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. 2026 Jun 23;15:231. doi: 10.1186/s13643-026-03251-5

Meta-analysis of the effects of ginger supplementation on glycemic control, blood pressure and lipid profile in patients with type 2 diabetes

Xin Chen 1, Shaomin Cheng 1,✉, Delin Zhang 1,✉
PMCID: PMC13495174  PMID: 42337792

Abstract

Background

Ginger has shown promising effects on metabolism in preclinical and clinical studies. This updated and comprehensive meta-analysis aimed to investigate the effects of ginger on the cardiometabolic profile of patients with type 2 diabetes.

Methods

Scopus, PubMed, the Cochrane Library, and Web of Science were searched from the inception to July 2, 2025, to find randomized controlled trials that compared the effects of ginger with placebo on glycemic indexes, blood pressure, and lipid profile among those with type 2 diabetes. A random-effects model (DerSimonian-Laird) was employed to pool data because of high heterogeneity.

Results

In total, 13 articles were included in this meta-analysis. Ginger supplementation was associated with a statistically significant reduction in fasting blood sugar (FBS) (MD −16.27 mg/dl, 95% CI (−25.75, −6.80), I2 = 86.39%), hemoglobin A1c (HbA1c) (MD −0.41%, 95% CI (−0.63, −0.20), I2 = 92.09%) systolic blood pressure (MD −1.62, 95% CI (−3.01, −0.24), I2 = 6.09%), and triglyceride level (MD −17.10 mg/dL, 95% CI (−31.13, −3.07), I2 = 81.61%); however, the magnitude of these effects was of limited clinical importance. A statistically significant increase in high-density lipoprotein cholesterol (HDL-C) level (MD 2.13 mg/dL, 95% CI (0.44, 3.82), I2 = 85.72%) was also observed. However, treatment with ginger did not significantly change homeostasis model assessment for insulin resistance (HOMAIR), diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol (LDL-C), and body mass index (BMI).

Conclusion

This meta-analysis indicated that ginger may probably improve the metabolic indices of patients with type 2 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13643-026-03251-5.

Keywords: Ginger, Type 2 diabetes, Blood pressure, Lipid profile, Glycemic index, HbA1c, Fasting blood sugar, Triglyceride

Introduction

Globally, there were 529 million subjects with diabetes in 2021, with a global age-standardized prevalence of 6.1% [1]. Furthermore, over 1.31 billion individuals are projected to suffer from diabetes in 2050, with an expected age-standardized prevalence of more than 10% [1]. Patients with type 2 diabetes suffer from a series of vascular diseases and metabolic syndrome, leading to end-organ damage [2].

Some herbal medicines and nutrients can affect these diseases [3, 4]. Ginger, a herbal medicine with many active components, such as volatile oil, gingerol analogues, phenylalkanoids, sulfonates, diarylheptanoids, and monoterpenoid glycosides, was shown to promote the expression of hepatic glycolytic enzymes in streptozotocin-induced diabetic rats, thereby ameliorating hyperglycemia and hyperlipidemia [5, 6]. Furthermore, ginger was found to enhance insulin release and sensitivity and modulate lipid metabolism to improve metabolism in diabetes [7, 8].

Due to the promising results of preclinical studies, soon clinical trials started to measure the effects of ginger on individuals with type 2 diabetes [9]. Although several clinical trials have investigated the therapeutic effects of ginger in the management of patients with type 2 diabetes, there are significant differences and inconsistencies among the results of the existing trials in terms of the direction and magnitude of the effect, making it challenging to achieve clear recommendations [9–21].

Although there are some meta-analyses in this regard, several new clinical trials have been published in recent years [22, 23]. Therefore, this updated and comprehensive meta-analysis aimed to investigate the effects of ginger on the cardiometabolic profile of patients with type 2 diabetes.

Method

Search strategy

We systematically searched PubMed, the Cochrane Library, Web of Science, and Scopus from the inception to July 2, 2025, using the following search keywords: (“ginger” OR “Zingiber officinale”) AND (“blood pressure” OR “systolic blood pressure” OR “diastolic blood pressure” OR “cholesterol” OR “triglyceride” OR “HDL” OR “LDL” OR “low-density lipoprotein” OR “high-density lipoprotein” OR “VLDL” OR “very low-density lipoprotein” OR “low density lipoprotein” OR “high density lipoprotein” OR “very low density lipoprotein” OR “HbA1c” OR “hemoglobin A1c” OR “FBS” OR “FPG” OR “fasting blood sugar” OR “fasting plasma glucose” OR “HOMA” OR “HOMAIR” OR “homeostasis model assessment for insulin resistance”).

The detailed search strategy is shown in Supplementary Material 1. Besides, both backward (reference list screening) and forward (citation tracking) snowballing searches were performed for all included studies [3]. All articles were transferred to EndNote 9.0, and duplicate records were deleted. This study adhered to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline [24], and the protocol of our meta-analysis was registered in PROSPERO (CRD420251009998).

Inclusion and exclusion criteria

The inclusion criteria were as follows: (I) study design being a randomized controlled trial; (II) comparing the effect of ginger to placebo on the glycemic indexes, lipid profile, blood pressure, and BMI; and (III) all participants had type 2 diabetes.

The exclusion criteria were as follows: (I) observational studies, case reports, and review articles; (II) absence of a placebo group; (III) reporting none of the target outcomes, including systolic and diastolic blood pressure, total cholesterol, LDL-C, HDL-C, triglyceride, FBS, HbA1c, HOMAIR, and BMI; and (IV) ginger was administered combined with other drugs.

Data extraction and outcome measures

The study selection and data extraction were conducted by two independent reviewers (X.C. and D.Z.). During the screening phase, titles and abstracts were first assessed independently. Then, the full text of potentially eligible studies was evaluated by two independent reviewers (X.C. and D.Z.). Data extraction was also performed independently using a standardized extraction form. Any disagreements at either stage were resolved through discussion. In case of disagreement, a third reviewer (S.C.) was consulted to make the final decision. Agreement between two reviewers was evaluated using Cohen's kappa coefficient. This coefficient for steps of initial screening and full-text assessment was estimated at 0.91 and 0.93, respectively.

The following data were collected: study characteristics (the first author’s name, trial registry identifier, year of publication, and country of study), population (sample size, sex, age, baseline BMI, and baseline HbA1c), interventions (dose of ginger, type of placebo, length of treatment), and the outcomes (systolic and diastolic blood pressure, total cholesterol, LDL-C, HDL-C, triglyceride, FBS, HbA1c, HOMAIR, and BMI).

Risk of bias assessment

Two reviewers (X.C. and D.Z.) independently evaluated the risk of bias for all included trials, and all disagreements were solved through discussion. Risk of bias was assessed at the outcome level using the revised Cochrane risk-of-bias tool for randomized trials (RoB2) and in accordance with Cochrane guidance [25]. Thus, we used the tool for assessing the risk of bias for triglyceride level, an outcome reported by most studies. In case of disagreement, a third reviewer (S.C.) was consulted to make the final decision. We used the revised Cochrane risk-of-bias tool for randomized trials (RoB2) to determine the risk of bias. The tool assesses the risk of bias based on the randomization process, deviations from intended interventions, missing outcome data, outcome measurement, and selection of the reported results, thereby providing an overall risk of bias. All domains receive one of the following ranks: low risk of bias, some concerns, and high risk of bias [26].

Statistical analysis

Changes in mean and standard deviation (SD) for all outcome measures were extracted from the articles. These data were employed to calculate the pooled effect size. We utilized the chi-square test, τ2, Cochran’s Q test, I2 statistic to determine between-trial heterogeneity, and I2 more than 50% was deemed high statistical heterogeneity [27]. Because of significant methodological and statistical heterogeneity, a random-effects model (the DerSimonian and Laird approach) was employed to pool data [28]. Moreover, a random-effects model was selected to consider clinical and methodological diversity across the studies, including differences in study populations, interventions, outcome definitions, and study designs [29]. Parameters entered into the random model include sample size, mean, and standard deviation related to the cardiometabolic profile of patients with type 2 diabetes in the control and treatment groups. These parameters were used to compute mean differences (MD) and their confidence intervals. This meta-analysis was conducted using Stata version 17.0 (StataCorp, TX, USA).

Other analyses

Subgroup analysis was performed based on baseline characteristics to identify the factors associated with the effect of ginger on metabolic indices in type 2 diabetes [30]. Based on distribution of data entered to the meta-analysis, countries were divided into two groups of Iran and other countries, sample size into two groups of less than 50 and more than 50, length of treatment into two groups of less than 10 weeks and 10 weeks or more, ginger dose into two groups of 2000 mg/day or less and more than 2000 mg/day, and percentage of males into two groups of less than 40% and more than 40%. The chi-square test was used to assess between-group differences in subgroup analysis.

Using the leave-one-out test, sensitivity analysis was conducted to assess the robustness of our findings [31]. Publication bias and small study effect were measured using funnel plot and Egger’s and Begg’s tests [32]. Additionally, the GRADE pro software was utilized to evaluate the level of certainty associated with the reported outcomes [33].

Results

Systematic search results

First, we found 144 records in the Cochrane Library, 266 records in PubMed, 835 records in Scopus, and 452 records in Web of Science. Of 1697 articles, 121 duplicate reports were deleted. Due to irrelevance or incompliance with the inclusion criteria, 1507 articles were excluded after screening the titles and abstracts. Next, the full-text version of 69 articles was precisely evaluated and their compliance with the inclusion and exclusion criteria was measured. Backward and forward snowballing searches did not identify any new eligible articles beyond the papers found through the database search. After full-text review, 56 articles were excluded for the following reasons: non-randomized or observational study design (n = 36), secondary analyses or substudy reports (n = 2), absence of relevant outcome data (n = 2), and inclusion of participants without type 2 diabetes (n = 16). Consequently, 13 randomized controlled trials comprising 422 participants in the ginger group and 415 participants in the placebo group met the eligibility criteria and were included in the meta-analysis [9–21] (Table 1 and Fig. 1). Except for three studies conducted by Carvalho et al., Elsaadany et al., and El Gayar et al., all other studies were from Iran. Except for the study conducted by Carvalho et al., all other studies had a sample size of less than 100. The length of treatment ranged from 8 to 12 weeks across studies. The dose of ginger ranged from 1200 mg/day to 3000 mg/day. The mean age of participants ranged from 46 to 59 years. Males constituted more than 50% of participants only in studies conducted by Veisi et al. and El Gayar et al. (Table 1).

Table 1.

Study characteristics

First author’s name Publication year Age (year, mean) Country of study Gender Ginger dose Length of treatment Number of participants in the ginger group Number of participants in the placebo group Type of placebo References
Arablou et al. 2015 52.3 Iran Both 1600 mg/day 12 weeks 33 30 Wheat flour [9]
Azimi et al. 2016 54.4 Iran Both 3000 mg/day 8 weeks 41 39 The solvent (black tea) [11]
Makhdoomi Arzati et al. 2017 50.7 Iran Both 2000 mg/day 10 weeks 23 22 Wheat flour [21]
Azimi et al. 2015 54.4 Iran Both 3000 mg/day 8 weeks 41 39 The solvent (black tea) [13]
Carvalho et al. 2020 58.64 Brazil Both 1200 mg/day 12 weeks 47 56 Microcrystalline cellulose [12]
Elsaadany et al. 2022 52.8 Saudi Arabia Both 3000 mg/day 8 weeks 11 11 Cellulose powder [10]
El Gayar et al. 2019 46.2 Egypt Both 1800 mg/day 8 weeks 40 40 Wheat flour [14]
Ghoreishi et al. 2024 54.01 Iran Both 2000 mg/day 12 weeks 36 36 Starch [15]
Mahluj et al. 2013 51.1 Iran Both 2000 mg/day 8 weeks 28 30 Corn starch [16]
Talaei et al. 2017 50.44 Iran Both 3000 mg/day 8 weeks 40 41 Cellulose microcrystalline [18]
Veisi et al. 2023 59.84 Iran Both 2000 mg/day 8 weeks 20 21 Starch [20]
Khandouzi et al. 2015 46.15 Iran Both 2000 mg/day 12 weeks 22 19 Lactose [17]
Mozaffari-khosravi et al. 2014 50.44 Iran Both 3000 mg/day 8 weeks 40 41 Cellulose microcrystalline [19]
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Fig. 1.

Fig. 1

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Systematic search flowchart

Risk of bias assessment

The revised Cochrane risk-of-bias tool for randomized trials (RoB2) revealed a high risk of bias for the articles reported by El Gayar et al. and Azimi et al. due to their single-blinded design [13, 14]. Other studies generally indicated a low risk of bias (Supplementary material 2).

Meta-analysis

Glycemic indexes

Because of considerable methodological heterogeneity, we employed a random-effects model (the DerSimonian and Laird approach) to perform this meta-analysis. The model indicated that ginger significantly decreased FBS (MD = −16.27 mg/dL, 95% CI (−25.75, −6.80), I2 = 86.39%, τ2 = 158.79, and Cochran’s Q: 66.11) (Fig. 2), HbA1c (MD = −0.41%, 95% CI (−0.63, −0.20), I2 = 92.09%, τ2 = 0.06, and Cochran’s Q: 113.8) (Fig. 3), but its effects on HOMAIR did not reach the threshold of statistical significance (MD = −0.37%, 95% CI (−0.78, 0.03), I2 = 76.35%, τ2 = 0.13, and Cochran’s Q: 21.14) (Fig. 4). Substantial between-study heterogeneity was observed for most outcomes, with I2 values frequently exceeding 75%.

Fig. 2.

Fig. 2

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The effect of ginger on FBS

Fig. 3.

Fig. 3

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The effect of ginger on HbA1c

Fig. 4.

Fig. 4

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The effect of ginger on HOMAIR

Blood pressure

Pooling data from 4 clinical trials, the model indicated that ginger significantly reduced systolic blood pressure (MD = −1.62 mmHg, 95% CI (−3.01, −0.24), I2 = 6.09%, τ2 = 0.44, and Cochran’s Q: 3.29) (Fig. 5), but not diastolic blood pressure (MD = −2.41 mmHg, 95% CI (−5.45, 0.64), I2 = 76.40%, τ2 = 6.07, and Cochran’s Q: 12.71) (Fig. 6).

Fig. 5.

Fig. 5

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The effect of ginger on systolic blood pressure

Fig. 6.

Fig. 6

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The effect of ginger on diastolic blood pressure

Lipid profile

Regarding lipid profile, ginger significantly decreased triglyceride level (MD = −17.10 mg/dL, 95% CI (−31.13, −3.07), I2 = 81.61%, τ2 = 334.97, and Cochran’s Q: 48.94) (Fig. 7) and increased HDL-C level (MD = 2.13 mg/dL, 95% CI (0.44, 3.82), I2 = 85.72%, τ2 = 4.35, and Cochran’s Q: 70.03) (Fig. 8). However, treatment with ginger did not change total cholesterol level (MD = −4.78 mg/dL, 95% CI (−15.27, 5.70), I2 = 92.45%, τ2 = 208.75, and Cochran’s Q: 119.21) (Fig. 9) and LDL-C level (MD = −5.36 mg/dL, 95% CI (−12.37, 1.65), I2 = 90.93%, τ2 = 99.72, and Cochran’s Q: 110.31) (Fig. 10).

Fig. 7.

Fig. 7

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The effect of ginger on triglyceride

Fig. 8.

Fig. 8

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The effect of ginger on HDL-C

Fig. 9.

Fig. 9

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The effect of ginger on total cholesterol

Fig. 10.

Fig. 10

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The effect of ginger on LDL-C

BMI

Pooling data from 8 studies, the random-effects model showed that the beneficial effects of ginger on BMI did not meet the threshold of statistical significance (MD = −0.25 kg/m2, 95% CI (−0.52, 0.03), I2 = 83.05%, τ2 = 0.08, and Cochran’s Q: 41.31) (Fig. 11). Although several outcomes reached statistical significance, the magnitude of effects for systolic blood pressure and BMI was small and may be of limited or modest clinical importance.

Fig. 11.

Fig. 11

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The effect of ginger on BMI

Subgroup analysis

Subgroup analyses were performed for the effects of ginger on triglyceride levels based on participants’ age, gender, daily dose of ginger, country of study, length of treatment, and sample size. The results revealed that ginger was significantly more effective in non-Iranian studies when administering a ginger dose of 2000 mg/day or less, and in studies where more than 40% of participants were male and the mean age of participants was less than 54 years. However, there was no significant difference between subgroups of the length of treatment and sample size (Supplementary material 3). However, the risk of type I error inflation from multiple subgroup analyses must be considered.

Sensitivity analysis

We conducted a sensitivity analysis for the effect of ginger on triglyceride levels using the leave-one-out test, one of the variables that was reported in at least 10 studies. The results showed that the removal of the study conducted by Arablou et al. made the non-significant result (p = 0.056), showing that the overall results regarding the effect of ginger on triglyceride levels may rely on the study conducted by Arablou et al. (Supplementary material 4).

Publication bias

Since the funnel plot indicated degrees of asymmetry in visual assessment, we conducted Egger and Begg’s tests to assess the risk of publication bias and small-study effects. The Egger and Begg’s tests indicated no significant risk of publication bias (P = 0.253 and P = 0.858, respectively) (Supplementary material 5).

Certainty assessment

Supplementary material 6 represents GRADE profiles related to the outcomes. The evaluation indicated that the level of confidence for outcomes of FBS, HbA1c, HOMAIR, systolic blood pressure, diastolic blood pressure, triglyceride, HDL-C, total cholesterol, LDL-C, and BMI was low, low, moderate, moderate, very low, low, low, very low, very low, and very low (Supplementary material 6).

Discussion

By pooling data from randomized controlled trials, this meta-analysis suggests that ginger supplementation may improve several cardiometabolic parameters in individuals with type 2 diabetes, including reductions in FBS, HbA1c, systolic blood pressure, and triglyceride levels, as well as an increase in HDL-C; however, no significant effects were observed for total cholesterol, LDL-C, HOMA-IR, diastolic blood pressure, or BMI. Although several outcomes reached statistical significance, the magnitude of some effects particularly the reduction in systolic blood pressure (approximately 1.6 mmHg) and BMI (approximately 0.25 kg/m2) may be clinically modest at the individual patient level. These findings should therefore be interpreted primarily as indicative of potential adjunctive or population-level benefits rather than clinically meaningful standalone effects. These findings indicate that ginger may exert modest benefits on selected metabolic outcomes, but the certainty of evidence remains limited. Individuals with type 2 diabetes are at increased risk of cardiovascular and cerebrovascular complications and often require multiple pharmacological therapies [34, 35]. In this context, ginger may have potential as an adjunctive intervention targeting multiple metabolic risk factors. Its proposed multi-component, multi-target mechanisms, such as effects on insulin secretion, glucose transporter type 4 translocation, lipid metabolism, inflammation, and oxidative stress, are biologically plausible but are largely supported by preclinical and indirect clinical evidence and should therefore be considered hypothesis-generating rather than confirmatory [36–40].

Our findings are in line with a previous meta-analysis conducted by Ebrahimzadeh et al., which reported improvements in FBS, HbA1c, and systolic blood pressure, but not lipid parameters [22]. Interestingly, the current meta-analysis revealed a notable impact on triglyceride levels and HDL-C. Nonetheless, sensitivity analyses confirmed that the triglyceride-lowering effect was insignificant after excluding the single influential study, thus warranting judicious interpretation. Subgroup analyses emphasized on greater effects in younger individuals, possibly indicating less advanced metabolic dysfunction; nevertheless, these findings were exploratory, not based on formal interaction testing, and may reflect residual confounding or chance. This updated meta-analysis with 13 articles indicated that ginger significantly decreased FBS, HbA1c, and systolic blood pressure, but could not significantly decrease diastolic blood pressure. In addition, we found that treatment with ginger significantly lowered triglyceride levels and increased HDL-C levels. Furthermore, our meta-analysis indicated that ginger was more effective for males younger than 54 years. Consistently, Ebrahimzadeh et al. indicated that ginger was more effective when administered to individuals older than 50 years [22], suggesting that treatment with ginger may be more effective for younger individuals who have not yet experienced less severe organ damage.

Previous meta-analyses assessing ginger supplementation have also reported beneficial effects on triglycerides and body weight, particularly among individuals with diabetes or obesity [41, 42]. Given the established role of obesity and dyslipidemia in metabolic syndrome and cardiovascular risk, even modest improvements may be clinically relevant [43]. Overall, while ginger supplementation may offer adjunctive benefits for glycemic control and selected lipid parameters in type 2 diabetes, the evidence is characterized by heterogeneity and low to very low certainty. Thus, the large degree of between-study heterogeneity substantially limited confidence in the pooled estimates and contributed to downgrading the certainty of evidence. Therefore, large, well-designed, multicenter randomized controlled trials are required to confirm these findings and to better define the populations most likely to benefit.

Limitations

This study has several limitations that should be considered when interpreting the findings. Firstly, some included trials employed a single-blind design, which may have increased the risk of performance and detection bias, contributing to downgrading the certainty of evidence for several outcomes. Secondly, there was notable clinical and methodological variability across studies, particularly in terms of ginger dosage and intervention duration, which may have contributed to inconsistency and reduced confidence in the pooled estimates. Thirdly, most trials were conducted predominantly in a single country with a limited sample size, resulting in imprecision and limited external validity, thereby attenuating the certainty of evidence due to indirectness. Consequently, large, multicenter randomized controlled trials are warranted to validate these findings. Finally, considerable statistical heterogeneity was noted for the majority of outcomes, despite the implementation of random-effects models and subgroup analyses to address the issue.

Conclusion

Results suggest that ginger supplementation may be associated with modest improvements in FBS, HbA1c, systolic blood pressure, triglyceride levels, and HDL-C among individuals with type 2 diabetes, while no significant effects were observed on total cholesterol, LDL-C, HOMA-IR, or diastolic blood pressure. Given the substantial heterogeneity across studies and the low to very low certainty of the evidence, these results should be interpreted with caution. Ginger should be considered an adjunctive, rather than a primary, therapeutic option, and its potential metabolic benefits remain exploratory and hypothesis-generating. Further large-scale, well-designed randomized controlled trials are required to confirm these findings and to clarify the clinical relevance of ginger supplementation in the management of type 2 diabetes.

Supplementary Information

Supplementary Material 1.  (15.6KB, docx)
Supplementary Material 2. (203KB, docx)
Supplementary Material 3. (312KB, docx)
Supplementary Material 4. (136.4KB, docx)
Supplementary Material 5. (53KB, doc)
Supplementary Material 6. (19.1KB, docx)

Acknowledgements

None.

Authors’ contributions

Xin Chen (literature search, data extraction, and writing the draft), Shaomin Cheng (conceptualization, literature search, data extraction, data analysis, and writing the draft), and Delin Zhang (conceptualization, writing, and editing the article). All authors reviewed and edited the manuscript and approved the final version of the manuscript.

Funding

This study was supported by the following funds:

1. High level Key Discipline Construction Project of Traditional Chinese Medicine by the State Administration of Traditional Chinese Medicine—Traditional Chinese Medicine Health Preservation (National Medical Education Letter [2023] No. 85)

2. Jiangxi Provincial Administration of Traditional Chinese Medicine Key Research Laboratory on the Fundamentals of Chinese Medicine Evidence (Gan TCM Science and Education Word [2022] No.8–4).

3. Jiangxi University of Traditional Chinese Medicine School-level Science and Technology Innovation Team (CXTD22016)

Data availability

Data will be available by the corresponding author on a reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Shaomin Cheng, Email: csm21cn@139.com.

Delin Zhang, Email: 389372362@qq.com.

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Associated Data

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Supplementary Materials

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Supplementary Material 2. (203KB, docx)
Supplementary Material 3. (312KB, docx)
Supplementary Material 4. (136.4KB, docx)
Supplementary Material 5. (53KB, doc)
Supplementary Material 6. (19.1KB, docx)

Data Availability Statement

Data will be available by the corresponding author on a reasonable request.

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