 390 duplicates were excluded and 674 studies remained.We also reached to 800 records from supplementary searches.After title and abstract screening of 1474 papers, 621 RCTs were recognized as the eligible studies for full-text review.Next, we removed 421 studies due to the following reasons: lack of required data as indicated in the inclusion/exclusion criteria, not having an appropriate control group, and co-supplementation of probiotics and/or synbiotics with other active ingredients.However, there were some studies that were removed due to having the same sample of participants  and hence were treated as a single study. Finaly, 200 unique RCTs with 220 effect sizes were included for quantitative and qualitative analysis.

| Study characteristics
The general characteristics of the included studies are outlined in Table S4.[280] In total, 12,603 participants (6507 case subjects and 6096 control subjects) with ages ranged from 18 to 82 years and baseline BMI ranged between 19.1 and 38.76 kg/m 2 . Twenty-ix studies investigated the effects of probiotics and/or synbiotics in healthy subjects, 111,118,141,144,146,148,155,161,171,180,191,192,195,200,201,207,219,232,235,237,240,241,247,260,265,272 and the remaining studies enrolled unhealthy participants. All theudies were performed in both genders, whereas seven studies conducted on males 192,224,229,239,260,265,272 and 30 studies were on females.12,27,85,103,105,120,129,133,158,161,162,188,191,197,203,206,210,216,218,221,222,227,235,237,248,254,256,259,262,264 Follow-up length of the studies varied from 2 to 56 weeks. Among icluded studies, 50 RCTs administered synbiotics 27,30,77,84,89,91,93,94,97,100,[102][103][104]107,108,119,120,126,149,153,162,164,166,169,170,181,184,192,194,199,206,209,210,212,213,216,222,226,227,233,238,242,243,251,260,265,268,270,273,274 and the rest of the studies were investigated the effectiveness of probiotics.S5).
Forty-three effect sizes reported WHR as an outcome measure.
Overall, results from the random-effects model demonstrated that probiotics and/or synbiotics administration resulted in a significant reduction in WHR (WMD: À0.01; 95% CI: À0.01, À0.00; p < 0.001; P heterogeneity < 0.001, I 2 = 82.0%)(Figure S2D).On subgroup analyses, we observed that probiotics and/or synbiotics consumption significantly reduced WHR values in RCTs enrolled both genders and individuals with metabolic disorders or overweight and obese subjects.
Additionally, reduced WHR values were significant in studies with normal BMI or overweight subjects.Notably, the significant effect of probiotics and/or synbiotics intake on WHR was irrespective of follow-up duration, form and type of intervention (Table S5).

| Effects of probiotics and/or synbiotics supplementation on body composition indicators
Pooled data from 50 effect sizes indicated that FM values were reduced significantly in those receiving probiotics and/or synbiotics compared to controls (WMD: À0.92 kg; 95% CI: À1.05, À0.79; p < 0.001; P heterogeneity = 0.986, I 2 = 0.0%) (Figure S2E).Moreover, the effect of probiotics and/or synbiotics supplementation on %BF was evaluated in 73 clinical trials and the pooled mean difference revealed a reduction in %BF (WMD: À0.68%; 95% CI: À0.94, À0.42; p < 0.001; P heterogeneity < 0.001, I 2 = 63.5%)(Figure S2F).In subgroup analysis, the effect of probiotics and/or synbiotics consumption on FM and %BF was significant in groups who were supplemented with either food or supplement form of probiotics, studies with healthy and overweight or obese subjects, when the duration of intervention was 12 weeks or longer, as well as in subgroups with BMI > 25 kg/m 2 and both genders (Table S5).

| Sensitivity analysis
Upon removing individual study from the meta-analysis to assess the possible influence of each individual study on the body weight, BMI, WC, WHR, FM, %BF, FFM, and LBM, the overall results did not significantly change.

| Meta-regression analysis
Meta-regression using the random-effects model was applied to explore the potential association between a decrease in anthropometric and body composition indicators and duration of intervention (weeks).Meta-regression analysis showed a linear relationship between duration changes in body weight (r = À1.04,P linearity = 0.003), BMI (r = À0.07,P linearity = 0.001), and FM (r = À1.55,P linearity = 0.007) (Figure S5).

| Grading of evidence
The GRADE protocol was used for the assessment of the certainty of the evidence (Table S6).Because most studies evaluating body weight, BMI, WC, WHR, %BF, FFM, and LBM had a low to moderate risk of bias with low heterogeneity and narrow CIs, the quality of evidence for FM was high.Furthermore, the quality of evidence related to FFM and LBM downgraded to moderate due to serious imprecision (wide CIs; p = 0.685 and p = 0.914, respectively).The quality of evidence for body weight due to publication bias ( p = 0.026), WC, and % BF due to serious inconsistency (I 2 = 43.9% and I 2 = 63.5%,respectively) was also downgraded to be considered as low.Finally, owing to serious inconsistency (I 2 = 58.7%)and evidence of publication bias ( p = 0.004), the GRADE assessment for BMI was considered as low, and also due to very serious inconsistency (I 2 = 82%), the quality of evidence for WHR was low.Regarding sex-related differences, we observed that supplementation with probiotics and/or synbiotics resulted in a significant reduction in anthropometric measures among females rather than males.Furthermore, probiotic or synbiotic in any forms either food or supplement resulted in significant changes on anthropometric and body composition measurements.However, body composition indices were influenced by intervention type; compared to controls, FM and %BF values were only reduced after probiotic consumption.
To our knowledge, this systematic review and meta-analysis is the first to investigate the association between GM alterations through probiotics or synbiotics consumption and anthropometric and body composition changes in the adult population.As obesity is associated with cardiometabolic complications and a range of chronic disorders, including hypertension, diabetes, heart attacks, metabolic syndrome, and renal failures, body composition assessment and anthropometric index management are essential components of maintaining health. 281,282Recent evidence has indicated that gut dysbiosis (change in microbial community in favor of pathogenic microbes) may be a factor leading to obesity. 283,284The relationship between GM composition and obesity is bidirectional; microbiota affects obesity and the host's health conditions including obesity influence on the composition of microbiota. 285The fermentation process in the gut microbes releases bioactive compounds that trigger responses in the intestinal mucosa and impact metabolic processes in the liver and adipose tissue, which in turn helps in regulating lipid and glucose homeostasis. 286The GM also influences the endocrine function and intestinal barrier, which affects the absorption and transportation of nutrients.Therefore, GM regulation can be an efficient strategy in management of obesity. 286The administration of probiotics or synbiotics has been as a potential treatment for obesity due to the ability to alter microbiota composition. 287[290][291][292][293] There is a significant disparity in terms of GLP-1 response to intraduodenal glucose infusion between women and men.Healthy young women showed a considerably greater GLP-1 levels after glucose infusion compared to men. 294It can be hypothesized that women may achieve a quicker feeling of satiety than men following probiotics and/or synbiotics consumption.The composition of the GM varies between health and disease conditions. 295A previous meta-analysis examined the prevalence of small intestinal bacterial overgrowth (SIBO), a type of intestinal microbial dysbiosis, in obese and non-obese populations.The results indicated that the risk of SIBO was twice as high in obese individuals as non-obese individuals with no statistical difference. 296We also observed that probiotics and/or synbiotics intake improved anthropometric indices among individuals with obesity, metabolic disorders, and healthy subjects.It could partly be due to higher microbial dysbiosis among these populations.In addition, study duration appears to be a crucial factor in determining the effect of probiotic on body adiposity.Studies with a duration less than 12 weeks showed that only 18% reduction in BMI and 22% reduction in WC, while none of them observed a substantial decrease in body weight and total body mass. 297These findings are in agreement with our results, in which we reported that optimum intervention duration to achieve positive effects on BW, BMI, and %BF was approximately 40, 40, and 15 weeks, respectively.
There have been many studies that suggested anti-obesity effects of probiotics including two previous preclinical studies, which demonstrated that probiotics administration can mitigate obesity through GM modulation. 285,298Furthermore, in contrast to previous meta-analyses, 26,[32][33][34][35][36][37][38][39] the current study revealed a significant decrease in anthropometric measurements due to the supplementation of probiotics or synbiotics, in line with other previous meta-analyses conducted in adults, 36,40 overweight and obese individuals, 23,[41][42][43][44] patients with cardiometabolic disease 45 including patients with T2DM, [46][47][48] patients with non-alcoholic fatty liver disease, and individuals with PCOS. 49Inconsistent results between the present study and previous meta-analyses may be due to the various target populations and the differences in the number of the included studies.John et al. reported the positive effects of supplementation with probiotic on body weight, BMI, and FM; however, they showed no effects of synbiotics on these outcomes, 36 which is in disagreement with the results of the present study.However, the present meta-analysis included 200 RCTs, which assessed a much bigger sample size than 21 RCTs in the John et al. study.In addition, this study is the first systematic review and meta-analysis exploring the effectiveness of probiotics and synbiotics on FFM and LBM, demonstrating non-significant changes in these endpoints.Out of all the RCTs included in this study, only one showed a significant decrease in LBM following the probiotics and synbiotics supplementation. 28wever, further research is needed to confirm these findings.
The present meta-analysis has several strengths.It is the first systematic review and meta-analysis of RCTs that simultaneously evaluated the effectiveness of probiotics and synbiotics on changes in anthropometric measurements and body composition among healthy and unhealthy adults.Further, we reviewed various databases extensively to make this the most comprehensive study to date, minimize bias, and assess ethnic populations.To highlight the differences between trials, sensitivity analyses were performed, indicating nonsignificant changes after excluding individual study for any outcome.
We also performed analyses separately for probiotics and synbiotics, coupled with a combined analysis to further our findings on combination treatment.Additionally, previous meta-analyses have been expanded in our study by conducting a GRADE assessment, subgroup analyses, dose-response, and meta-regression analyses.However, both the present study and the included studies have limitations.
Some RCTs provided insufficient information regarding the risk of biased judgment.Moreover, there were disparities between studies regarding dietary intake, age, intake of antibiotics, infections, and epigenetics, which influences GM composition 295,299 and consequently might influence the findings of this study.The following are some of our study's limitations: firstly, despite the fact that RCTs used a range of probiotic or synbiotic bacteria strains and dosages, we were unable to conduct subgroup analysis based on these factors.Secondly, our findings might have been impacted by the heterogeneity of the included trials in terms of the populations studied and the supplementation types, doses, and durations.Thirdly, we excluded non-English submissions and those that were not peer-reviewed.Finally, the present study lacks a predefined review protocol, and we did not register the review before we began our search.

| CONCLUSION
Our results showed that a supplementation of probiotics and synbiotics has beneficial effects on anthropometric indices and body composition in adults.However, further large-scale and well-designed trials are warranted to confirm these findings and to provide a more guidance on probiotic strains.In addition, the limitation of the present study highlighted the need for trials controlling for dietary intake as diet can independently influence the gut flora.

3. 7 |
Non-linear dose-responses between duration of probiotics and/or synbiotics supplementation and anthropometric and body composition indices Dose-response analysis showed that probiotics and/or synbiotics supplementation changed body weight (r = À0.19,P nonlinearity = 0.001), BMI (r = À0.07,P nonlinearity = 0.001), and %BF (r = À1.05,P nonlinearity = 0.022) significantly based on duration in non-linear fashion.Importantly, we found that the optimum duration in which the most reduction in body weight and BMI was seen was 40 weeks, while this time for %BF was roughly 15 weeks (Figure S4).

4 |
DISCUSSIONThe present systematic review and meta-analysis explored the effectiveness of probiotics and/or synbiotics consumption on anthropometric measurements and body composition in adults.Cumulative results from the pooled analysis of 200 eligible RCTs indicated that supplementation of probiotics and/or synbiotics decreased body weight, BMI, WC, WHR, FM, and %BF compared to a control group.However, administration of probiotics and/or synbiotics did not affect FFM and LBM compared to controls.In the subgroup analyses based on study duration, we demonstrated that although probiotics and/or synbiotics supplementation had more favorable effects on FM and % BF when interventions were 12 weeks or longer, the changes on anthropometric indices were irrespective of study duration.Notably, probiotics or synbiotics resulted in a significant reduction in anthropometric measurements among participants who were healthy, with overweight, obesity, or metabolic disorders compared to controls.