Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: An umbrella review and updated meta-analysis

Thanika Pathomwichaiwat; Peerawat Jinatongthai; Napattaoon Prommasut; Kanyarat Ampornwong; Wipharak Rattanavipanon; Surakit Nathisuwan; Ammarin Thakkinstian

doi:10.1371/journal.pone.0288997

. 2023 Jul 20;18(7):e0288997. doi: 10.1371/journal.pone.0288997

Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: An umbrella review and updated meta-analysis

Thanika Pathomwichaiwat ¹, Peerawat Jinatongthai ^2,^*, Napattaoon Prommasut ³, Kanyarat Ampornwong ³, Wipharak Rattanavipanon ³, Surakit Nathisuwan ^3,^*, Ammarin Thakkinstian ⁴

Editor: Mohammad Reza Mahmoodi⁵

PMCID: PMC10359013 PMID: 37471428

Abstract

Aims

This study aims to comprehensively review the existing evidence and conduct analysis of updated randomized controlled trials (RCTs) of turmeric (Curcuma longa, CL) and its related bioactive compounds on glycemic and metabolic parameters in patients with type 2 diabetes (T2DM), prediabetes, and metabolic syndrome (MetS) together with a sub-group analysis of different CL preparation forms.

Methods

An umbrella review (UR) and updated systematic reviews and meta-analyses (SRMAs) were conducted to evaluate the effects of CL compared with a placebo/standard treatment in adult T2DM, prediabetes, and MetS. The MEDLINE, Embase, The Cochrane Central Register of Control Trials, and Scopus databases were searched from inception to September 2022. The primary efficacy outcomes were hemoglobin A1C (HbA1C) and fasting blood glucose (FBG). The corrected covered area (CCA) was used to assess overlap. Mean differences were pooled across individual RCTs using a random-effects model. Subgroup and sensitivity analyses were performed for various CL preparation forms.

Results

Fourteen SRMAs of 61 individual RCTs were included in the UR. The updated SRMA included 28 studies. The CCA was 11.54%, indicating high overlap across SRMAs. The updated SRMA revealed significant reduction in FBG and HbA1C with CL supplementation, obtaining a mean difference (95% confidence interval [CI]) of –8.129 (–12.175, –4.084) mg/dL and –0.134 (–0.304, –0.037) %, respectively. FBG and HbA1C levels decreased with all CL preparation forms as did other metabolic parameters levels. The results of the sensitivity and subgroup analyses were consistent with those of the main analysis.

Conclusion

CL supplementation can significantly reduce FBG and HbA1C levels and other metabolic parameters in T2DM and mitigate related conditions, including prediabetes and MetS.

Trial registration

PROSPERO (CRD42016042131).

Introduction

Type 2 diabetes mellitus (T2DM) has rapidly become a leading global health burden among non-communicable diseases (NCD), given its serious complications, including heart disease, cerebrovascular disease, renal failure, limb amputation and blindness [1]. Over 437.9 million people were living with T2DM in 2019, 80% of whom were in low- and middle-income countries (LMICs). The disease accounts for approximately 1.5 million deaths and 66.3 million disability-adjusted life years worldwide [2]. The rise in T2DM cases along with the public health burden has been much more prominent in the developing than in the developed countries, which may be due to limited healthcare resources, less organized and immature health services, lower health literacy, and limited access to advanced treatment options [3,4].

While the management of T2DM requires multiple interventions ranging from lifestyle modification, social policy, health system management, to public education, access to treatment is always the cornerstone of disease control [5–8]. The accessibility of advanced treatments among LMICs is limited due to the high cost of newer treatments [9]; thus, many LMICs, especially those in tropical regions, have attempted to uncover the pharmacological properties of native plants that have long been used for medicinal purposes [10]. Some plants have been extensively studied for diabetes, Curcuma longa L. (CL), a member of the Zingiberaceae family, has been used as both food and medicine [11–13]. Curcumin and its related compounds, such as curcuminoids and essential oils, have been extensively studied for their anti-diabetic effects ranging from molecular mechanisms, cellular signaling, in vitro/in vivo studies and randomized, controlled trials (RCTs) [12,14,15]. Several systematic reviews and meta-analyses (SRMAs) of RCTs [15–20] have been performed to assess the anti-diabetic effects of curcumin, but the results obtained were conflicting due to different populations, CL preparation forms, duration of use and outcomes.

An umbrella review (UR) can summarize the findings of these SRMAs and evaluate the quality of evidence, as well as assess the robustness of key findings [21]. Therefore, the present UR of SRMAs of RCTs was conducted to comprehensively review the existing evidence on the effects of turmeric preparations and its related bioactive compounds on glycemic and metabolic parameters in T2DM, prediabetes, and MetS. In addition, an updated MA was also performed by including new RCTs to perform a comprehensive analysis of glycemic and metabolic markers, along with a subgroup analysis of different CL preparation forms.

Methods

Study design

The protocols for the UR and updated MA have been registered with the PROSPERO registry (CRD42016042131). This study has complied with the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting SRMAs [22].

Search strategy

For the UR, a literature search for SRMAs was conducted without language restrictions on the MEDLINE (PubMed), EMBASE, Cochrane Central Register of Control Trials, and Scopus databases from inception to September 2022. For the updated MA, we retrieved RCTs from the most recent SRMAs conducted between March and September 2022. The search algorithms and strategies are provided in Figs 1 and 2 and S1 Table in S1 File.

Study selection

Two reviewers (T.P. and P.J.) independently screened the titles and abstracts of the retrieved articles to identify potentially relevant studies. The full texts were retrieved if no decision the selection could be made. Any discrepancy was resolved by a third reviewer (S.N.). Studies were eligible for review if they met the following criteria: (i) SRMAs of RCTs or individual RCTs; (ii) studied in adult patients with T2DM, prediabetes, or MetS; (iii) investigated the effects of CL supplementation in addition to the standard treatment and compared with the placebo or standard treatment; (iv) compared blood glucose parameters (i.e., fasting blood glucose [FPG], glycated hemoglobin A1C [HbA1C]).

Types of interventions

CL supplementation could be administered in any of the following forms: 1) a whole preparation rich in phytochemicals, e.g., dry rhizome or standardized CL powder; 2) an extract preparation containing only portion of the phytochemicals found in CL, e.g., a standardized curcuminoid extract; and 3) a bioavailability-enhanced preparation, a modified CL preparation containing curcumin or curcuminoids (e.g., nanomicelle curcumin, liposome preparations [e.g., phospholipid complex, phytosome, phosphatidylcholine, phosphatidylserine, or phospholipid curcumin]) or any CL preparation with a low dose of piperine (S2 Table in S1 File).

Outcomes of interest

The primary outcomes were the HbA1C and FBG levels measured 4–16 weeks after receiving CL supplementation. Secondary outcomes were lipid profiles: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG). The other selected outcomes were also collected including systolic blood pressure (SBP), diastolic blood pressure (DBP), homeostatic model assessment of insulin resistance (HOMA-IR), uric acid and high sensitivity C-reactive protein (hs-CRP).

Data extraction and quality assessment

Relevant data were extracted by two reviewers (N.P. and K.A.) using a standardized extraction form. The extracted data included study/patient characteristics, interventions, outcomes, and other relevant findings. For outcomes, pooled effect sizes of each outcome (i.e., unstandardized mean difference [UMD]; standardized mean difference [SMD]) along with p-values and corresponding 95% confidence intervals (CI) for both postintervention values and the change from baseline were extracted.

The methodological quality of the studies was independently assessed by at least two reviewers (T.P., P.J., or W.R.) using the AMSTAR 2 tool [23] for SRMAs and the Cochrane risk-of-bias tool (RoB 2) [24] for individual RCTs. All extracted data were cross-checked by at least two other reviewers (P.J., W.R., and A.T.) and discrepancies resolved by consensus.

Quality of evidence

The quality of evidence was evaluated by W.R. and P.J. using GRADEpro^® GDT software online version [25] based on five domains, namely, the risk of bias, inconsistency, indirectness, imprecision, and publication bias. The quality of evidence was graded as high, moderate, low, or very low.

Data synthesis and statistical analysis

For the UR, the overlap of primary studies was assessed across the included SRMAs [26,27] and assessed using Graphical Representation of Overlap for OVErviews (GROOVE) [28].

For the updated MA, the effect sizes (i.e., UMD, SMD) along with 95% CIs of the glucose and metabolism outcomes were estimated and pooled across studies using the DerSimonian and Laird random-effects model [29]. Heterogeneity and publication bias were assessed using the I² statistic and Egger’s test [30], respectively.

Pre-specified subgroup analyses were performed for the types of patients (diabetes, prediabetes, and MetS), CL preparation forms (whole powder, extract, and bioavailability-enhanced preparation), and baseline characteristics of patients (including mean body mass index [BMI], lipid and lipoprotein profiles, blood pressure, and blood sugar). Additional post-hoc analyses were also performed for the CL preparation forms. For the sensitivity analyses, small-sized trials (<25th percentile) [31] and trials with a high risk of bias were excluded. All analyses were performed by P.J., T.P., and W.R. using STATA^® version 17.0 (StataCorp, College Station, Texas, USA) along with the self-programmed STATA^® for meta-analysis described elsewhere [32]. A.T. and S.N. provided technical analysis advice. A p-value ≤ 0.05 was considered statistically significant.

Results

Umbrella review

Identification and selection of SRMAs and individual RCTs

Of 3,507 identified studies, 14 SRMAs [15–20,33–40] containing 61 individual RCTs were eligible in the UR (Fig 1). For the updated MA, individual RCTs were screened from two sources. First, of the 61 RCTs in 14 SRMAs, 41 studies were excluded since most of them were conducted in non-interested patients leaving 20 studies that met the inclusion criteria. Second, of 774 RCTs retrieved from the updated search, only 8 studies met the inclusion criteria. In total 28 RCTs were included in the updated MA (Fig 2).

Description of SRMAs

All 14 SRMAs [15–20,33–40] were pairwise MAs, published in 2015–2022 and included 5–26 RCTs with sample sizes of 290–1,790 patients (S3 Table in S1 File). The outcome measures were pooled using either SMD (6 studies) or UMD (9 studies). As for the CL preparation forms, whole, extract and bioavailability-enhanced preparations were evaluated in 9, 10 and 13 studies, respectively. Most SRMAs reported the outcomes at 8–12 weeks. Additional details on each SRMA are provided in S3 Table in S1 File.

Quality of SRMAs

All 14 included SRMAs [15–20,33–40] were graded with critically low quality based on the AMSTAR-2 rating (S4 Table in S1 File) due to missing information on the justification of excluded studies (100%), the funding sources of included studies (100%), missing consideration for the risk of bias when interpreting the results of the review (90.91%), missing assessment of the impact of risk of bias on study results (72.73%), and a lack of established review methods (63.64%).

Degree of overlap in SRMAs

The degree of overlap of individual included RCTs across SRMAs based on the study-citation matrix is shown in S17 Fig in S1 File. The corrected covered area (CCA) score was 11.54% indicating a high degree of overlap. Thirty-one of 91 RCTs were included in multiple SRMAs, indicating limited incremental information in these SRMAs.

Primary efficacy outcomes

Nine SRMAs [15,17–19,33,36,37,39,40] reported changes in FBG after CL administration through various preparations. Of these, 8 SRMAs [15,17–19,33,36,37,39,40] found significant reductions with SMDs of –0.38 to –1.09 mg/dL and UMDs of –8.85 to –27.07 mg/dL. Nine SRMAs [15,16,18,19,35–37,39,40] reported changes in HbA1C, 8 [15,16,18,19,36,37,39,40] found significant reductions with SMDs of –0.42 to –1.06 and UMDs of –0.41% to –0.85% (Table 1). In addition, 3 of 5 SRMAs found significant reductions in HOMA-IR after CL administration with SMDs of –0.28 to –0.8 (Table 1).

Table 1. Difference of post-intervention values and change from baseline for glycemic and metabolic outcomes between Curcuma longa (CL) supplementation and control group from previous SRMAs.

SRMAs	RCTs (N)	Patients (N)	Type of patients	Outcome measurement	Mean difference (95% CI)	I²	Type of mean difference	Analysis model
FBG
Ashtary-Larky, D, 2021 [33]	3	76	MetS	Change from baseline	-28.29 (-63.34, 6.76)	69	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	3	150	T2DM	Change from baseline	-27.07 (-39.61, -14.52)	54	UMD	Random effect
Azhdari M, 2019 [17]	5	359	MetS	Change from baseline	-9.18 (-16.7, -1.66)	90	UMD	Random effect
de Melo, 2018 [18]	8	923	pre-DM, T2DM, MetS	Post-intervention value	-13.86 (-21.17, -6.56)	74	UMD	Random effect
Huang, J, 2019 [19]-	5	509	T2DM	Change from baseline	-0.681 (-1.067, -0.294)	75	SMD	Random effect
Huang, J, 2019 [19]-	8	556	NAFLD/MetS	Change from baseline	-0.149 (-0.348, 0.049)	26	SMD	Random effect
Tabrizi, R, 2018 [36]	7	662	T2DM	Change from baseline	-1.09 (-1.91, -0.27)	95	SMD	Random effect
Tian, J, 2022 [37]	9	565	T2DM	Change from baseline	-8.85 (-14.4, -3.29)	41	UMD	Random effect
Yuan, F, 2022 [39]	11	1,445	T2DM	Change from baseline	-12.88 (-17.49, -8.28)	80	UMD	Random effect
Zhang, T, 2021 [15]	5	564	T2DM	Change from baseline	-0.28 (-0.62, 0.06)	72	SMD	Random effect
Zheng, ZH, 2021 [40]	4	316	T2DM	Post-intervention value	-14.49 (-21.2, -7.79)	34	UMD	Fixed effect
HbA1c
Altobelli, E, 2021 [16]	5	333	T2DM	Change from baseline	-0.42 (-0.72, -0.11)	42	SMD	Random effect
de Melo, 2018 [18]	7	797	pre-DM, T2DM, MetS	Post-intervention value	-0.54 (-1.09, -0.002)	90	UMD	Random effect
Huang, J, 2019 [19]	3	223	NAFLD/MetS	Change from baseline	-0.244 (-0.854, 0.366)	81	SMD	Random effect
Huang, J, 2019 [19]	5	478	T2DM	Change from baseline	-0.455 (-0.713, -0.198)	45	SMD	Random effect
Macena, ML, 2022 [35]	1	46	T2DM	Change from baseline	0.96 (-0.28, 2.20)	NR	SMD	Random effect
Tabrizi, R, 2018 [36]	6	583	T2DM	Change from baseline	-1.06 (-1.51, -0.60)	83	SMD	Random effect
Tian, J, 2022 [37]	9	565	T2DM	Change from baseline	-0.54 (-0.81, -0.27)	65	UMD	Random effect
Yuan, F, 2022 [39]	10	1,405	T2DM	Change from baseline	-0.41 (-0.56, -0.26)	73	UMD	Random effect
Zhang, T, 2021 [15]	5	524	T2DM	Change from baseline	-0.7 (-0.87, -0.54)	0	UMD	Fixed effect
Zheng, ZH, 2021 [40]	3	272	T2DM	Post-intervention value	-0.85 (-1.16, -0.54)	0	UMD	Fixed effect
HOMA-IR
Altobelli, E, 2021 [16]	4	432	T2DM	Change from baseline	-0.41 (-0.66, -0.22)	0	SMD	Random effect
de Melo, 2018 [18]	3	531	pre-DM, T2DM, DLP	Post-intervention value	-1.26 (-3.71, 1.19)	96	UMD	Random effect
Huang, J, 2019 [19]	3	213	NAFLD/MetS	Change from baseline	-0.284 (-0.554, -0.013)	0	SMD	Random effect
Huang, J, 2019 [19]	4	608	T2DM	Change from baseline	-0.360 (-0.762, 0.043)	82	SMD	Random effect
Tabrizi, R, 2018 [36]	5	682	T2DM	Change from baseline	-0.80 (-1.58, -0.02)	95	SMD	Random effect
Zhang, T, 2021 [15]	4	413	T2DM	Change from baseline	-1.76 (-3.65, 0.13)	95	UMD	Random effect
BMI
Altobelli, E, 2021 [16]	3	189	T2DM	Change from baseline	-0.30 (-0.62, 0.02)	0	SMD	Random effect
Zheng, ZH, 2021 [40]	3	233	T2DM	Post-intervention value	-1.75 (-2.23, -1.27)	39	UMD	Fixed effect
TC
Altobelli, E, 2021 [16]	5	333	T2DM	Change from baseline	-0.30 (-0.53, -0.07)	0	SMD	Random effect
Ashtary-Larky, D, 2021 [33]	1	43	MetS	Change from baseline	10.4 (-11.09, 31.89)	NR	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	2	70	T2DM	Change from baseline	-6.24 (-35.65, 23.17)	91	UMD	Random effect
Tabrizi, R, 2018 [36]	8	493	T2DM	Change from baseline	-0.48 (-0.99, 0.02)	87	SMD	Random effect
Tian, J, 2022 [37]	9	565	T2DM	Change from baseline	-8.91 (-14.18, -3.63)	29	UMD	Random effect
Yuan, F, 2019 [38]	14	812	T2DM	Change from baseline	-12.00 (-20.00, -4.04)	46	UMD	Random effect
Zhang, T, 2021 [15]	4	453	T2DM	Change from baseline	-2.00 (-39.91, 35.91)	95	UMD	Random effect
Zheng, ZH, 2021 [40]	5	328	T2DM	Post-intervention value	-11.30 (-20.69, -1.91)	20	UMD	Fixed effect
TG
Altobelli, E, 2021 [16]	5	476	T2DM	Change from baseline	-0.57 (-0.83, -0.31)	42	SMD	Random effect
Ashtary-Larky, D, 2021 [33]	3	76	MetS	Change from baseline	-29.11 (-61.92, 3.68)	40	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	2	70	T2DM	Change from baseline	16.25 (-51.16, 83.67)	92	UMD	Random effect
Azhdari, M, 2019 [17]	5	359	MetS	Change from baseline	-33.66 (-51.28, -16.04)	94	UMD	Random effect
Tabrizi, R, 2018 [36]	8	706	T2DM	Change from baseline	-0.85 (-1.63, -0.07)	95	SMD	Random effect
Tian, J, 2022 [37]	9	565	T2DM	Change from baseline	-18.97 (-36.47, -1.47)	81	UMD	Random effect
Yuan, F, 2019 [38]	12	742	T2DM	Change from baseline	-24.60 (-48.6, -0.59)	84	UMD	Random effect
Zhang, T, 2021 [15]	4	453	T2DM	Change from baseline	-33.45 (-70.6, 3.71)	87	UMD	Random effect
Zheng, ZH, 2021 [40]	4	233	T2DM	Post-intervention value	-13.99 (-26.91, -1.07)	0	UMD	Fixed effect
LDL-C
Altobelli, E, 2021 [16]	5	333	T2DM	Change from baseline	-0.28 (-0.52, -0.04)	0	SMD	Random effect
Ashtary-Larky, D, 2021 [33]	1	43	MetS	Change from baseline	16.50 (-9.06, 42.06)	NR	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	2	70	T2DM	Change from baseline	-4.72 (-34.37, 24.91)	94	UMD	Random effect
Tabrizi, R, 2018 [36]	8	493	T2DM	Change from baseline	-0.10 (-0.78, 0.58)	93	SMD	Random effect
Tian, J, 2022 [37]	9	565	T2DM	Change from baseline	-4.01 (-10.96, 2.95)	50	UMD	Random effect
Yuan, F, 2019 [38]	13	712	T2DM	Change from baseline	-10.70 (-18.1, -3.38)	51	UMD	Random effect
Zhang, T, 2021 [15]	5	497	T2DM	Change from baseline	-6.33 (-12.48, -0.17)	89	UMD	Fixed effect
Zheng, ZH, 2021 [40]	5	321	T2DM	Post-intervention value	-11.19 (-19.54, -2.84)	0	UMD	Fixed effect
HDL-C
Altobelli, E, 2021 [16]	5	333	T2DM	Change from baseline	0.22 (-0.08, 0.52)	46	SMD	Random effect
Ashtary-Larky, D, 2021 [33]	3	76	MetS	Change from baseline	5.66 (3.34, 7.98)	0	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	2	70	T2DM	Change from baseline	6.84 (-2.85, 16.53)	93	UMD	Random effect
Azhdari, M., 2019 [17]	5	359	MetS	Change from baseline	4.89 (4.59, 5.18)	99	UMD	Random effect
Tabrizi, R, 2018 [36]	8	493	T2DM	Change from baseline	0.36 (-0.19, 0.90)	89	SMD	Random effect
Tian, J, 2022 [37]	9	565	T2DM	Change from baseline	0.32 (-0.74, 1.37)	19	UMD	Random effect
Yuan, F, 2019 [38]	16	812	T2DM	Change from baseline	2.74 (-0.02, 5.50)	77	UMD	Random effect
Zhang, T, 2021 [15]	5	497	T2DM	Change from baseline	2.26 (-2.03, 6.55)	90	UMD	Random effect
Zheng, ZH, 2021 [40]	6	361	T2DM	Post-intervention value	2.92 (1.65, 4.19)	0	UMD	Fixed effect
SBP
Ashtary-Larky, D, 2021 [33]	3	76	MetS	Change from baseline	-11.98 (-21.29, -2.68)	69	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	1	0	T2DM	Change from baseline	-3.60 (-8.27, 1.07)	NR	UMD	Random effect
Azhdari, M., 2019 [17]	3	280	MetS	Change from baseline	-1.69 (-4.68, 1.30)	48	UMD	Random effect
DBP
Azhdari, M, 2019 [17]	3	280	MetS	Change from baseline	-2.96 (-5.09, -0.83)	49	UMD	Random effect
CRP
Ashtary-Larky, D, 2021 [33]	2	33	MetS	Change from baseline	-0.64 (-1.52, 0.24)	86	UMD	Random effect
Ashtary-Larky, D, 2021 [33]	1	0	T2DM	Change from baseline	-3.60 (-8.27, 1.07)	NR	UMD	Random effect
Macena, ML, 2022 [35]	1	53	T2DM	Change from baseline	-1.60 (-3.14, -0.06)	NA	SMD	Random effect
Panahi, Y, 2015 [20]	8	562	MetS	Change from baseline	-2.20 (-3.96, -0.44)	95	UMD	Random effect
Hs-CRP
Gorabi, AM, 2022 [34]	3	232	MetS	Change from baseline	-0.81 (-2.72, 1.10)	94	SMD	Random effect
Gorabi, AM, 2022 [34]	4	279	T2DM	Change from baseline	-0.17 (-1.75, 1.42)	66	SMD	Random effect

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Abbreviations: BMI, body mass index; CRP, C-reactive protein; DBP, diastolic blood pressure; FBG, Fasting blood glucose; HbA1C, Hemoglobin A1C; HDL-c, High-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein; LDL-c, Low-density lipoprotein cholesterol; MetS, metabolic syndrome; NR, Not reported; pre-DM, pre-diabetic mellitus; SBP, systolic blood pressure; SMD, standardized mean difference; T2DM, type 2 diabetic mellitus; TC, Total cholesterol; TG, Triglyceride; UMD, unstandardized mean difference.

Secondary efficacy outcomes

Among 7 SRMAs [15,16,33,36–38,40] reporting changes in LDL-C and TC, 4 [16,37,38,40] reported a significant reduction in LDL-C with an SMD of –0.28 and UMDs of –6.33 to –11.19 mg/dL, whereas 4 studies [15,16,38,40] found a significant reduction in TC with an SMD of –0.3 and UMDs of –8.91 to –12 mg/dL. Among 8 SRMAs [15–17,33,36–38,40] reporting changes in TG and HDL-C, 6 [16,17,36–38,40] found a significant reduction in TG with SMDs of –0.57 to –0.85 and UMDs of –13.99 to –33.66 mg/dL. No studies found a significant increase in HDL-C (Table 1). Several SRMAs [16,17,20,33–35,40] also reported changes in BMI, blood pressure, CRP and hs-CRP after CL administration. Results consistently showed a reduction in outcomes with CL administration but with limited significance (Table 1).

Updated meta-analysis

Baseline characteristics

Twenty-eight RCTs [20,41–72] involving 2,362 patients were included in the updated MA. The details and baseline characteristics are shown in S6 and S7 Tables in S1 File, respectively. All studies compared one to two CL forms of supplementation with placebo. Sixteen [41,42,45,49,54,55,58–62,64–66,68,70,71], six [20,43,46,47,52,63,67,72], and three [48,56,57,69] studies involved patients with T2DM, MetS, and prediabetes, respectively, whereas three studies [44,50,51,53] involved a mix of these three patient types. The mean age range was 34.5–70.0 years and 34.2–69 years in the CL and placebo groups, respectively, whereas the mean BMI range 23.4–31.7 kg/m² and 22.8–31.9 kg/m², respectively.

CL preparation forms and outcomes

Regarding CL preparation forms, 11 [42,43,48,49,54,56,57,61,62,70–72], 11 [20,45–47,52,53,60,63–69], and 7 [41,44,50,51,55,58,59,67] RCTs compared CL extract (300–1,950 mg/day), bioavailability-enhanced preparations (80–1,000 mg/day), and whole CL powder (1,000–2,400 mg/day) with a placebo, respectively. One RCT [67] compared a bioavailability-enhanced preparation (1,000 mg/day) with whole CL powder (1,000 mg/day) and placebo. The study duration ranged from 4 to 16 weeks.

In 28 RCTs [20,41–72], the outcomes of interest included FBG (n = 26), HbA1C (n = 22), HOMA-IR (n = 12), insulin (n = 10), TC (n = 22), TG (n = 25), LDL-C (n = 24), HDL-C (n = 24), SBP (n = 15), DBP (n = 15), hs-CRP (n = 10) and uric acid (n = 2) (S6 and S7 Tables in S1 File).

Risk of bias of included RCTs

The overall risk of bias in 7 (25%) [43–45,48,49,52,72], 14 (50%) [41,42,46,47,50,51,53–58,60–62,67,68], and 7 (25%) [20,59,63–66,69,70] RCTs were graded as low, some concern, and high, respectively. The most common reasons were an inadequate randomization process and deviation from intended interventions, which were identified by per-protocol analyses (S5 Table in S1 File).

Primary efficacy outcomes

Twenty-eight RCTs [20,41–72] involving 2,297 participants and 23 RCTs [20,41,45–51,53–57,59–66,68–72] involving 1,945 participants evaluated FBG and HbA1C levels with the administration of three different CL preparation forms, respectively. Figs 3 and 4 show forest plots of the primary efficacy outcomes. CL supplementation resulted in significant reductions in FBG and HbA1C with UMDs of –8.129 mg/dL (95% CI: –12.175, –4.084 mg/dL; p < 0.001; I² = 75.8%) (Fig 3A) and –0.134% (95% CI: –0.304, –0.037; p < 0.001; I² = 83.0%) (Fig 4A) relative to standard/placebo treatment. In addition, CL significantly reduced FBG and HbA1C changes from the baseline with UMDs of –8.833 mg/dL (95% CI: –13.907, –3.758 mg/dL; p < 0.001; I² = 98.2%) (Fig 3B) and –0.517% (95% CI: –0.707, –0.327; p = 0.004; I² = 61.3%) in HbA1C (Fig 4B).

Fig 3 — (a) Post-intervention fasting blood glucose value. (b) Change from baseline.

Fig 4 — (a) Post-intervention HbA1C value. (b) Change from baseline.

Secondary efficacy outcomes

In comparing the postintervention UMDs, CL supplementation resulted in a significant reduction of –6.199 mg/dL (95% CI: –12.061, –0.336 mg/dL; p = 0.038) for LDL-C and 2.746 mg/dL (95% CI: 0.875, 4.617 mg/dL; p = 0.004) for HDL-C. No significant reductions were observed for TC or TG. In comparing the mean changes from baseline, CL resulted in significant reduction of –12.652 mg/dL (95% CI: –20.066, –5.238 mg/dL; p = 0.001) for TG (S8 Table in S1 File).

CL supplementation also significantly reduced postintervention insulin and DBP levels with UMDs of –0.663 μIU/mL (95% CI: –1.156, –0.171μIU/mL; p = 0.008) and –2.876 mmHg (95%CI: –4.919, –0.833 mmHg; p = 0.006), respectively. In comparing the differences in the mean changes from baseline, significant reductions of 0.444% (95%CI: –0.750, –0.139%; p = 0.004) in HOMA-IR, 0.686 μIU/mL (95%CI: –0.890, –0.481 μIU/mL; p < 0.001) in insulin and –0.589 mg/L (–1.158, –0.021 mg/L; p = 0.042) for hs-CRP were observed. All results for the MA are provided in S8 Table in S1 File.

Subgroup analyses

Figs 5 and 6 show forest plots of the subgroup analyses. For the different CL preparation forms, a significant reduction in FBG from baseline was observed for CL extract and bioavailability-enhanced preparations. However, a significant reduction in HbA1C was noted for all CL preparation forms. In addition, a subgroup analysis based on dose showed that the reduction in FBG and HbA1C levels increased with higher doses. Subgroup analysis based on types of patients showed a significant reduction in FBG from baseline in T2DM and MetS, whereas a significant reduction in HbA1C was observed only in T2DM. Furthermore, the findings of the subgroup analysis based on patient baseline characteristics were consistent with those of the main analysis. Details of the subgroup analyses of the primary efficacy outcomes are presented in S9 and S10 Tables in S1 File. The details of the post-hoc analysis of the secondary outcomes stratified by CL preparation forms are provided in S11 Table in S1 File.

Fig 5 — (a) Post-intervention values. (b) Change from baseline. Abbreviations: BMI, body mass index; CL, Curcuma longa; DBP, diastolic blood pressure; DM, diabetic mellitus; FBG, fasting blood glucose; HbA1C, hemoglobin A1C; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; MetS, metabolic syndrome; NA, not applicable; pre-DM, pre-diabetic mellitus; SBP, systolic blood pressure; TC, total cholesterol; TG, triglyceride.

Fig 6 — (a) Post-intervention values. (b) Change from baseline. Abbreviations: BMI, body mass index; CL, Curcuma longa; DBP, diastolic blood pressure; DM, diabetic mellitus; FBG, fasting blood glucose; HbA1C, hemoglobin A1C; HDL-c, high-density lipoprotein cholesterol; LDL-c, low-density lipoprotein cholesterol; MetS, metabolic syndrome; NA, not applicable; pre-DM, pre-diabetic mellitus; SBP, systolic blood pressure; TC, total cholesterol; TG, triglyceride.

Sensitivity analyses and publication bias

Three sensitivity analyses were conducted: 1) analysis using the fixed effects model; 2) exclusion of trials with a high risk of bias; and 3) exclusion of small-sized studies (<25^th percentile). The results of these analyses remained consistent with those of the overall analysis (S12 Table in S1 File). Publication bias was assessed using funnel plots and Egger’s test for all outcomes. The funnel plots were symmetrical (S30–S42 Figs in S1 File) corresponding to the results of the Egger’s tests, suggesting no publication bias (S13 Table in S1 File), except for postintervention FBG and BMI outcomes.

Quality of evidence

The quality of direct evidence for all primary outcomes was generally rated moderate. The grade was decreased by inconsistency due to a large heterogeneity (large I²). More details on the quality of evidence are provided in S14 Table in S1 File.

Discussion

Our UR that include 14 SRMAs and an updated MA of RCTs indicated significant reductions due to CL supplementation in FBG and HbA1C of about 8 mg/dL and 0.134% to 0.517%, respectively. In addition, CL extract and bioavailability-enhanced preparations could significantly reduce both FBG and HbA1C.

CL has long been used in Eastern medicine for treating various diseases and symptoms and is one of the most studied medicinal plants on earth. The most recent scientific evidence suggests that CL exhibits various cellular actions that can mitigate diabetes [14]. In vitro studies have shown that CL increases insulin expression and secretion by activating the phosphatidylinositol-3-kinase/protein kinase B/glucose transporter 2 (PI3K/Akt/GLUT2) signaling pathway and upregulates insulin mRNA expression [73]. In mouse models, CL attenuated oxidative stress, dose-dependently reducing the apoptosis of pancreatic β-cells [74]. In hepatocytes and adipocytes, CL reduced glucose uptake by inhibiting the translocation of GLUT4 from the cytosol to the plasma membrane via the insulin receptor substance 1/PI3K/Akt signaling pathway [75]. In the gut, CL inhibited the enzymes involved in glucose digestion, i.e., α-amylase and α-glucosidase [76]. CL also stimulated the secretion of glucagon-like peptide-1, and incretins, which are a validated pathway of important classes of anti-diabetic drugs [77]. Notably, CL upregulated peroxisome proliferator-activated receptor-γ (PPAR-γ) expression in liver cells, thereby downregulating p65 nuclear factor kappa B, a protein complex central to the inflammation [78]. CL curcuminoids also inhibited advanced glycation end-products which are the key mediators associated with metabolic complications [76].

Three forms of CL preparation are most commonly used, namely, whole CL, CL extract and bioavailability-enhanced preparations. The different preparation forms may be administered with different types and doses of bioactive compounds [79]. Studies have shown that bioavailability-enhanced preparations, such as curcumin-phosphatidylcholine phytosome complex, curcumin micelles, water-soluble curcumin formulation containing, or colloidal nanoparticle formulation, increased the absorption of curcumin by 6.9–20.0 times compared with whole CL preparation [79]. Therefore, an assessment of the effects of different CL preparations on outcomes is imperative.

Results from both the UR and the updated MA suggest that CL preparations can reduce FBG and modest HbA1C. Interestingly, subgroup analysis showed that CL exhibited beneficial effects on glycemic management, especially in T2DM, pre-diabetes, MetS, and high SBP/DBP. Similar positive effect on glucose homeostasis had also been proved in nonalcoholic fatty liver disease [80]. Regardless of the preparations used, a dose-response relationship was observed, where higher doses of the same preparation elicited stronger effects. In addition, significant reductions in other metabolic parameters were observed, further confirming the potent effects of CL that may be expressed via multiple pathways.

Limitations and strengths

Our study has several limitations. First, the quality of SRMAs were all considered critically low. Second, some relevant outcomes (i.e., HOMA-IR, insulin, blood pressure, CRP) were reported in only a few studies. Hence, the effect sizes were not accurately estimated. Third, differences in bioactive compounds contained in various preparations may exist, which may affect the clinical effects. Such differences are due to varying qualities of the raw materials, extraction methods, and formulation techniques.

Conclusions

Our review revealed that CL supplementation can significantly reduce FBG and HbA1C levels in T2DM and mitigate related conditions, including prediabetes and MetS, after short-term use. The effects appear consistent regardless of the form of CL preparation used. A dose-response relationship is suggested in the findings, where higher doses of the same preparation elicited stronger responses. In addition, significant reductions in other metabolic parameters were observed. Further studies should be conducted to assess whether the effects on glycemic management can be sustained on a long-term basis and/or whether they can reduce the risk of diabetic complications.

Supporting information

S1 Checklist. PRISMA 2020 checklist.

(DOCX)

Click here for additional data file.^{(39.7KB, docx)}

S1 File

(ZIP)

Click here for additional data file.^{(3.5MB, zip)}

Abbreviations

CCA: corrected covered area
CL: Curcuma longa
CRP: C-reactive protein
FBG: fasting blood glucose
hs-CRP: high sensitivity C-reactive protein
MA: meta-analysis
SMD: standardized mean difference
SRMAs: systematic reviews and meta-analyses
TC: total cholesterol
TG: triglycerides
UMD: unstandardized mean difference
UR: umbrella review

Data Availability

All relevant data are within the manuscript and its supporting information files.

Funding Statement

This study was supported by the National Research Council of Thailand (N42A640323). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0288997.r001

Decision Letter 0

Mohamed Ezzat Abd El-Hack

11 Jan 2023

PONE-D-22-31206Effects of Curcuma longa supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysisPLOS ONE

Dear Dr. Jinatongthai,

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Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

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Reviewer #1: No

**********

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Reviewer #1: Yes

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Reviewer #1: This is a well designed, well written manuscript. Only, I recommend to discuss all related papers such as https://doi.org/10.1038/s41430-018-0382-9. Although some papers are on other disorders, they have measured similar blood values.

**********

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PLoS One. 2023 Jul 20;18(7):e0288997. doi: 10.1371/journal.pone.0288997.r002

Author response to Decision Letter 0

28 Jan 2023

Dear editor,

Thank you for your valuable recommendation and comments. We have checked and revised according to your comments. The revised manuscript and point-by-point responses to the additional requirements and reviewer’s comments files have been attached with this submission. We look forward to hearing from you soon.

Thank you for your consideration.

Sincerely,

PLoS One. doi: 10.1371/journal.pone.0288997.r003

Decision Letter 1

Mohammad Reza Mahmoodi

24 May 2023

PONE-D-22-31206R1

Effects of Curcuma longa supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis

PLOS ONE

Dear Dr. Jinatongthai,

Please submit your revised manuscript by Jul 08 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Mohammad Reza Mahmoodi, Ph.D.

Academic Editor

PLOS ONE

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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# Please make the minor editorial changes in wording suggested by the reviewer. After that, I am happy to accept the manuscript for publication.

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Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: All my comments are addressed. The manuscript can be accepted in its current format.

there is no added comments.

Reviewer #2: The current manuscript was an umbrella review that was designed and written well. The only minor flaw in this manuscript is the lack of an expansion discussion regarding the reasons and mechanisms of the effect of turmeric on reducing glycemic indices. Curcuma longa is a food additive most studied in the scientific domain.

Title:

1. Title change to Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis

Abstract:

2. Line 20: Curcuma longa convert to turmeric (Curcuma longa)

3. Lines 20 & 21: “its related compounds on glycemic” convert to “its related bioactive compounds on glycemic”

4. Line 22 and the remainder of abstract: CL convert to turmeric

5. Lines 22 & 23: “different CL preparation-forms” convert to “different CL preparation forms” OR “different CL preparations” (Conversion should be accomplished throughout the text of the manuscript)

6. Line 26 & 27: As the authors know, Scopus and Web of Science are big databases. Why did the authors not use these databases? The number of articles on a topic may be 3-4 times more in Scopus database than PubMed database.

Introduction:

7. Line 73. CL preparation forms convert to turmeric (CL) preparation forms

8. Line 79. “the effects of curcumin and its related compounds on glycemic” converted to “the effects of turmeric preparations and its related bioactive compounds on glycemic”

Methods:

9. In flowchart (Fig 1), the authors identified that 1750 abstracts were extracted from Scopus database. Why this database didn’t mention in the abstract together the other databases?

Types of interventions

10. Line 115: “curcuminoid standardized extract” convert to “standardized curcuminoid extract”

11. Please kindly correct S1 Table to Table S1, S2 Table to Table S2, etc. throughout the manuscript text.

Outcomes of interest

12. According to NCEP ATP III, MetS was identified based on five criteria. Among five criteria, there aren’t serum uric acid and hsCRP. The authors describe, why these biomarkers selected for MetS outcomes.

Data synthesis and statistical analysis

13. Line 161: “lipid profiles” modify to “lipoprotein profiles”

Results:

14. As I noted in comment 11, all “S1, 2, 3, ……. Table” modify to “Table S1, 2, 3, …….” In the manuscript text.

15. The authors should be modified “S1, 2, 3, …… Fig” to “Fig S1, 2, 3, ……” throughout in manuscript text similar to Tables.

Table 1:

16. BMI is abbreviate body mass index not bone mass index. Modify it in footnote of Table 1.

17. Would you please review Huang [19] study rows for biomarkers in table 1? Is there any inconsistency in recorded data in table 1?

Figs:

18. Did the professor Ammarin Thakkinstian perform all the meta-analyses of this study?

19. Line 321: “bone mass index” modify to “body mass index” in Abbreviation of Fig 6.

20. Line 332: “S30–S42 Figs” modify to “Figs S30-S42”. The other Tables and Figs should be corrected.

21. Lines 367-368: What are “bioavailability-enhanced preparations” in the other studies? Modify to “bioavailability-enhanced preparations such as ………….”

22. The last paragraph of the discussion section should be separated under “Limitations and Strengths”.

23. As the authors converted Type 2 diabetes mellitus to T2DM, metabolic syndrome modify to MetS in throughout the manuscript text.

24. Which of the tables or figures in the supporting information section are more important to appear in the manuscript? Or to remain in the supporting information section?

Congratulations

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

PLoS One. 2023 Jul 20;18(7):e0288997. doi: 10.1371/journal.pone.0288997.r004

Author response to Decision Letter 1

6 Jun 2023

Comment #1 Title change to Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis.

Response #1 The title was changed as the reviewer recommended.

Lines 1–2,

Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis

Comment #2 Line 20: Curcuma longa convert to turmeric (Curcuma longa)

Response #2 The common name was added as recommended.

Line 20,

“…(RCTs) of turmeric (Curcuma longa, CL) and its related bioactive compounds…”

Comment #3 Lines 20 & 21: "its related compounds on glycemic" convert to "its related bioactive compounds on glycemic"

Response #3 The sentence was changed as the reviewer recommended.

Line 20–21,

“…and its related bioactive compounds on glycemic…”

Comment #4 Line 22 and the remainder of abstract: CL convert to turmeric

Response #4 We appreciate your advice. We acknowledge turmeric is a well-known common name of Curcuma longa L. However, using the turmeric term could mislead many plants, such as, C. inodora Blatt., C. pseudomontana J.Graham, C. caulina J.Graham, C. roscoeana Wall., and Zingiber officinale Roscoe [1]. Therefore, to prevent common taxonomical errors [2], we agree to preserve Curcuma longa and its abbreviation, CL, according to the original manuscript.

References:

1. POWO (2023). "Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Published on the Internet; https://powo.science.kew.org/results?q=turmeric. Retrieved 30 May 2023.

2. Bennett, B. C., & Balick, M. J. (2014). Does the name really matter? The importance of botanical nomenclature and plant taxonomy in biomedical research. Journal of Ethnopharmacology, 152(3), 387–392.

Comment #5 Lines 22 & 23: "different CL preparation-forms" convert to "different CL preparation forms" OR "different CL preparations" (Conversion should be accomplished throughout the text of the manuscript)

Response #5 The words have changed as reviewer recommended from “CL preparation-forms” to “CL preparation forms” and checked throughout the manuscript.

Comment #6 Line 26 & 27: As the authors know, Scopus and Web of Science are big databases. Why did the authors not use these databases? The number of articles on a topic may be 3-4 times more in Scopus database than PubMed database.

Response #6 We apologize for the typographical error. Scopus was one of the included databases according to our protocol. The abstract was revised and corrected.

Lines 26–27,

“…The MEDLINE, Embase, The Cochrane Central Register of Control Trials, and Scopus databases were searched…”

Comment #7 Line 73. CL preparation forms convert to turmeric (CL) preparation forms

Response #7 Please refer to the response to reviewer comments #4.

Comment #8 Line 79. "the effects of curcumin and its related compounds on glycemic" converted to "the effects of turmeric preparations and its related bioactive compounds on glycemic"

Response #8 Line 79,

“…curcumin and its related bioactive compounds on glycemic…”

Comment #9 In flowchart (Fig 1), the authors identified that 1750 abstracts were extracted from Scopus database. Why this database didn't mention in the abstract together the other databases?

Response #9 The Scopus database was included in the systematic searching according to our study protocol. We followed the advice by correcting the abstract.

Line 26-27,

“…The MEDLINE, Embase, The Cochrane Central Register of Control Trials, and Scopus databases…”

Comment #10 Line 115: "curcuminoid standardized extract" convert to "standardized curcuminoid extract"

Response #10 Line 115,

“…e.g., a standardized curcuminoid extract; and 3)…”

Comment #11 Please kindly correct S1 Table to Table S1, S2 Table to Table S2, etc. throughout the manuscript text.

Response #11 We followed the advice of the reviewer’s comments by correcting the label of supplementary table throughout the manuscript.

Comment #12 According to NCEP ATP 111, Mets was identified based on five criteria. Among five criteria, there aren't serum uric acid and hsCRP. The authors describe, why these biomarkers selected for Mets outcomes.

Response #12 We followed our study protocol. Although the exact mechanism has not yet been clarified., several evidence implied that an elevation of serum uric, C-reactive protein (CRP) and high sensitivity C-reactive protein (hs-CRP) are associated with an increased risk of developing metabolic syndrome components, such as hypertension, insulin resistance, and dyslipidemia [1-3]. With a certain number of published evidence and none of the previous SRMAs have been investigated related to these markers, therefore we included them as one of outcomes of interest to provide the most up-to-date and comprehensive evidence. We added more details to acknowledge this comment as below.

References:

1. López-Olivo MA, et al. Serum uric acid as a predictor of incident metabolic syndrome: a secondary analysis of a longitudinal cohort study. Arthritis Care Res. 2013;65(12):2026-2031.

2. Kanbay M, et al. Uric acid and metabolic syndrome: lessons from a large, multicenter study. PLoS ONE. 2018;13(3):e0194125.

3. Lin SD, et al. Hyperuricemia and metabolic syndrome: associations with endothelial dysfunction. Am J Med Sci. 2010;339(3):233-239.

Data synthesis and statistical analysis

Comment #13 Line 161: "lipid profiles" modify to "lipoprotein profiles"

Response #13 We followed our study protocol. A lipid profile typically includes measurements of total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides,which are the common markers used in a routine clinical practice and also general clinical research. Whereas the term “lipoprotein profiles” may refer to subclasses of lipoproteins, such as, LDL particles (including small, dense LDL), very low-density lipoprotein (VLDL) particles, and HDL subclasses. To provide the clinical aspects for the readers, we agreed to preserve the term “lipid profiles” according to the original manuscript.

Comment #14 As I noted in comment 11, all "S1, 2, 3, ....... Table" modify to "Table S1, 2, 3, ....... " In the manuscript text

Response #14 The words were changed as reviewer recommended and checked throughout the manuscript.

Comment #15 The authors should be modified "S1, 2, 3, ...... Fig" to "Fig S1, 2, 3, ...... " throughout in manuscript text similar to Tables.

Response #15 The words were changed as reviewer recommended and checked throughout the manuscript.

Comment #16 BMI is abbreviate body mass index not bone mass index. Modify it in footnote of Table 1.

Response #16 We apologize for the typographical error. The word was corrected and checked throughout the manuscript.

Lines 223 and 310,

“Abbreviations: BMI, body mass index;…”

Comment #17 Would you please review Huang [19] study rows for biomarkers in table 1? Is there any inconsistency in recorded data in table 1?

Response #17 We have rechecked all the records. All reported data is correct. The number of reported outcomes may difference within its original study because of the difference in number of subpopulations reported for each outcome.

Comment #18 Did the professor Ammarin Thakkinstian perform all the meta-analyses of this study?

Response #18 We added more details about the author’s responsibility for “Data synthesis and statistical analysis” as described below. We also corrected the method on STATA program and the citation error as below.

Lines 162-166,

“All analyses were performed by P.J., T.P., and W.R. using STATA® version 17.0 (StataCorp, College Station, Texas, USA) along with the self-programmed STATA® for meta-analysis described elsewhere[32]. A.T. and S.N. provided technical analysis advice. A p-value ≤ 0.05 was considered statistically significant.”

Line 513

32. Palmer TM, Sterne JAC. Meta-analysis in Stata: An Updated Collection from the Stata Journal: Stata Press; 2016.

Comment #19 Line 321: "bone mass index" modify to "body mass index" in Abbreviation of Fig 6.

Response #19 We apologize for the typographical error. The word was corrected.

Line 318,

“Abbreviations: BMI, body mass index;…”

Comment #20 Line 332: "S30-S42 Figs" modify to "Figs S30-S42". The other Tables and Figs should be corrected.

Response #20 The words were changed as reviewer recommended and checked throughout the manuscript.

Comment #21 Lines 367-368: What are "bioavailability-enhanced preparations" in the other studies? Modify to "bioavailability-enhanced preparations such as

Response #21 We followed the advice of the reviewer’s comments by adding the details to explain about the preparation.

Lines 365–367,

“…bioavailability-enhanced preparations, such as curcumin-phosphatidylcholine phytosome

complex, curcumin micelles, water-soluble curcumin formulation containing, or colloidal nanoparticle formulation, increased the absorption…”

Comment #22 The last paragraph of the discussion section should be separated under "Limitations and Strengths".

Response #22 The last paragraph was separated as recommended.

Line 378,

“Limitations and Strengths

Our study has several limitations. First,…”

Comment #23 As the authors converted Type 2 diabetes mellitus to T2DM, metabolic syndrome modify to Mets in throughout the manuscript text.

Response #23 The metabolic syndrome was converted to MetS throughout the manuscript.

Comment #24 Which of the tables or figures in the supporting information section are more important to appear in the manuscript? Or to remain in the supporting information section?

Response #24 We have reviewed throughout the manuscript. All major results with graphic have been reported in main manuscript.

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PLoS One. doi: 10.1371/journal.pone.0288997.r005

Decision Letter 2

Mohammad Reza Mahmoodi

15 Jun 2023

PONE-D-22-31206R2

Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis.

PLOS ONE

Dear Dr. Jinatongthai,

As the authors know, the publication a manuscript depends on satisfaction of the reviewers of a manuscript. I am sure that these minor changes will also be applied in the manuscript and the dear authors' article will reach the publication process.

Please submit your revised manuscript by Jul 30 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

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Kind regards,

Mohammad Reza Mahmoodi, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: Some comments were not accomplished. The authors should be modified the manuscript based on the following comments that did not modified.

8. Line 79. “the effects of curcumin and its related compounds on glycemic” converted to “the effects of turmeric preparations and its related bioactive compounds on glycemic”

12. “Outcomes related to MetS were also collected …” should be modified to “The other selected outcomes were also collected …”

Based on the response to comment 21, comment 12 should be modified! On the other hand, unfortunately, the authors did not understand my comment (number 12). Some biomarkers were measured for participants took part in a study either might exaggerated some main biomarkers and patients outcome Or they are measured according to the wishes of the authors. Therefore, authors should be subject to the reviewer's comments. If the authors want measure association metabolic syndrome with C-peptide; we can assume that this indicator is one of the main indicators of metabolic syndrome? Such an assumption is completely wrong. Researchers can measure the correlation/association/relationship of a biomarker or an outcome in a disease based on a strong implementation necessity, but they cannot relate that biomarker as a main indicator to that disease.

13. The authors mentioned that they followed the study protocol. This explanation was rejected. If a phrase or phrases was/were wrong, we could not compliance with it/them. Hence, the phrases should be modified to “lipid and lipoprotein profile”.

17. I am not convinced.

19. Bone mass index (BMI) was not a typographical error. It was a wrong compliance.

24. The authors didn't understand what I meant. I mean, which of the tables and figures in the appendix section should be added to the text of the main manuscript?

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

**********

PLoS One. 2023 Jul 20;18(7):e0288997. doi: 10.1371/journal.pone.0288997.r006

Author response to Decision Letter 2

4 Jul 2023

#8 “the effects of curcumin and its related compounds on glycemic” converted to “the effects of turmeric preparations and its related bioactive compounds on glycemic”

We followed the advice of the reviewer’s comments by modifying the following sentences.

Line 79,

“…the effects of turmeric preparations and its related bioactive compounds on glycemic…”

#12 “Outcomes related to MetS were also collected …” should be modified to “The other selected outcomes were also collected …”

We followed the advice of the reviewer’s comments by modifying the following sentences.

Line 126,

“…The other selected outcomes were also collected including…”

#13 The authors mentioned that they followed the study protocol. This explanation was rejected. If a phrase or phrases was/were wrong, we could not compliance with it/them. Hence, the phrases should be modified to “lipid and lipoprotein profile”.

We followed the advice of the reviewer’s comments by modifying the following sentences.

Line 160,

“…baseline characteristics of patients (including mean body mass index [BMI], lipid and lipoprotein profiles, blood pressure…”

#17 I am not convinced.

Would you please review Huang [19] study rows for biomarkers in table 1? Is there any inconsistency in recorded data in table 1?

We have gone through this paper and have changed numbers to be consistent with the original paper. Please accept our sincere apology for our mistake.

#19 Bone mass index (BMI) was not a typographical error. It was a wrong compliance.

We apologize for our inaccurate explanation of our response. It was a wrong compliance. The manuscript has been corrected according to the reviewer’s comments.

#24 The authors didn't understand what I meant. I mean, which of the tables and figures in the appendix section should be added to the text of the main manuscript?

After careful consideration, we believe that the information included in the main manuscript is sufficient to maintain concise and focused data according to the objective of study. We also cited in the main manuscript to refer related additional information to the supplementary.

In case you feel that we still do not fully understand your question well enough, we kindly request you to clearly specify those details. We will thoroughly review your suggestions and make necessary revisions accordingly. Thank you.

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PLoS One. doi: 10.1371/journal.pone.0288997.r007

Decision Letter 3

Mohammad Reza Mahmoodi

10 Jul 2023

Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis.

PONE-D-22-31206R3

Dear Dr. Jinatongthai,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Mohammad Reza Mahmoodi, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

**********

PLoS One. doi: 10.1371/journal.pone.0288997.r008

Acceptance letter

Mohammad Reza Mahmoodi

13 Jul 2023

PONE-D-22-31206R3

Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: an umbrella review and updated meta-analysis.

Dear Dr. Jinatongthai:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Mohammad Reza Mahmoodi

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. PRISMA 2020 checklist.

(DOCX)

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S1 File

(ZIP)

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Data Availability Statement

All relevant data are within the manuscript and its supporting information files.

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PERMALINK

Effects of turmeric (Curcuma longa) supplementation on glucose metabolism in diabetes mellitus and metabolic syndrome: An umbrella review and updated meta-analysis

Thanika Pathomwichaiwat

Peerawat Jinatongthai

Napattaoon Prommasut

Kanyarat Ampornwong

Wipharak Rattanavipanon

Surakit Nathisuwan

Ammarin Thakkinstian

Roles

Abstract

Aims

Methods

Results

Conclusion

Trial registration

Introduction

Methods

Study design

Search strategy

Fig 1. Flow diagram of included studies in umbrella review.

Fig 2. Flow diagram of included studies in updated meta-analysis.

Study selection

Types of interventions

Outcomes of interest

Data extraction and quality assessment

Quality of evidence

Data synthesis and statistical analysis

Results

Umbrella review

Identification and selection of SRMAs and individual RCTs

Description of SRMAs

Quality of SRMAs

Degree of overlap in SRMAs

Primary efficacy outcomes

Table 1. Difference of post-intervention values and change from baseline for glycemic and metabolic outcomes between Curcuma longa (CL) supplementation and control group from previous SRMAs.

Secondary efficacy outcomes

Updated meta-analysis

Baseline characteristics

CL preparation forms and outcomes

Risk of bias of included RCTs

Primary efficacy outcomes

Fig 3. Forest plot of the differences of fasting blood glucose (mg/dL) within 4 months between Curcuma longa (CL) supplementation and control group.

Fig 4. Forest plot of the differences of hemoglobin A1C (%) within 4 months between Curcuma longa (CL) supplementation and control group.

Secondary efficacy outcomes

Subgroup analyses

Fig 5. Subgroup analysis of difference of fasting blood glucose (mg/dL) within 4 months between Curcuma longa (CL) supplementation and control group.

Fig 6. Forest plot of subgroup analysis of difference in change of hemoglobin A1C (%) within 4 months between Curcuma longa (CL) supplementation and control group.

Sensitivity analyses and publication bias

Quality of evidence

Discussion

Limitations and strengths

Conclusions

Supporting information

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Mohamed Ezzat Abd El-Hack

Roles

Author response to Decision Letter 0

Decision Letter 1

Mohammad Reza Mahmoodi

Roles

Author response to Decision Letter 1

Decision Letter 2

Mohammad Reza Mahmoodi

Roles

Author response to Decision Letter 2

Decision Letter 3

Mohammad Reza Mahmoodi

Roles

Acceptance letter

Mohammad Reza Mahmoodi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS