Propolis Supplementation and Metabolic Syndrome Components in Adults at Risk: A Systematic Review and Meta‐Analysis of Randomized Controlled Trials

ABSTRACT

Background and Aims

Propolis is a natural resinous substance produced by bees, recognized for its antioxidant and anti‐inflammatory properties. Previous clinical trials have reported inconsistent results regarding its effects on various components of metabolic syndrome (MetS). To address this, we conducted a comprehensive meta‐analysis to evaluate the impact of propolis on components of MetS in adults at risk.

Methods

A systematic search was conducted in PubMed, Web of Science, Cochrane, Scopus, ISI Web of Science, and Google Scholar up to July 2025. This search aimed to identify all randomized controlled trials (RCTs) that examined the effects of propolis supplementation on various components of MetS in propolis on components of MetS in adults at risk. Relevant studies were included in this systematic review and meta‐analysis based on keywords related to propolis and MetS. The weighted mean difference (WMD) was calculated using a random‐effects model.

Results

A total of 20 RCTs involving 1091 participants were included in this meta‐analysis. The results indicated that propolis supplementation significantly reduced fasting blood sugar (FBS) (WMD: −7.93 mg/dL, 95% CI: −12.37 to −3.50, p < 0.001) and triglyceride (TG) levels (WMD: −12.32 mg/dL, 95% CI: −21.08 to −3.56, p = 0.006) when compared to the control group. However, the analysis revealed that propolis did not have a significant effect on waist circumference, high‐density lipoprotein cholesterol levels, or on either systolic or diastolic blood pressure.

Conclusion

Supplementation with propolis significantly lowered FBS and TG levels in individuals with MetS risk factors. However, there were no significant effects showed on other components of MetS. These findings suggest potential benefits for glycemic and TG control, but more high‐quality clinical trials with extended follow‐up periods are needed to confirm and further investigate these results.

1. Introduction

Metabolic syndrome (MetS), also known as syndrome X, is a widespread public health concern characterized by a combination of risk factors including (1) abdominal obesity (defined as an increased waist circumference [WC] based on population or country‐specific cutoffs), (2) low high‐density lipoprotein cholesterol (HDL‐C) levels (< 40 mg/dL for men and < 50 mg/dL for women), (3) high triglyceride (TG) levels (≥ 150 mg/dL), (4) abnormal fasting blood sugar (FBS) levels (≥ 100 mg/dL), and (5) high blood pressure (BP) (≥ 130/85 mmHg) [1, 2, 3]. These factors collectively increase the risk of developing noncommunicable diseases such as cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), nonalcoholic fatty liver disease (NAFLD), chronic kidney disease (CKD), and overall mortality [4, 5]. Globally, the prevalence of MetS varies widely due to differences in lifestyle, genetic predispositions, and socioeconomic conditions, with estimates ranging between 12.5% and over 30% [6, 7].

Studies have shown that biological mechanisms such as oxidative stress, insulin resistance, neurohormonal imbalances, and chronic inflammation contribute to MetS pathogenesis and its complications [2, 8]. The parallel rise in obesity rates highlights the urgent need for effective strategies targeting MetS [9, 10]. Current management primarily emphasizes lifestyle interventions, including healthy diet and regular physical activity, complemented by pharmacological treatments like statins, antihypertensives, and antidiabetic agents [11]. Nevertheless, challenges such as poor adherence to lifestyle changes and medication side effects have sparked growing interest in complementary and alternative therapies, particularly the use of natural compounds [11, 12].

Propolis, a resinous mixture produced by bees from plant exudates, has been used traditionally for its antimicrobial, anti‐inflammatory, antioxidant, and immune‐modulating properties [13, 14]. Its chemical composition is highly variable, depending on factors such as plant source, season, bee species, and extraction methods, but typically includes flavonoids, phenolic compounds, terpenes, and various bioactive substances. This complex composition underlies propolis's diverse biological effects [15, 16, 17]. In addition to Apis mellifera, stingless bees (Meliponini) also produce propolis, which has distinct chemical compositions. The species of bees significantly influences the phytochemical profile and biological properties of propolis [18, 19].

Experimental and clinical studies suggest that propolis may improve lipid and glucose metabolism, reduce BP, and mitigate oxidative stress and inflammation, key elements in MetS pathology [20, 21, 22]. These attributes position propolis as a promising natural agent for supporting metabolic and cardiovascular health [23].

Findings from randomized controlled trials (RCTs) investigating the effects of propolis supplementation on the components of MetS in adults have reported inconsistent findings [24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]. While some studies have revealed improvements in lipid profiles, glycemic control, BP, and anthropometric measurements after propolis supplementation [25, 27, 32, 34, 35, 41, 43], other studies have not shown significant changes [24, 26, 28, 29, 30, 31, 33, 36, 37, 38, 39, 40, 42]. Consequently, this systematic review and meta‐analysis aimed to assess the specific effects of propolis supplementation on components of MetS in adults at risk.

2. Methods

The present research was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) 2020 guidelines (Supporting Information S2: Table 1) [44], and follows the recommendations outlined in the “Guidelines for Reporting of Statistics for Clinical Research in Urology” [45].

2.1. Search Strategy

A comprehensive search was conducted using several electronic databases, including PubMed, Web of Science, Cochrane, Scopus, ISI Web of Science, and Google Scholar. The search was conducted on July 2025 and utilized both MeSH (Medical Subject Headings) and non‐MeSH keywords. The search terms included: (“Propolis” OR “Bee glue” OR “Bee bread”) AND (“Insulin resistance syndrome” OR “Syndrome X” OR “Cardio‐metabolic syndrome” OR “Metabolic syndrome” OR “Ravens syndrome” OR “Metabolic syndrome X” OR “Glucose” OR “Fasting blood sugar” OR “Fasting blood glucose” OR “FBS” OR “FBG” OR “Triglyceride” OR “Triacylglycerol” OR “TG” OR “TAG” OR “Hypertriglyceridemia” OR “Blood pressure” OR “BP” OR “Hypertension” OR “Abdominal obesity” OR “Waist circumference” OR “WC” OR “High density lipoprotein” OR “Dyslipidemia” OR “HDL”). No restrictions were applied regarding language or publication status to ensure a thorough retrieval of relevant studies. Additionally, the reference lists of included studies and pertinent reviews were manually searched for further publications.

2.2. Study Selection

After completing the literature search, all retrieved records were imported into EndNote software, and duplicate entries were removed. A two‐stage screening process was then conducted to accurately identify eligible studies. In the first stage, titles and abstracts were screened, followed by a full‐text review of potentially relevant article. According to PICOS (population, intervention, comparison, outcome, and setting), the eligible articles must fulfill the following criteria: (a) Population: adults aged 18 years and older; (b) Intervention: propolis administered for more than 1 week; (c) Comparators: placebo or a comparison group were used; (d) Outcomes: at least one of the following indicators was reported: FBS, HDL‐C, TG, WC, systolic BP (SBP), or diastolic BP (DBP); and (e) study design: RCTs with either a parallel or crossover design. Exclusion criteria were: (a) studies using propolis in combination with other herbal products or active compounds; (b) studies involving pregnant or lactating women, patients with gestational diabetes, or healthy individuals; and (c) studies lacking sufficient or extractable data. Study selection was performed independently by two investigators (S. O. R. and M. K.). Any discrepancies were resolved through discussion and consensus, or by consulting a third reviewer (M. N.) when necessary.

2.3. Data Extraction

Eligible RCTs were independently assessed by two authors M. H. and S. M.), and data were extracted using a predesigned standardized form. The extracted data included the following components: (1) study characteristics (first author's last name, year of publication, location of the study, and sample size); (2) participants' information (gender, mean body mass index [BMI] and mean age); (3) intervention details (duration of treatment, dose, formulation, and type of intervention for both the experimental and comparison groups); and (4) main outcomes. For studies that presented results only in graphical form, we utilized specialized software (GetData Graph Digitizer) to extract numerical data. In instances where essential data were missing, corresponding authors were contacted for clarification. Any disagreements during data extraction were resolved through discussion and consensus between the reviewers.

2.4. Quality Assessment

The methodological quality of the included RCTs was evaluated using the Cochrane Collaboration's Risk of Bias tool [46]. Potential sources of bias were assessed across several domains: sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective outcome reporting, and other potential sources of bias. Two reviewers (S. O. R. and M. K.) independently evaluated each study, categorizing the risk of bias for each domain as “low,” “high,” or “unclear.” Based on these evaluations, the overall quality of the studies was classified as follows: “good” if four or more domains were rated as low risk, “fair” if exactly three domains were rated as low risk, and “weak” if fewer than three domains were rated as low risk. Any disagreements between the two reviewers were resolved through discussion, and, when necessary, a third reviewer (M. N.) was consulted to reach a consensus.

2.5. Statistical Analysis

Before calculating effect sizes, all outcome variables were converted to uniform units to ensure consistency across studies. For each outcome, the mean change and its standard deviation (SD) were extracted for both intervention and control groups. If net changes were not directly reported, they were computed by subtracting baseline values from postintervention values within each group and then calculating the difference between the two groups. When SDs of mean changes were not available, they were estimated using the following formula: (measure at the end of follow‐up in the treatment group − measure at baseline in the treatment group) − (measure at the end of follow‐up in the control group − measure at baseline in the control group). Also, the SD of mean change was calculated as follows: SD = square root [(SD pretreatment)² + (SD posttreatment)² − (2 R × SD pretreatment × SD posttreatment)], assuming a correlation coefficient of 0.5. In studies reporting only standard error (SE), SD was derived using the formula: SD = SE × √n, where n is the sample size of each group. The weighted mean difference (WMD) was calculated using a random‐effects model. Statistical heterogeneity was assessed using the I ² statistic, with values ≥ 50% indicating substantial heterogeneity [47]. Subgroup analyses were conducted to explore sources of heterogeneity based on intervention duration (≥ 12 weeks or > 12 weeks), participants mean age (< 55 years or ≥ 55 years), study location (Iran or other countries), participants' health status (T2DM or other conditions), and propolis dosage (< 900 mg/day or ≥ 900 mg/day). Sensitivity analyses were performed by systematically removing each study to assess its influence on the overall effect size. Potential publication bias was examined using funnel plot, Egger's regression test [48], and Begg's rank correlation method [49]. All statistical analyses were performed using STATA version 16.0 (StataCorp, College Station, TX, USA), with a significance level set at p < 0.05. Statistical analyses were conducted following the Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines for transparent and accurate reporting of statistical methods [50].

3. Results

3.1. Identification and Selection of Relevant Studies

A total of 521 publications were identified through a specific search strategy. After removing 115 duplicate records, 406 publications remained. Based on the title and abstract assessment, 380 articles were excluded. This left 26 full‐text studies that were evaluated for eligibility. Of these, 6 articles were excluded for the following reasons: they lacked an appropriate control group (n = 2), administered propolis in combination with other herbal ingredients (n = 2), or were conducted on healthy individuals (n = 2). Consequently, 20 articles [24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43] that met the inclusion criteria were ultimately included in the systematic review and meta‐analysis. The literature screening process is summarized in Figure 1.

Figure 1.

Flow diagram of literature selection process.

3.2. Study Characteristics

The key characteristics of the included studies are summarized in Table 1. These studies were published between 2015 and 2024 and involved a total of 1091 subjects. The research was conducted in several countries, including Iran [24, 25, 26, 30, 31, 32, 33, 35, 36, 39, 40, 41, 43], Japan [28], China [29, 42], Brazil [38], France [37], Mexico [34], and Egypt [27], with participants' ages ranging from 32 to 69 years. The mean BMI of the participants was ~30 kg/m². Participants received varying doses of propolis, ranging from 226 to 1500 mg/day, over periods of 8–48 weeks. The participant groups consisted of patients with T2DM [25, 27, 28, 29, 32, 34, 36, 41, 42, 43], individuals with MetS [30, 35], patients with rheumatoid arthritis [31], patients with CKD [26, 38], women with polycystic ovary syndrome [24], patients with NAFLD [33, 39, 40], and obese individuals [37]. Among the studies reviewed, 17 reported FBS levels [24, 25, 26, 27, 28, 29, 30, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43], 7 reported BP [24, 26, 30, 31, 34, 35, 38], and another 8 assessed WC [24, 30, 33, 34, 35, 36, 37, 40]. Furthermore, HDL‐C levels were reported in 14 studies [24, 25, 28, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41], while TG levels were available in 12 studies [24, 25, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41].

Table 1.

Characteristics of included studies.

Reference	Country	Trial sample size	Gender	Mean age of participants (year)	Mean BMI of participants (kg/m2)	Duration (week)	Participants	Type of intervention (dose)	Propolis composition	Type of control	Outcomes
Anvarifard et al. [26]	Iran	35	Both	59	29	12	Chronic kidney disease	Propolis (250 mg)	36 mg phenolic compounds	Placebo	FBS, SBP, DBP
Abbasi et al. [24]	Iran	57	Women	32	27	12	Polycystic ovary syndrome	Propolis (500 mg)	280 mg of the polyphenolic compound	Placebo	FBS, SBP, DBP, WC, TG, HDL‐C
Maddahi et al. [31]	Iran	45	Women	47	27	12	Rheumatoid arthritis	Propolis (1000 mg)	NR	Placebo	SBP, DBP, TG, HDL‐C
Sajjadi et al. [35]	Iran	62	Both	54	33	12	Metabolic syndrome	Propolis (500 mg)	90 mg gallic acid equivalent and 67 mg flavonoids	Placebo	FBS, SBP, DBP, WC, TG, HDL‐C
Silveira et al. [38]	Brazil	32	Both	61	29	48	Chronic kidney disease	Propolis (500 mg)	77.96 mg of total phenolic compounds	Placebo	SBP, DBP
Gholami et al. [30]	Iran	84	Both	52	29	12	Metabolic syndrome	MIND diet + propolis (900 mg)	NR	MIND diet + placebo	FBS, SBP, DBP, WC, TG, HDL‐C
Afsharpour et al. [25]	Iran	60	NR	50	26	8	Type 2 diabetes	Propolis (1500 mg)	NR	Placebo	FBS
Samadi et al. [36]	Iran	66	Both	54	28	12	Type 2 diabetes	Propolis (900 mg)	NR	Placebo	FBS, TG, HDL‐C
Nikbaf‐Shandiz et al. [33]	Iran	44	Both	40	33	8	Nonalcoholic fatty liver	Calorie‐restricted diet + propolis (1500 mg)	NR	Calorie‐restricted diet + placebo	FBS, WC, TG, HDL‐C
Soleimani et al. [39]	Iran	51	Both	42	29	12	Nonalcoholic fatty liver	Propolis (500 mg)	90 mg gallic acid equivalent and 67 mg flavonoids	Placebo	FBS, TG, HDL‐C
Moayedi et al. [32] A	Iran	30	Women	53	NR	8	Type 2 diabetes and dyslipidemia	Propolis (500 mg)	NR	Placebo	HDL‐C
Moayedi et al. [32] B	Iran	30	Women	53	NR	8	Type 2 diabetes and dyslipidemia	Propolis (500 mg) + exercise	NR	Exercise	HDL‐C
Zakerkish et al. [41]	Iran	94	Both	55	30	12	Type 2 diabetes	Propolis (1000 mg)	Total flavones and flavonols: 8.4%, total flavanones and dihydroflavonols: 4.6% and total phenolic compounds: 28%	Placebo	FBS, TG, HDL‐C
Tutunchi et al. [40]	Iran	52	Both	36	33	8	Obesity + Nonalcoholic fatty liver	Propolis (1500 mg) + dietary recommendation	NR	Placebo + dietary recommendation	FBS, WC, TG, HDL‐C
Gao et al. [29]	China	61	Both	59	26	18	Type 2 diabetes	Propolis (900 mg)	NR	Control	FBS
El‐Sharkawy et al. [27]	Egypt	50	Both	50	27	24	Type 2 diabetes + periodontitis	Propolis (400 mg) + scaling and root planing	NR	Placebo + scaling and root planing	FBS
Sani et al. [37]	France	9	NR	49	31	12	Insulin‐resistant with Obesity	Propolis (1500–2000 mg)	30% total polyphenols	Placebo	FBS, WC, TG, HDL‐C
Fukuda et al. [28]	Japan	80	Both	69	25	8	Type 2 diabetes	Propolis (226 mg)	NR	Placebo	FBS, HDL‐C
Zhao et al. [42]	China	65	Both	60	26	18	Type 2 diabetes	Propolis (900 mg)	NR	Control	FBS
Ochoa‐Morales et al. [34]	Mexico	24	Both	47	30	12	Type 2 diabetes	Propolis (600 mg)	NR	Placebo	FBS, SBP, DBP, WC, TG, HDL‐C
Yousefi et al. [43]	Iran	60	Both	50	27	8	Type 2 diabetes	Propolis (1500 mg)	NR	Placebo	FBS

Abbreviations: BMI, body mass index; DBP, diastolic blood pressure; FBS, fasting blood sugar; HDL‐C, high‐density lipoprotein cholesterol; MIND diet, The Mediterranean‐DASH Intervention for Neurodegenerative Delay diet; NR, not reported; SBP, systolic blood pressure; TG, triglyceride; WC, waist circumference.

3.3. Risk of Bias Assessment

Based on the Cochrane risk of bias checklist, all included studies were rated as high quality, except for three studies which were assessed as having weak [29] and fair [30, 42] quality, respectively. The details of quality assessment in individual studies are provided in Table 2.

Table 2.

Quality assessment of included studies based on Cochrane guidelines.

Reference	Random sequence generation	Allocation concealment	Blinding of participants, personnel	Blinding of outcome assessment	Incomplete outcome data	Selective outcome reporting	Other sources of bias	Overall quality
Anvarifard et al. [26]	L	L	L	L	L	L	U	Good
Abbasi et al. [24]	L	L	L	L	L	U	L	Good
Maddahi et al. [31]	L	L	L	U	L	U	U	Good
Sajjadi et al. [35]	L	L	L	L	L	L	U	Good
Silveira et al. [38]	L	L	L	U	L	L	H	Good
Gholami et al. [30]	L	L	H	H	L	U	U	Fair
Afsharpour et al. [25]	L	U	L	U	L	L	U	Good
Samadi et al. [36]	L	L	L	U	L	L	U	Good
Nikbaf‐Shandiz et al. [33]	L	L	L	U	L	L	U	Good
Soleimani et al. [39]	L	L	L	L	L	L	L	Good
Moayedi et al. [32]	L	L	L	U	L	L	U	Good
Zakerkish et al. [41]	L	L	L	U	L	L	L	Good
Tutunchi et al. [40]	L	L	L	L	L	L	L	Good
Gao et al. [29]	H	H	H	U	L	L	U	Weak
El‐Sharkawy et al. [27]	L	L	L	U	L	L	L	Good
Sani et al. [37]	L	U	L	U	L	L	U	Good
Fukuda et al. [28]	L	U	L	U	L	L	U	Good
Zhao et al. [42]	L	U	U	U	L	L	U	Fair
Ochoa‐Morales et al. [34]	L	L	L	U	L	L	L	Good
Yousefi et al. [43]	L	L	L	L	L	L	L	Good

Abbreviations: H, high risk of bias; L, low risk of bias; U, unclear risk of bias.

3.4. Meta‐Analysis Results

3.4.1. Effect of Propolis Supplementation on Fasting Blood Sugar

A total of 17 clinical trials [24, 25, 26, 27, 28, 29, 30, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43] evaluated the impact of propolis supplementation on FBS levels. The pooled analysis demonstrated that propolis supplementation, when compared to the control group, resulted in a statistically significant reduction in FBS levels (WMD: −7.93 mg/dL, 95% CI: −12.37 to −3.50, p < 0.001). However, there was a significant heterogeneity (I ² = 83.0%, p < 0.001) between studies (Figure 2). Subgroup analyses, which considered participants' health status, country of study, propolis dosage, duration of intervention, and mean age, showed that the significant effect was consistent primarily in studies conducted in Iran, among participants with a mean age under 55 years, among patients with T2DM, and in trials that lasted 12 weeks or more. Additionally, the pooled averages indicated that FBS levels decreased in both dosage subgroups. The pooled estimates regarding the effect of propolis on FBS across different subgroups are detailed in Table 3.

Figure 2.

Forest plot showing pooled WMDs with 95% CI for the effect of propolis supplementation on fasting blood sugar.

Table 3.

Subgroup analyses to assess the effect of propolis supplementation on components of metabolic syndrome.

Subgrouped by	No. of arms	Effect sizea	95% CI	I 2 (%)	p for heterogeneity	p for effect size
FBS
Health status
Type 2 diabetes mellitus	9	−14.06	−21.02 to −7.09	72.2	< 0.001	< 0.001
Other conditions	8	−2.40	−6.38 to 1.59	72.1	0.23	0.001
Age
< 55 years	12	−9.71	−15.12 to −4.31	87.4	< 0.001	< 0.001
≥ 55 years	5	−3.09	−9.09 to 2.90	25.3	0.25	0.31
Country
Iran	11	−7.60	−12.44 to −2.77	82.4	< 0.001	0.002
Other	6	−7.49	−17.32 to 2.33	78.8	< 0.001	0.13
Propolis dosage
< 900 mg/d	11	−7.36	−13.30 to −1.42	83.6	< 0.001	0.01
≥ 900 mg/d	6	−9.25	−17.02 to −1.48	84.3	< 0.001	0.02
Duration
≤ 12 weeks	14	−7.52	−11.89 to −3.15	79.4	< 0.001	0.001
> 12 weeks	3	−6.79	−23.40 to 9.81	83.6	< 0.001	0.42
HDL‐C
Health status
Type 2 diabetes mellitus	7	2.24	−0.77 to 5.24	92.1	< 0.001	0.14
Other conditions	8	0.58	−1.48 to 2.56	62.2	0.01	0.57
Age
< 55 years	13	1.14	−1.05 to 3.34	88.9	< 0.001	0.30
≥ 55 years	2	2.27	−1.88 to 6.43	64.4	0.09	0.28
Country
Iran	12	2.14	0.16 to 4.12	87.4	< 0.001	0.03
Other	3	−3.24	−9.25 to 2.78	75.4	0.001	0.29
Propolis dosage
< 900 mg/d	9	1.20	−1.39 to 3.79	90.5	< 0.001	0.36
≥ 900 mg/d	6	1.42	−1.75 to 4.58	78.0	< 0.001	0.38
TG
Health status
Type 2 diabetes mellitus	4	−20.56	−40.69 to −0.43	45.5	0.13	0.04
Other conditions	8	−9.17	−14.00 to −4.33	0.3	0.42	< 0.001
Country
Iran	10	−14.37	−24.83 to −3.91	37.6	0.10	0.007
Other	2	−1.76	−22.68 to 19.15	0.0	0.74	0.86
Propolis dosage
< 900 mg/d	6	−17.40	−32.66 to −2.14	6.5	0.37	0.02
≥ 900 mg/d	6	−10.8	−21.83 to 1.67	44.1	0.11	0.09
WC
Health status
Type 2 diabetes mellitus	2	0.05	−2.05 to 2.16	0.0	0.43	0.96
Other conditions	6	−0.89	−2.20 to 0.43	33.6	0.18	0.18
Country
Iran	6	−0.95	−1.98 to 0.09	15.3	0.31	0.07
Other	2	1.74	−1.57 to 5.05	0.0	0.44	0.30
Propolis dosage
< 900 mg/d	5	−0.66	−2.13 to 0.81	37.9	0.16	0.37
≥ 900 mg/d	3	−0.71	−2.55 to 1.12	14.6	0.31	0.44
SBP
Country
Iran	5	−2.26	−4.88 to 0.36	0.0	0.67	0.09
Other	2	0.30	−3.59 to 4.19	0.0	0.57	0.87
Age
< 55 years	5	−0.94	−3.25 to 1.36	0.0	0.73	0.42
≥ 55 years	2	−5.55	−12.05 to 0.95	0.0	0.79	0.09
DBP
Country
Iran	5	0.11	−1.59 to 1.80	0.0	0.99	0.90
Other	2	0.35	−2.91 to 3.62	0.0	0.34	0.83
Age
< 55 years	5	−0.08	−1.65 to 1.49	0.0	0.99	0.92
≥ 55 years	2	2.82	−2.44 to 8.08	0.0	0.93	0.29

Abbreviations: DBP, diastolic blood pressure; FBS, fasting blood sugar; HDL‐C, high‐density lipoprotein cholesterol; SBP, systolic blood pressure; TG, triglyceride; WC, waist circumference.

^a Calculated by random‐effects model.

3.4.2. Effect of Propolis Supplementation on High‐Density Lipoprotein Cholesterol

The effect of the propolis supplementation on HDL‐C was examined in 14 clinical trials (15 arms) [24, 25, 28, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41]. The meta‐analysis revealed that propolis supplementation had no significant overall effect on HDL‐C concentrations compared to the control group (WMD: 1.29 mg/dL, 95% CI: −0.66 to 3.24, p = 0.19). There was considerable heterogeneity (I ² = 87.4%, p < 0.001) among the studies (Figure 3). Subgroup analysis by country showed that in studies conducted in Iran, propolis supplementation was associated with a significant increase in HDL‐C levels (WMD: 2.14 mg/dL, 95% CI: 0.16–4.12, p = 0.03). However, the results for all other subsets remained nonsignificant (Table 3).

Figure 3.

Forest plot showing pooled WMDs with 95% CI for the effect of propolis supplementation on high‐density lipoprotein cholesterol.

3.4.3. Effect of Propolis Supplementation on Triglyceride

Twelve RCTs [24, 25, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41] evaluated TG levels. Results of the meta‐analysis showed that TG concentration decreased significantly following propolis supplementation (WMD: −12.32 mg/dL, 95% CI: −21.08 to −3.56, p = 0.006). The heterogeneity among the trials included was low (I ² = 27.7%, p = 0.17) (Figure 4). Subgroup analysis revealed that this effect was primarily observed in studies conducted in Iran and in interventions using doses below 900 mg/day. Significant reductions in TG levels were also observed in both subgroups of health conditions (Table 3).

Figure 4.

Forest plot showing pooled WMDs with 95% CI for the effect of propolis supplementation on triglyceride.

3.4.4. Effect of Propolis Supplementation on Waist Circumference

Eight RCTs [24, 30, 33, 34, 35, 36, 37, 40] assessed the effect of propolis on WC. The meta‐analysis found that the reduction in WC (WMD: −0.70 cm, 95% CI: −1.75 to 0.35, p = 0.19) was not statistically significant when compared to the control group. Additionally, there was low heterogeneity (I ² = 20.4%, p = 0.26) between the studies (Figure 5). Subgroup analyses based on health status, dosage, and country showed that the effect remained nonsignificant across all subgroups (Table 3).

Figure 5.

Forest plot showing pooled WMDs with 95% CI for the effect of propolis supplementation on waist circumference.

3.4.5. Effect of Propolis Supplementation on Blood Pressure

Seven RCTs [24, 26, 30, 31, 34, 35, 38] reported the impact of propolis supplementation on BP. The data analysis revealed no significant reduction in SBP (WMD: −1.46 mmHg, 95% CI: −3.63 to 0.72, p = 0.18) or DBP (WMD: 0.16 mmHg, 95% CI: −1.35 to 1.66, p = 0.83) compared to the control group. Furthermore, no evidence of heterogeneity was found among the studies (I ² = 0.0%, p = 0.70; I ² = 0.0%, p = 0.97) for SBP and DBP, respectively (Figure 6). Subgroup analyses based on the country and the mean age also showed nonsignificant results across all subsets (Table 3).

Figure 6.

Forest plot showing pooled WMDs with 95% CI for the effect of propolis supplementation on systolic and diastolic blood pressure.

3.4.6. Sensitivity Analysis and Publication Bias

Sensitivity analyses showed that excluding individual publications did not significantly change the overall results for FBS, WC, TG, SBP, and DBP. However, when the study by Sani et al. [37] was removed, there was a significant increase in HDL‐C levels (WMD: 1.87 mg/dL, 95% CI: 0.02–3.72, p = 0.04). Publication bias was evaluated using funnel plot, Egger's, and Begg's tests. All tests showed no evidence of bias for the FBS (p = 0.29, Egger's test and p = 0.41, Begg's test), WC (p = 0.22, Egger's test and p = 0.13, Begg's test), TG (p = 0.42, Egger's test and p = 0.41, Begg's test), SBP (p = 0.19, Egger's test and p = 0.17, Begg's test), DBP (p = 0.09, Egger's test and p = 0.05, Begg's test), and HDL‐C (p = 0.05, Egger's test and p = 0.08, Begg's test). Additionally, the symmetric distribution of articles observed in the funnel plot indicates no publication bias for all outcomes (Supporting Information S1: Figure 1).

4. Discussion

In the present meta‐analysis of 20 RCTs, propolis supplementation was associated with significant reductions in FBS and TG levels. However, the pooled analysis did not reveal any significant effects on WC, BP, or HDL‐C. Sensitivity analysis indicated that overall estimates for all outcomes, except for HDL‐C, were not influenced by the removal of any study. Furthermore, we found no evidence of publication bias.

Subgroup analyses indicated that the reduction in FBS was significant only among participants with T2DM, in studies conducted in Iran, among individuals under 55 years of age, and in interventions lasting < 12 weeks. Additionally, the reduction in TG was significant only in studies conducted in Iran and in trials that used doses below 900 mg/day. Notably, the analysis also showed a significant increase in HDL‐C in studies conducted in Iran. Present results may indicate differences in both the composition of propolis and the characteristics of the participants. Propolis sourced from Iran often comes from unique local plants, which can change its profile of bioactive compounds such as flavonoids, phenolic acids, and terpenes [51, 52]. These compounds not only possess antioxidant and anti‐inflammatory properties but may also influence lipid metabolism directly [52, 53]. For instance, they could enhance reverse cholesterol transport and reduce the catabolism of HDL‐C [54, 55]. Such effects may be more significant in populations with lower baseline HDL‐C levels or those whose diet and lifestyle make them more responsive to interventions aimed at modifying lipid levels [55]. The stronger metabolic effects observed in younger participants might be linked to better beta‐cell function and a lower oxidative burden [56]. In contrast, individuals with T2DM may benefit more due to greater baseline metabolic issues [14, 25]. Additionally, the observed reduction in TG levels at lower doses might be associated with improved absorption or reduced metabolic saturation of the active compounds.

The findings of the present meta‐analysis are partly consistent with previous reports. Similar to our results, Karimian et al. [14] found that propolis supplementation significantly reduced FBS in patients with T2DM. The subgroup analysis indicated a larger effect of propolis on FBS in studies conducted outside of East Asian countries. Another meta‐analysis also confirmed a glucose‐lowering effect but reported no significant changes in TG or HDL‐C levels [57]. In contrast, Salehi‐Sahlabadi et al. [53] observed significant reductions in TG and increases in HDL‐C, with no effect on anthropometric indices. Consistent with our observations, Vajdi et al. [58] reported no significant impact on WC or BP in adults, while El‐Sehrawy et al. [59] documented a reduction in SBP. These discrepancies may be explained by differences in total sample size, the number and type of trials included in each meta‐analysis, and variations in target populations, all of which can influence the magnitude and statistical significance of pooled effects.

The precise biological mechanisms behind the hypoglycemic effects of propolis have not yet been fully established, but several potential mechanisms have been suggested. Propolis contains bioactive compounds, such as flavonoids and phenolic acids, which can enhance insulin sensitivity, protect pancreatic β‐cells, and lower FBS levels [14, 60]. Mechanistically, propolis improves glucose metabolism through various pathways. It enhances insulin secretion and cellular responsiveness, inhibits carbohydrate digestion by suppressing α‐glycosidase and intestinal sucrase to reduce postprandial glucose spikes, stimulates glucose uptake through GLUT4 translocation by activating PI3K and AMPK in peripheral tissues, and suppresses hepatic gluconeogenesis, particularly by downregulating glucose‐6‐phosphatase [41, 60, 61, 62]. Additionally, propolis promotes hepatic glycolysis and enhances glucose utilization [33]. In terms of lipid regulation, propolis modulates peroxisome proliferator‐activated receptors (PPARs α, γ, and δ), which influence the expression of genes involved in lipid metabolism, thereby reducing TG and cholesterol synthesis and regulating their absorption [55, 60]. It also increases the production of ATP‐binding cassette transporters in the liver, supporting reverse cholesterol transport and HDL‐C synthesis [55]. By activating PPARγ, propolis may further improve insulin sensitivity and modulate lipolysis and lipogenesis, resulting in better control of hyperglycemia and dyslipidemia [55, 60].

Although previous studies [20, 59] have suggested that propolis may lower BP through various mechanisms such as inhibiting angiotensin‐converting enzyme, promoting nitric oxide‐mediated vasodilation, exhibiting diuretic effects, inducing acetylcholine relaxation of vascular smooth muscle, and preventing calcium influx into smooth muscle cells, present meta‐analysis did not find significant effects on BP or WC. Similarly, animal studies indicate that propolis may help prevent obesity by modulating gut microbiota composition and function, regulating leptin secretion, and PPARs in liver and adipose tissue [60, 63]. However, these mechanisms have not been sufficiently validated in human trials. The lack of significant findings in the present analysis may be partly due to the limited number of eligible studies for these outcomes, only seven for BP and eight for WC, which reduces statistical power. Additionally, the relatively short intervention durations in most included trials may not be long enough to produce measurable changes in these parameters. Moreover, the multifactorial regulation of BP and central obesity, which is strongly influenced by factors such as diet, physical activity, genetics, and medication use, may obscure any modest effects of propolis supplementation in clinical settings [53, 58].

Propolis is generally considered safe for human consumption when used within commonly recommended doses, and adverse effects are rare in individuals without a history of allergic reactions. Clinical studies have shown good tolerability, with no significant changes in liver or kidney function markers during supplementation periods. However, high intakes, such as 15 g/day, have been linked to adverse effects, especially in individuals sensitive to bee products. These effects can include skin rashes, respiratory symptoms, gastrointestinal discomfort, or irritation of the oral mucosa [59]. Although such side effects are rare, they highlight the importance of dose control and individual sensitivity awareness.

A major strength of this meta‐analysis is the inclusion of a relatively large number of clinical trials, along with systematic subgroup, which enhance the reliability of the findings. Additionally, the absence of evidence for publication bias and the consistency of results in sensitivity testing further support the conclusions drawn from the analysis. However, there are several limitations to consider. First, the study protocol was not registered in advance, which may introduce potential reporting bias. Most of the studies included in this meta‐analysis involved both genders, while some did not report the participants' gender at all. As a result, a sex‐specific subgroup analysis could not be conducted. Given the known biological and hormonal differences between sexes, it is possible that propolis supplementation may have different effects based on sex. Furthermore, most of the included trials were conducted in Iran, which may limit the applicability of the findings to other populations with different genetic, environmental, and dietary backgrounds. Insufficient reporting on bee species and the chemical composition of propolis in most studies limits subgroup analysis and affects comparability. Due to natural variability, the lack of standardization reduces result reliability. Future research should use well‐standardized propolis preparations to improve quality. Additionally, there was high heterogeneity for FBS and HDL‐C, so these results should be interpreted with caution. Lastly, key confounding factors such as dietary intake, physical activity, and smoking status were not reported or controlled for in most trials, which hinders the ability to assess their potential impact on the observed effects.

4.1. Clinical Recommendations

Our findings suggest that propolis may be a useful supportive therapy, especially for T2DM patients, as it significantly reduces FBS and TG levels. However, its effectiveness depends on the right dosage, treatment duration, and individual patient factors. The absorption and processing of propolis's active compounds can vary, affecting how well it works. Currently, there is limited information on its bioavailability and metabolism, making it difficult to determine the optimal dose and predict outcomes. More research is needed to explore the best ways to prepare and use propolis, its interactions with other medications, and its long‐term safety. Until clearer guidelines are established through further clinical trials, propolis should be used with caution.

5. Conclusion

The present meta‐analysis indicates that propolis supplementation can reduce FBS and TG levels. However, it does not significantly affect other components of MetS. These findings suggest potential benefits for glycemic and dyslipidemia control. However, considering the existing limitations, further research is needed to determine the optimal dosage, standardize propolis composition, and evaluate long‐term effects to better define its clinical applicability.

Author Contributions

Safia Obaidur Rab: conceptualization, investigation, funding acquisition, writing – original draft, writing – review and editing, visualization, validation, software, formal analysis, project administration, resources, supervision, data curation, methodology. Mudher Kadhem: writing – original draft, investigation, writing – review and editing, conceptualization, methodology, data curation. Malathi H.: writing – original draft, investigation, writing – review and editing, methodology, conceptualization, data curation. Swati Mishra: writing – original draft; writing – review and editing. Ishant Arora: writing – original draft; writing – review and editing. Mehran Nouri: conceptualization, investigation, funding acquisition, writing – original draft, writing – review and editing, visualization, validation, methodology, software, formal analysis, resources, supervision, data curation, project administration.

Funding

The authors received no specific funding for this work.

Disclosure

The lead author Mehran Nouri affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: Funnel plots for the effect of propolis on (a) fasting blood sugar, (b) triglyceride, (c) high density lipoprotein cholesterol, (d) waist circumference, (e) systolic blood pressure, and (f) diastolic blood pressure.

Table S1: PRISMA 2020 checklist.

Data Availability Statement

The data set and analyses are available from the corresponding author on reasonable request.