Impacts of Curcumin Supplementation on Cardiometabolic Risk Factors in Patients With Polycystic Ovary Syndrome: A Systematic Review and Dose−Response Meta‐Analysis

ABSTRACT

Background and Aim

Patients with polycystic ovary syndrome (PCOS) commonly have cardiometabolic risk factors. Oxidative stress (OS) significantly contributes to the development of cardiometabolic diseases. Curcumin (CUR) exhibits antioxidant properties that aid in OS regulation. This systematic review and dose–response meta‐analysis of randomized clinical trials (RCTs) evaluated the effects of CUR supplementation on cardiometabolic risk factors in women with PCOS.

Methods

A systematic search across various databases was implemented to identify eligible RCTs published until January 2024. A meta‐analysis was conducted employing a random‐effects model.

Results

Eight RCTs were included in the meta‐analysis. It was indicated that CUR supplementation substantially reduced fasting blood sugar (FBS) (standardized mean difference [SMD]: −0.40 mg/dL, 95% confidence interval [CI]: −0.59, −0.21; p < 0.001), insulin (SMD: −0.32 µU/mL, 95% CI: −0.49, −0.14; p < 0.001), homeostasis model assessment of insulin resistance (HOMA‐IR) (SMD: −0.36, 95% CI: −0.54, −0.19; p < 0.001), and total cholesterol (TC) (SMD: −0.34 mg/dL, 95% CI: −0.61, −0.08; p = 0.01). In addition, it substantially increased the quantitative insulin sensitivity check index (QUICKI) (SMD: 0.37, 95% CI: 0.13, 0.61; p < 0.001) in the CUR‐treated group compared with the control group. However, CUR did not have significant impacts on body mass index (BMI), body weight, serum levels of follicle‐stimulating hormone (FSH), triglycerides (TG), dehydroepiandrosterone (DHEA), high‐density lipoprotein (HDL), testosterone, low‐density lipoprotein (LDL), and luteinizing hormone (LH).

Conclusion

This study revealed that CUR may have the potential to enhance cardiometabolic health by reducing hyperglycemia, insulin resistance, and serum TC levels in women with PCOS.

1. Introduction

Cardiometabolic syndrome (CMS) or insulin resistance syndrome, or metabolic syndrome (MetS) is a complex of metabolic abnormalities [1, 2]. Several cardiovascular risk factors (at least three) are present in this condition, including abdominal obesity, hypertension (HTN), dyslipidemia, impaired glucose tolerance, and insulin resistance (IR) [3, 4]. Polycystic ovarian syndrome (PCOS) and MetS are interrelated conditions that significantly affect reproductive health [5, 6]. The estimated prevalence of MetS in patients with PCOS is around 30% [7]. PCOS is the most prevalent metabolic disorder in women of reproductive age [8, 9]. PCOS is multifaceted, impacting various bodily systems and manifesting as irregular ovulation, hyperandrogenism, hirsutism, the presence of polycystic ovaries, infertility [10, 11], and metabolic issues (e.g., IR, dyslipidemia, and hyperglycemia) [12].

IR is an underlying pathological process associated with the onset of MetS in women with PCOS [13]. In these patients, elevated insulin levels are considered a compensatory response linked to hyperandrogenism [14, 15]. In addition, women with PCOS often experience overweight and obesity which are significantly associated with hyperglycemia and IR [16, 17]. Patients with PCOS and MetS have increased susceptibility to cardiovascular diseases (CVDs) [5]. Furthermore, MetS is correlated with elevated levels of inflammatory markers and oxidative stress (OS) [18]. Inflammation may contribute to the development of MetS and its complications [19]. Nutritional and dietary habits are expected to substantially affect health outcomes and metabolic disease management [20, 21]. Antioxidant therapy has shown promise in preventing MetS [22] and obesity‐associated comorbidities [23]. It is essential to emphasize the reduction of OS and inflammation as therapeutic objectives in treating and preventing MetS and its complications [24, 25]. Nutrition is critical in mitigating OS and low‐grade inflammation [26]. Dietary antioxidants and polyphenols found in fruits and vegetables act as effective scavengers of free radicals [27, 28, 29, 30, 31].

Turmeric (Curcuma longa Linn.) is a spice with a rich historical background in traditional usage, primarily valued for its color and flavor‐enhancing properties across various applications [32] as well as its medicinal benefits [33, 34, 35]. Curcumin (CUR), a bioactive polyphenol, is the principal constituent of turmeric [36, 37, 38]. It was indicated that the administration of CUR in whole turmeric powder exhibits higher bioavailability than when it is administered in isolation [39]. This phenomenon suggests a synergistic effect between the various components present in turmeric and CUR [39]. There has been a substantial increase in the utilization of CUR in recent years, attributed to its diverse biological, pharmacological, and beneficial effects [40, 41]. CUR exhibits promising therapeutic potential, offering a wide range of healing and preventive effects against various diseases [42, 43, 44, 45, 46, 47, 48, 49, 50, 51]. It exhibits anti‐inflammatory [52], antioxidant, and radical scavenging properties [53, 54, 55]. Furthermore, CUR demonstrates various pharmaceutical activities, including antidiabetic [56, 57], anti‐hyperlipidemia [58], anti‐atherogenic [59], hepatoprotective [60, 61, 62], anti‐carcinogenic [63], and neuroprotective [64] effects.

Several studies have reported positive effects of CUR on OS [65], endothelial function [66], and inflammation [67], all of which are implicated in CVDs [68]. The beneficial effects of CUR in enhancing IR [69], glycemic indices [70], lipid profiles [71], and anthropometric parameters [72] have also been documented. It was indicated that CUR can improve insulin sensitivity by positively influencing glucose homeostasis, beta‐cell activity, and insulin secretion in diabetic patients [73, 74]. Recently, the advantages of CUR in regulating glycemic parameters have prompted researchers to further investigate its effects on glycemic and metabolic parameters [75, 76, 77]. However, existing data on the effectiveness of CUR administration in managing CMS risk factors in patients with PCOS are limited, inconclusive, and controversial [78, 79, 80, 81]. Therefore, this systematic review and meta‐analysis of randomized controlled trials (RCTs) intended to investigate the impact of CUR supplementation on cardiometabolic risk factors in women with PCOS.

2. Materials and Methods

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‐Analyses) guidelines were utilized for the present systematic review and meta‐analysis [82]. The study protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO) (registration no. CRD42024529987).

2.1. Search Strategy

A systematic search was implemented to identify eligible RCTs published until January 2024 in various databases (PubMed or MEDLINE and Web of Science Scopus) with no restrictions on date or language. The search strategy was organized into four principal components relevant to the RCTs (Supporting Information S1: Table S1). These components included the target population (women with PCOS), intervention or exposure (CUR supplements), comparator or control group (placebo or no intervention), and defined outcomes. The outcomes included anthropometric parameters (body weight and body mass index [BMI]), glycemic profile (fasting blood sugar [FBS], quantitative insulin sensitivity check index [QUICKI], insulin levels, and homeostasis model assessment of insulin resistance [HOMA‐IR]), lipid profiles (high‐density lipoprotein [HDL] cholesterol, triglycerides [TG], low‐density lipoprotein [LDL] cholesterol, and total cholesterol [TC]), and hormone levels (luteinizing hormone [LH], follicle‐stimulating hormone [FSH], testosterone, and dehydroepiandrosterone [DHEA]).

The search strategy encompassed the following Medical Subject Headings (MeSH) and non‐MeSH terms: (“Curcuma” OR “Curcuminoid” OR “Zedoary” OR “zedoaria” OR “Longa” OR “Curcuma longa”) AND (“fasting blood sugar” OR “FBS” OR “Insulin” OR “Lipid Profile” OR “triglycerides” OR “total cholesterol” OR “TC” OR “TG” OR “HDL” OR “body mass index” OR “LDL” OR “body weight” OR “Homeostatic Model Assessment for Insulin Resistance” OR “HOMA‐IR” OR “BMI” OR “quantitative insulin sensitivity check index” OR “QUICKI” OR “high‐density lipoprotein” OR “low‐density lipoprotein” OR “testosterone” OR “DHEA” OR “dehydroepiandrosterone” OR “FSH” OR “LH” OR “follicle‐stimulating hormone” OR “luteinizing hormone”) AND (“Polycystic Ovary Syndrome” OR “PCOS” OR “Polycystic ovary disease” OR “Stein Leventhal Syndrome” OR “Sclerocystic Ovarian Degeneration” OR “Sclerocystic Ovary Syndrome Study”).

2.2. Selection Criteria

EndNote reference management software was utilized to export the records. Two researchers (S.M. and J.H.) independently evaluated the trials and eligible RCTs were selected according to the inclusion criteria. Discrepancies were resolved after discussion with a third researcher. The RCTs in this study involved women with PCOS and had a placebo or a control group. These trials had a minimum duration of 2 weeks and employed a pre−post design. Furthermore, the RCTs included in the analysis provided comprehensive data on the measured outcomes for both the CUR treatment and placebo groups at the beginning and end of each trial. This meta‐analysis intended to evaluate the impacts of CUR supplementation on cardiometabolic parameters in patients with PCOS. Trials were excluded based on specific criteria, such as the absence of control or placebo groups, a trial duration of less than 2 weeks, the inclusion of pregnant or lactating women, non‐RCTs, observational studies, and trials with inadequate data on the specified outcomes at baseline and follow‐up evaluations.

2.3. Data Extraction

Two researchers (S.M. and J.H.) independently extracted data from selected full‐text articles. Any discrepancies that emerged were resolved by discussion. The extracted data were various study characteristics, such as the primary author's name, sample size, trial duration and setting, dosage of CUR supplements, and publication year. In addition, demographic information about the participants (average age, BMI, and sex) was collected. Furthermore, assessments of specific outcomes (body weight, BMI, and values of insulin, FBS, HOMA‐IR, QUICKI, TC, HDL, TG, LDL, testosterone, DHEA, FSH, and LH) were conducted at the beginning and end of the RCTs.

2.4. Risk of Bias Evaluation

Two independent reviewers (S.M. and J.H.) evaluated the quality of the study using the adapted Cochrane Risk of Bias (RoB2) tool [83]. Several sources of bias were evaluated, including attrition, reporting, detection, allocation, and performance biases. The risk of bias within each domain was classified as unclear, low, or high [83].

2.5. Certainty Assessment

The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology was used to assess the certainty of evidence. The quality of evidence was categorized into four levels: low, moderate, high, and very low [84].

2.6. Statistical Analysis

This meta‐analysis employed the STATA statistical software (version 17). The analysis involved the evaluation of standardized mean differences (SMDs) and 95% confidence intervals (CIs) to determine the overall changes in the study outcomes from baseline to the conclusion of the study in both the CUR‐treated and control groups. SMDs enable the synthesis of results from diverse studies by standardizing the effect size, rendering it unit‐free, and facilitating comparisons. A random‐effects model was utilized to compute pooled SMDs [85]. Heterogeneity between trials was evaluated using the I² statistic [86] and Cochran's Q test. The I² values indicated different degrees of heterogeneity across trials, which were classified as moderate (25%−50%), low (< 25%), and high (> 50%) [87].

Subgroup analyses were applied to find any sources of heterogeneity among the RCTs in the meta‐analysis. These analyses were stratified based on trial duration (≥ 10 vs. < 10 weeks) and type of supplementation (CUR vs. high‐bioavailable CUR). Leave‐one‐out sensitivity analysis was employed to assess the effect of each study on the overall outcomes. Furthermore, funnel plots, along with Begg's [88] and Egger's [89] tests, were utilized to identify publication bias. A meta‐regression analysis was implemented to investigate the association between CUR dosage, trial duration, and effect sizes to investigate potential linear relationships among these variables [90]. A fractional polynomial model was applied to display the potential nonlinear relationships between trial duration (weeks), CUR dosage (mg/day), and changes in outcomes. In addition, a two‐tailed p‐value of less than 0.05 was deemed to be statistically significant.

3. Results

3.1. Studies Selection

Figure 1 presents a flow diagram illustrating the screening and selection process for the RCTs. The initial search yielded 154 relevant entries in several databases. Subsequently, 58 duplicate entries were removed and an additional 86 studies were excluded after a comprehensive review of their abstracts and titles. Furthermore, 10 full‐text articles were evaluated, and two studies were excluded because they contained unrelated outcomes. Ultimately, the meta‐analysis included eight RCTs [75, 76, 77, 91, 92, 93, 94, 95] that met the inclusion criteria.

Figure 1.

Flow diagram of study selection.

3.2. Study Characteristics

Eight trials [75, 76, 77, 91, 92, 93, 94, 95] that enrolled 54 women with PCOS were identified for this systematic review and meta‐analysis. Table 1 displays the characteristics of the trials. These articles were published between 2019 and 2023. The length of the interventions varied from 6 to 24 weeks, and the total number of participants ranged from 30 to 104 women with PCOS. The mean BMI of the participants was between 19 and 36 kg/m², and their ages ranged from 21 to 39 years. These trials were conducted in Iran [75, 76, 77, 92, 93], Turkey [91], and China [94, 95]. The daily dosage of CUR supplementation was between 90 and 1500 mg.

Table 1.

Characteristics of included studies in the meta‐analysis.

Author, year	Country	Sample size	Cur (mg/day)	Trial duration (weeks)	Mean age (years)		Mean BMI (kg/m2)
					IG	CG	IG	CG
Asan et al. 2020 [91]	Turkey	30	93.34	8	27.6 ± 3.6	28.3 ± 5.9	29.8 ± 6.3	30.9 ± 4.6
Heshmati et al. 2020 [76]	Iran	72	1500	12	30.9 ± 5.2	30.7 ± 7.9	28.7 ± 4.9	27.2 ± 4.8
Jamilian et al. 2020 [75]	Iran	60	500	12	28.6 ± 4.7	27.2 ± 3.4	27.4 ± 3.9	26.4 ± 3.8
Sohaei et al. 2019 [77]	Iran	60	1000	6	29.4 ± 5.3	29.5 ± 5	29.6 ± 3.7	31.3 ± 4.6
Ghanbarzadeh‐Ghashti et al. 2023 [92]	Iran	60	500	12	28.4 ± 7.6	30.8 ± 8.6	27.3 ± 5.4	26.4 ± 4.2
Sohrevardi et al. 2021 [93]	Iran	100	160	12	29.0 ± 2.0	28.8 ± 2.46	27.2 ± 2.2	27.0 ± 1.6
Wu et al. 2020 [94]	China	60	90	12	26.1 ± 4.9	25.6 ± 5.0	24.4 ± 4.8	24.6 ± 5.8
Wu et al. 2022 [95]	China	104	90	24	27.1 ± 4.9	27.1 ± 4.8	24.6 ± 3.8	25.3 ± 5.8

Abbreviations: BMI, body mass index; CG, control group; Cur, curcumin; IG, intervention group.

3.3. Impact of CUR Supplementation on Anthropometric Parameters

3.3.1. Body Weight

The meta‐analysis of three trials [77, 91, 93] with 190 participants did not determine any considerable differences in body weight between the CUR‐treated group and the placebo group (SMD: −0.03 kg, 95% CI: −0.32, 0.26; p = 0.85) (Figure 2A).

Figure 2.

Impacts of curcumin supplementation on anthropometric parameters in patients with PCOS: (A) body weight and (B) BMI.

3.3.2. BMI

Seven studies [75, 76, 77, 91, 93, 94, 95] with 486 participants investigated the impact of CUR supplementation on BMI. The pooled data analysis indicated no significant changes in the BMI of women with PCOS after CUR administration (SMD: −0.11 kg/m², 95% CI: −0.29, 0.08; p = 0.25) (Figure 2B).

3.4. Impact of CUR on Glycemic Parameters

3.4.1. FBS

The pooled analysis of eight RCTs [75, 76, 77, 91, 92, 93, 94, 95], which included 546 participants, demonstrated that CUR supplementation significantly reduced serum FBS levels in the CUR group (SMD: −0.40 mg/dL, 95% CI: −0.59, −0.21; p < 0.001) compared to the untreated group (Figure 3A). Subgroup analysis indicated similar outcomes associated with long‐term supplementation (≥ 10 weeks) using both CUR and high‐bioavailable CUR supplements (Table 2).

Figure 3.

Impacts of curcumin supplementation on glycemic parameters in patients with PCOS: (A) FBS, (B) insulin, (C) HOMA‐IR, and (D) QUICKI.

Table 2.

Subgroup analyses of the effects of supplementation with CUR on cardiometabolic risk factors in patients with PCOS.

Sub‐groups	Number of effect sizes	SMD (95% CI)	Heterogeneity
			I 2 (%)	p value heterogeneity
Impacts of CUR on BMI (kg/m2)
Overall effect	7	−0.11 (−0.29, 0.08)	00.00	0.990
Cur type
Cur	3	−0.06 (−0.36, 0.23)	00.00	0.900
High bioavailable cur	4	−0.14 (−0.37, 0.10)	00.00	0.920
Trial duration (weeks)
< 10	2	−0.01 (−0.41, 0.44)	00.00	0.960
≥ 10	5	−0.14 (−0.34, 0.07)	00.00	0.980
Impacts of CUR on FBS (mg/dL)
Overall effect	8	−0.40 (−0.59, −0.21) a	12.42	0.330
Cur type
Cur	4	−0.47 (−0.73, −0.20) a	00.00	0.480
High bioavailable cur	4	−0.35 (−0.66, −0.03) a	39.91	0.170
Trial duration (weeks)
< 10	2	−0.45 (−1.04, 0.14)	42.47	0.190
≥ 10	6	−0.39 (−0.61, −0.18) a	19.95	0.280
Impacts of CUR on Insulin (µU/mL)
Overall effect	8	−0.32 (−0.49, −0.14) a	00.00	0.970
Cur type
Cur	4	−0.33 (−0.60, −0.07) a	00.00	0.910
High bioavailable cur	4	−0.30 (−0.53, −0.07) a	00.00	0.740
Trial duration (weeks)
< 10	2	−0.41 (−0.85, 0.02)	00.00	0.580
≥ 10	6	−0.30 (−0.49, −0.11) a	00.00	0.940
Impacts of CUR on HOMA‐IR
Overall effect	8	−0.36 (−0.54, −0.19) a	0.00	0.970
Cur type
Cur	4	−0.38 (−0.64, −0.11) a	00.00	0.910
High bioavailable cur	4	−0.35 (−0.58, −0.11) a	00.00	0.740
Trial duration (weeks)
< 10	2	−0.42 (−0.85, 0.02)	00.00	0.520
≥ 10	6	−0.35 (‐0.54, −0.16) a	00.00	0.930
Impacts of CUR on TC (mg/dL)
Overall effect	6	−0.34 (−0.61, −0.08) a	34.84	0.180
Cur type
Cur	3	−0.24 (−0.55, 0.07)	00.00	0.580
High bioavailable cur	3	−0.40 (−0.90, 0.09)	62.46	0.070
Trial duration (weeks)
< 10	2	−0.09 (−0.52, 0.34)	00.00	0.760
≥ 10	4	−0.44 (−0.77, −0.10) a	44.57	0.140
Impacts of CUR on TG (mg/dL)
Overall effect	6	−0.68 (−1.75, 0.39) a	95.26	< 0.001
Cur type
Cur	3	0.00 (−0.41, 0.42)	43.45	0.170
High bioavailable cur	3	−1.38 (−3.53, 0.77)	97.33	< 0.001
Trial duration (weeks)
< 10	2	−0.23 (−0.66, 0.20)	00.00	0.900
≥ 10	4	−0.91 (−2.52, 0.71)	97.07	< 0.001
Impacts of CUR on HDL (mg/dL)
Overall effect	6	0.47 (−0.09, 1.03)	84.37	< 0.001
Cur type
Cur	4	0.61 (−0.18, 1.40)	89.22	< 0.001
High bioavailable cur	2	0.21 (−0.20, 0.61)	00.00	0.630
Trial duration (weeks)
< 10	2	0.08 (−0.35, 0.50)	00.00	0.970
≥ 10	4	0.65 (−0.09, 1.40)	88.24	< 0.001
Impacts of CUR on LDL (mg/dL)
Overall effect	6	−0.31 (−0.68, 0.05)	64.42	0.020
Cur type
Cur	3	−0.26 (−0.70, 0.17)	48.11	0.150
High bioavailable cur	3	−0.35 (−1.00, 0.31)	78.51	0.010
Trial duration (weeks)
< 10	2	0.14 (−0.29, 0.56)	00.00	0.790
≥ 10	4	−0.51(−0.88, −0.13) a	55.91	0.080

Note: Bold values are indicate statistically significant p‐values.

Abbreviations: BMI, body mass index; CI, confidence interval; Cur, curcumin; FBS, fasting blood sugar; HDL, high‐density lipoprotein; HOMA‐IR, homeostasis model assessment of insulin resistance; LDL, low‐density lipoprotein; PCOS, polycystic ovarian syndrome; QUICKI, quantitative insulin sensitivity check index; SMD, standardized mean difference; TC, total cholesterol; TG, triglycerides.

^a Statistically significant.

3.4.2. Insulin

A pooled analysis of eight effect sizes [75, 76, 77, 91, 92, 93, 94, 95] with 546 participants revealed that CUR supplementation significantly reduced serum insulin concentrations in the CUR‐treated group in comparison with the control group (SMD: −0.32 µU/mL, 95% CI: −0.49, −0.14; p < 0.001) (Figure 3B). The subgroup analysis showed similar results for long‐term (≥ 10 weeks) supplementation with both CUR and high‐bioavailable CUR supplements (Table 2).

3.4.3. HOMA‐IR

A meta‐analysis of eight trials [75, 76, 77, 91, 92, 93, 94, 95], which included 546 participants, revealed a significant decline in HOMA‐IR levels following CUR intake (SMD: −0.36, 95% CI: −0.54, −0.19; p < 0.001) in the CUR‐treated group compared to the untreated group (Figure 3C). Subgroup analysis revealed similar results for long‐term supplementation (≥ 10 weeks) with both CUR and high‐bioavailable CUR supplements (Table 2).

3.4.4. QUICKI

The impact of CUR supplementation on QUICKI was assessed in four RCTs [75, 76, 77, 93] involving 292 PCOS patients. Pooled analysis demonstrated a substantial increase in QUICKI values (SMD, 0.37; 95% CI: 0.13, 0.61; p < 0.001) (Figure 3D).

3.5. Impact of CUR Supplementation on Lipid Profile

3.5.1. TC

A meta‐analysis of six trials [75, 77, 91, 92, 93, 94] with 370 participants demonstrated that CUR significantly reduced serum TC levels in the CUR group compared to the control group (SMD: −0.34 mg/dL, 95% CI: −0.61, −0.08; p = 0.01) (Figure 4A). Subgroup analysis revealed consistent results for long‐term (≥ 10 weeks) CUR supplementation (Table 2).

Figure 4.

Impacts of curcumin supplementation on lipid profile in patients with PCOS: (A) TC, (B) TG, (C) HDL, and (D) LDL.

3.5.2. TG

A pooled analysis of six RCTs [75, 77, 91, 92, 93, 94] with 370 participants did not display any substantial effects of CUR administration on serum TG levels in the experimental group (SMD: −0.68 mg/dL, 95% CI: −1.75, 0.39; p = 0.21) when compared to the untreated group (Figure 4B). There was notable heterogeneity among the trials (I² = 95.26%, p < 0.001) (Table 2).

3.5.3. HDL

The effect of CUR supplementation on serum HDL concentrations was evaluated in six studies [75, 77, 91, 92, 93, 94] with 370 participants (Figure 4C). Analysis of the pooled data did not reveal considerable changes in serum HDL levels in the CUR‐treated group compared with the control group (SMD: 0.47 mg/dL, 95% CI: −0.09, 1.03; p = 0.10). Furthermore, a high level of heterogeneity was detected among the RCTs (I ^² = 84.37%, p < 0.001) (Table 2).

3.5.4. LDL

A pooled analysis of six trials [75, 77, 91, 92, 93, 94] with 370 participants did not indicate any substantial changes in serum levels of LDL following CUR consumption in the CUR group compared to the untreated group (SMD: –0.31 mg/dL, 95% CI: –0.68, 0.05; p = 0.09) (Figure 4D). In addition, there was considerable heterogeneity among RCTs (I ^² = 64.42%, p = 0.02). A subgroup analysis revealed a substantial fall in serum LDL levels following long‐term (≥ 10 weeks) CUR supplementation (Table 2).

3.6. Impact of CUR Supplementation on Reproductive Hormones

3.6.1. DHEA, FSH, and LH

The meta‐analysis of three RCTs [76, 91, 93] with 202 participants did not reveal any substantial changes in the serum levels of DHEA following CUR administration (SMD: −0.05 μg/dL, 95% CI: −0.33, 0.23; p = 0.73) (Figure 5A), FSH (SMD: 0.10 mIU/mL [95% CI: −0.18, 0.37; p = 0.49]) (Figure 5B), and LH (SMD: −0.24 mIU/mL [95% CI: −0.52, 0.04; p = 0.10]) (Figure 5C).

Figure 5.

Impacts of curcumin supplementation on reproductive hormones in patients with PCOS: (A) DHEA, (B) FSH, (C) LH, and (D) testosterone.

3.6.2. Testosterone

The pooled analysis of two trials [91, 93] with 130 participants indicated that CUR supplementation did not considerably change serum testosterone levels (SMD: –0.73 μg/L, 95% CI: –2.66, 1.20; p = 0.46) (Figure 5D).

3.7. Risk of Bias Assessment

The RoB assessment for the included RCTs is displayed in Supporting Information S1: Table S2. Four studies [91, 93, 94, 95] exhibited a high RoB owing to inadequate randomization procedures. In contrast, the remaining four trials demonstrated a low risk of bias [75, 76, 77, 92].

3.8. GRADE Evaluation

The GRADE assessment of the evaluated outcomes is presented in Supporting Information S1: Table S3. The outcomes for body weight, FBS, insulin, FSH, LH, HOMA‐IR, and DHEA levels were supported by evidence of moderate certainty. The quality of evidence for BMI, HDL, TC, LDL, and testosterone levels was deemed low. Furthermore, the quality of outcomes for TG and testosterone levels were reduced to very low levels. The QUICKI outcome was rated as high.

3.9. Sensitivity Analysis

According to the sensitivity analysis, excluding specific RCTs related to BMI, FBS, HOMA‐IR, and insulin did not affect outcomes. However, the findings related to HDL and TG levels changed after the removal of one trial [93].

3.10. Publication Bias

There were noticeable levels of asymmetry in the funnel plots concerning BMI, HDL, TC, TG, and LDL outcomes based on visual inspection (Supporting Information S1: Figure S1). In addition, both Egger's and Begg's tests indicated substantial publication bias for outcomes related to BMI (p < 0.05). Furthermore, Egger's test also demonstrated significance for TC outcome.

3.11. Nonlinear and Linear Dose–Response Associations

A linear association (Supporting Information S1: Figure S5F) was identified between changes in the duration of CUR supplementation trials and alterations in the QUICKI (r = 15.15, p = 0.014). A nonlinear dose–response relationship (Supporting Information S1: Figure S2) was detected between changes in dosages of CUR supplements and alterations in outcomes related to HDL (r = 0.72, p = 0.003) and TG (r = −1.59, p = 0.003). No linear or nonlinear associations were identified between variations in the duration of CUR supplementation or its dosages and other outcomes, including body weight, insulin levels, FBS, HOMA‐IR, QUICKI, TC, TG, LDL, testosterone, DHEA, FSH, and LH (Supporting Information S1: Figures S2−S5).

4. Discussion

This dose–response meta‐analysis indicated that CUR supplementation was associated with improved glycemic control. This is evidenced by reductions in FBS, insulin levels, and HOMA‐IR, as well as increases in QUICKI values. In addition, the use of CUR as a supplement decreased TC levels. However, no substantial effect of CUR was observed on parameters such as body weight, BMI, TG, HDL, LDL, testosterone, DHEA, FSH, and LH. Subgroup analysis revealed that CUR supplementation decreased serum levels of insulin, LDL, FBS, TC, and HOMA‐IR in the CUR‐treated group compared with the control group during long‐term supplementation (≥ 10 weeks), regardless of whether standard CUR or high‐bioavailable CUR supplements were used. Furthermore, a linear association was identified between the duration of CUR supplementation and changes in the QUICKI scores. A nonlinear dose–response correlation was detected between variations in CUR dosage and changes in outcomes related to HDL and TG levels.

IR is frequently observed in women with PCOS [96]. Reduced sensitivity to insulin, linked to dysfunctional insulin receptors in various tissues, such as adipose tissue and skeletal muscle, can result in hyperinsulinemia among PCOS patients [97]. The results of this study support the effect of Cur on glucose regulation and enhancement of insulin sensitivity. These findings are consistent with a meta‐analysis of seven RCTs that demonstrated the efficacy of Cur in lowering blood glucose levels and enhancing insulin sensitivity [98]. Systematic reviews and meta‐analyses have demonstrated improvements in metabolic parameters, including decreases in HOMA‐IR and enhanced insulin sensitivity, in women with PCOS [78, 79, 81].

Cur appears to enhance insulin sensitivity through various mechanisms [99, 100, 101, 102, 103], primarily involving modulation of inflammatory pathways and gut microbiota. CUR enhances insulin sensitivity by targeting the nuclear factor kappa B (NF‐κB) pathway, reducing OS, and regulating inflammatory cytokines [104, 105, 106]. In addition, the effects of CUR on the gut microbiota contribute to its insulin‐sensitizing properties, as it alters the microbial composition, which in turn influences glucose metabolism [107]. Furthermore, CUR enhanced the expression of insulin‐degrading enzymes and preserved pancreatic islet integrity, particularly in elderly and obese models [108]. It also reduces OS, which is associated with diabetic complications [109]. It stimulates insulin secretion and sensitivity [110] as well as incretin hormones, thereby aiding glucose regulation [110]. Moreover, it modulates the AMP‐activated protein kinase (AMPK) pathway, reducing gluconeogenesis [109]. CUR decreases pro‐inflammatory cytokines that are detrimental to diabetes [111]. Although CUR shows promise in managing hyperglycemia, challenges such as its low bioavailability and solubility remain significant barriers to its clinical application [106]. The impact of CUR in improving insulin sensitivity highlights its potential as a therapeutic agent in the management of type 2 diabetes (T2DM) and its complications [111].

A significant number of women with PCOS have disorders related to lipid metabolism [112]. It has been suggested that CUR intake may lead to a reduction in TG and free fatty acids [113]. A previous meta‐analysis that evaluated the therapeutic effectiveness and safety of CUR in women with PCOS indicated that its impact on blood lipid levels, specifically HDL, TG, and LDL, was not statistically significant, unlike TC [98], which aligns with the findings of the present meta‐analysis. Furthermore, the antioxidant and anti‐inflammatory properties of CUR contribute to improved lipid profiles and overall metabolic health in women with PCOS [79, 114]. Several mechanisms underlying the lipid‐lowering effects of CUR have been identified, including inhibition of cholesterol absorption and synthesis, as well as regulation of fatty acid metabolism [115, 116]. Notably, it has been reported that CUR supplementation can substantially reduce TG, TC, and LDL levels in patients at risk for CVDs [117]. In addition, animal studies have indicated that CUR decreases abdominal fat and improves hepatic lipid profiles [118, 119]. CUR also boosts the antioxidant capacity, further supporting its role in lipid regulation [118]. The effects of CUR on lipid metabolism underscore its potential to reduce cardiovascular risk. However, some studies have reported no significant effects of CUR on lipid profiles, suggesting variability in responses and the necessity for further research to establish consistent outcomes [117].

Obesity is a critical exacerbating factor for the etiopathogenesis and development of PCOS. It is associated with menstrual irregularities and anovulation in women with PCOS [120]. CUR has shown efficacy in decreasing the synthesis of pro‐inflammatory cytokines and elevating adiponectin concentrations in individuals with overweight or obesity [121, 122, 123]. However, the current meta‐analysis indicated that CUR consumption does not have a significant impact on body weight or BMI.

Hyperandrogenism is a significant clinical feature observed in PCOS [124]. This condition leads to various pathophysiological changes such as IR, dyslipidemia, hyperinsulinemia, and an imbalance in LH and FSH levels [125]. These changes not only contribute significantly to the pathogenesis of PCOS but also interact synergistically [126]. Research on the impact of CUR on sex hormones is limited, and existing findings have shown inconsistencies. One study indicated that supplementation with CUR for 12 weeks reduced DHEA levels and elevated circulating estradiol levels in PCOS patients [76]. In this meta‐analysis, CUR supplementation did not have a substantial effect on testosterone, DHEA, LH, or FSH levels. These outcomes are consistent with a prior meta‐analysis that reported no substantial influence on sex hormone levels [98].

The rationale for selecting CUR type and treatment duration as subgrouping variables is crucial for understanding treatment efficacy. CUR exhibits limited absorption and solubility in its unbound form in the gastrointestinal tract [127]. In addition, its rapid biotransformation into inactive metabolites significantly restricts its effectiveness as a health‐promoting compound and dietary supplement [127]. However, recent advancements in micro‐ and nano‐formulations of CUR have substantially improved its absorption, leading to increased concentrations of active CUR in the bloodstream [127]. High‐bioavailable CUR had significantly improved absorption and bioavailability compared to standard CUR [127, 128, 129], leading to better systemic exposure and potential health benefits [127]. Nevertheless, while formulations with high bioavailability show promise, concerns regarding excessive CUR levels leading to adverse cellular effects necessitate careful monitoring [130].

Long‐term CUR supplementation had a more significant impact on reducing the risk of cardiometabolic disease than short‐term supplementation [131, 132, 133]. In addition, long‐term CUR supplementation in animal models could enhance metabolic responses and improve insulin sensitivity [134]. Moreover, longer durations of CUR intake have been associated with greater effects on IR and lipid profiles, particularly with formulations such as nano‐CUR [132]. The extended use of CUR has shown enhanced anti‐inflammatory effects [135]. In contrast, short‐term CUR supplementation often exhibits less pronounced effects on metabolic parameters, highlighting the need for longer intervention periods to achieve optimal results [136]. However, it has been suggested that the effectiveness of CUR may vary based on individual health status and gut microbiota, indicating that not all consumers may experience the same benefits from long‐term supplementation [137]. Cur has a favorable safety profile and is considered a promising natural compound for managing metabolic disorders [137].

This dose–response meta‐analysis evaluated the effect of CUR supplementation on cardiometabolic risk factors in women with PCOS. The systematic search imposed no limitations regarding period or language. In addition, subgroup analysis, dose–response evaluation, sensitivity analysis, and assessments for publication bias were performed. Based on the GRADE evaluation, a moderate level of certainty was observed for half of the outcomes assessed in the meta‐analysis. CUR is generally well tolerated, with minimal reported adverse effects [79, 114]. Although Cur demonstrates beneficial effects, further large‐scale RCTs are necessary to confirm its long‐term efficacy and safety in diverse populations with PCOS [114].

However, this meta‐analysis has several limitations. A substantial degree of heterogeneity was identified in various factors, such as demographic characteristics, differences in CUR supplementation, dosage levels, intervention durations, and study methodologies. The restrictive inclusion criteria resulted in a limited number of RCTs being incorporated into the meta‐analysis. Only two or three studies were available to assess the impact of CUR intake on reproductive hormones. Furthermore, the predominantly Middle Eastern and Asian populations in the included studies necessitate caution when extrapolating and interpreting the findings for other ethnic groups. In addition, a wide range of CUR dosages were administered in the trials. Half of the RCTs in this analysis exhibited a high RoB, while half of the evaluated outcomes had low or very low certainty. Subgroup and sensitivity analyses were conducted to address heterogeneity and potential bias among studies. Subgroup analysis facilitates the exploration of variations in treatment effects across different participant characteristics, thereby enhancing the robustness of findings by identifying specific subgroups that may derive greater benefits or experience adverse effects from interventions. Sensitivity analyses are crucial for verifying the reliability of results and ensuring that findings are not influenced by specific studies. While low‐quality evidence can lead to inaccurate conclusions, caution is warranted in its interpretation. It is important to recognize that not all studies of poor quality lack value; they may provide valuable insights or identify areas for further research.

5. Conclusion

The findings of this meta‐analysis revealed that CUR may enhance cardiometabolic health by alleviating hyperglycemia, IR, and TC levels in women with PCOS. This is evidenced by reductions in FBS, insulin levels, and the HOMA‐IR, as well as increases in the QUICKI values, with moderate to high certainty. In addition, CUR supplementation was related to decreased TC levels. However, there were no substantial impacts of CUR on anthropometric parameters (BMI and body weight), levels of LDL, HDL, TG, or reproductive hormones (testosterone, FSH, DHEA, and LH). These findings underscore the necessity for further validation through rigorously designed RCTs that incorporate larger sample sizes and extended follow‐up periods.

Author Contributions

Shooka Mohammadi: writing – original draft, writing – review and editing, investigation, data curation. Somayeh Ziaei: investigation. Mehrnaz Morvaridi: investigation. Motahareh Hasani: investigation. Elham Mirtaheri: investigation. Farnaz Farsi: investigation. Sara Ebrahimi: investigation. Elnaz Daneshzad: investigation. Javad Heshmati: investigation, conceptualization, methodology, data curation, supervision, formal analysis, project administration.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

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

Supporting information

Supporting information.

Data Availability Statement

The data analyzed in this study can be obtained from the corresponding author upon request.