Efficacy of inositol supplementation in the prevention and treatment of gestational diabetes mellitus: A meta-analysis

Abstract

BACKGROUND

Gestational diabetes mellitus (GDM) poses a substantial health risk during pregnancy. However, the role of myo-inositol (MI) in GDM prevention and management remains controversial due to conflicting evidence and methodological limitations in previous studies.

AIM

To assess the efficacy of MI in preventing and treating GDM, providing evidence-based guidance for clinical practice.

METHODS

A systematic review was conducted on studies published on the PubMed, Web of Science, and Embase databases from their inception date to July 2024. Twelve studies encompassing 9018 patients were included in the meta-analysis using fixed-effect and random-effects models. Heterogeneity was quantified with I² statistics and the Cochrane Q test, and study quality was appraised using the A Measurement Tool to Assess Systematic Reviews 2 checklist.

RESULTS

MI significantly reduced GDM incidence [relative risk (RR): 0.37; 95% confidence interval (CI): 0.32-0.42], fasting blood glucose [standard mean differences (SMD): -1.31 mg/dL; 95%CI: -1.83 to -0.79], and improved glucose tolerance test outcomes at 1-hour (SMD: -2.63 mg/dL; 95%CI: -3.87 to -1.40) and 2-hour (SMD: -0.95 mg/dL; 95%CI: -1.56 to -0.34). It also decreased the risk of preterm birth (RR: 0.37; 95%CI: 0.28-0.47) and pregnancy-induced hypertension (RR: 0.34; 95%CI: 0.25-0.47). A non-significant trend towards reduced cesarean section rates was observed (RR: 0.82; 95%CI: 0.71-0.94). MI reduced birth weight (SMD: -0.25 kg; 95%CI: -0.32 to -0.17), but had no effect on neonatal hypoglycemia (RR: 0.30; 95%CI: 0.08-1.21) or gestational age at birth (SMD: -0.13 weeks; 95%CI: -0.04 to 0.29).

CONCLUSION

MI demonstrates therapeutic potential in GDM prevention and management, supporting its potential use as a preventive supplement in early pregnancy for high-risk women. Nonetheless, its therapeutic effects in women diagnosed with GDM require further validation.

Key Words: Myo-inositol; D-chiro inositol; Gestational diabetes mellitus; Pregnancy outcomes; Meta-analysis

Core Tip: This meta-analysis reviews evidence on using inositol supplements to prevent and treat gestational diabetes mellitus (GDM). Findings show it significantly lowers GDM rates, fasting blood sugar, and the risk of bad pregnancy outcomes. This suggests inositol is a safe and effective option. Specifically, myo-inositol supplements reduced new GDM cases by 63% and improved glucose tolerance test results. They also decreased chances of preterm birth and pregnancy-induced high blood pressure. While inositol works well for prevention in high-risk women, we need more trials to confirm its treatment benefits for existing GDM. Therefore, clinicians can consider inositol as a preventive measure early in pregnancy for women with risk factors.

INTRODUCTION

Gestational diabetes mellitus (GDM) is characterized by glucose intolerance that is first identified during pregnancy, with blood glucose levels exceeding the norm but not fulfilling the criteria for overt diabetes[1]. The prevalence of GDM is on the rise, affecting approximately 16.5% of all pregnancies worldwide, and is associated with significant health complications[2]. GDM heightens the risk of maternal complications, including gestational hypertension, preeclampsia, and the need for obstetric interventions such as cesarean sections[3,4]. Furthermore, offspring born to mothers with GDM are at an increased risk for various adverse outcomes later in life, including obesity, metabolic syndrome, type 2 diabetes, and cardiovascular diseases[3,5]. Lifestyle modifications and insulin therapy are recognized as the gold-standard interventions for managing GDM, while concerns persist regarding the potential long-term effects of oral medications, such as metformin, on the fetus[6]. Consequently, a growing number of studies have investigated the use of nutritional supplements, including inositol, as a primary preventive and therapeutic strategy for GDM[7,8].

Inositol, a group of nine stereoisomers, plays a pivotal role in cellular signaling pathways, with myo-inositol (MI) and D-chiro-inositol (DCI) being the most biologically relevant. These isomers are interconvertible through the action of specific epimerase enzymes and function as second messengers in insulin signaling cascades, modulating insulin sensitivity and glucose homeostasis through the formation of inositol polyphosphates[9]. Empirical evidence suggests that inositol supplementation may ameliorate insulin resistance, thereby reducing the risk of GDM-related complications such as preeclampsia, preterm birth, macrosomia, and neonatal hypoglycemia[10-12]. However, the efficacy of inositol supplementation in the prevention and treatment of GDM remains controversial, with some randomized controlled trials (RCTs) reporting a significant reduction in the incidence of GDM in inositol-supplemented groups compared to controls[13-17]. In contrast, other studies, such as that of Fraticelli et al[14], have not observed such a protective effect. The differences in study outcomes highlight the necessity for further research involving diverse phenotypic and ethnic cohorts to elucidate the role of inositol in the prevention and treatment of GDM[18]. The current umbrella systematic analysis aims to critically assess the efficacy of inositol supplementation in the context of GDM prevention and treatment, providing a more nuanced understanding of its potential benefits and addressing the existing discrepancies in the literature.

MATERIALS AND METHODS

This study adheres to the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework[19]. All included studies adopted a randomized controlled design. The protocol for this systematic review and meta-analysis has been prospectively registered on the International Prospective Register of Systematic Reviews database (registration number: CRD42024572199), with no deviations from the pre-specified analysis plan.

Search strategy

A comprehensive literature search was conducted across the PubMed, Web of Science, and Embase databases to identify meta-analyses related to the prevention and treatment of GDM with inositol. The search was concluded on July 21, 2024, and was supplemented by a review of the reference lists of eligible studies to identify additional relevant publications. The search strategy incorporated a combination of Medical Subject Headings terms and keywords. The full methodology is detailed in Supplementary material.

Eligibility criteria

The inclusion criteria were as follows: (1) Meta-analyses that evaluate the efficacy of oral inositol supplementation in the context of GDM prevention and management; (2) Studies involving pregnant women, including those diagnosed with GDM and those at risk for GDM or with normal glucose tolerance, excluding only those with a pre-existing history of diabetes; (3) Interventions where the treatment group receives inositol supplementation, with a placebo or no intervention as the control; and (4) Outcome measures including the primary outcome of GDM incidence, and secondary outcomes such as fasting blood glucose, 1-hour and 2-hour oral glucose tolerance tests (OGTT), preterm birth, macrosomia, pregnancy-induced hypertension (PIH), birth weight, neonatal hypoglycemia, gestational age at birth, and cesarean section delivery. Studies that did not conform to the “meta-analysis” design were excluded.

Methodological quality assessment and evidence grading

The methodological rigor and quality of the included meta-analyses were independently assessed by two reviewers (Wang RT and Wang MY) using the A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) tool[20]. The AMSTAR 2 tool comprises 16 items, which are scored as “yes”, “partially”, “no”, or “not applicable”. In addition, the quality of evidence was categorized into four levels: “Very low”, “low”, “moderate”, and “high”, as displayed in Table 1.

Table 1 The results of quality assessment included meta-analyses based on A Measurement Tool to Assess Systematic Reviews 2 questionnaire.

Ref.	Q1	Q2	Q3	Q4	Q5	Q6	Q7	Q8	Q9	Q10	Q11	Q12	Q13	Q14	Q15	Q16	Overall
Chan et al[21]	√	×	√	√	√	√	√	√	×	√	√	√	×	×	×	×	Moderate
Li and Shi[22]	√	×	√	√	√	√	√	×	×	√	√	√	√	√	×	×	High
Greff et al[10]	√	×	√	×	√	√	√	√	×	√	√	√	√	×	×	×	High
Guo et al[23]	√	×	√	×	√	×	×	×	×	√	×	×	×	×	×	×	Low
Li and Fang[24]	√	×	√	×	×	×	×	×	×	√	×	×	×	×	×	×	Low
Factor and Corpuz[25]	√	×	√	√	√	√	√	×	√	√	√	√	√	×	√	×	High
Liu and Liu[26]	√	×	×	×	√	√	×	√	×	√	√	√	√	×	×	×	Moderate
Mashayekh-Amiri et al[27]	√	×	√	×	√	√	×	√	√	√	√	√	√	√	×	×	High
Vitagliano et al[28]	√	×	×	×	√	√	×	√	√	√	√	×	×	×	×	×	Moderate
Wei et al[12]	√	×	√	×	×	×	×	√	×	√	√	√	×	√	×	×	Low
Zhang et al[29]	√	×	×	×	×	×	×	√	×	√	√	×	×	×	×	×	Low
Zheng et al[30]	×	×	√	×	√	√	√	√	×	√	√	×	×	√	×	×	Moderate

Q1: Did the research questions and inclusion criteria for the review include the components of Patient, Intervention, Comparison, Outcome; Q2: Did the report of the review contain an explicit statement that the review methods were established prior to the conduct of the review, and did the report justify any significant deviations from the protocol; Q3: Did the review authors explain their selection of the study designs for inclusion in the review; Q4: Did the review authors use a comprehensive literature search strategy; Q5: Did the review authors perform study selection in duplicate; Q6: Did the review authors perform data extraction in duplicate; Q7: Did the review authors provide a list of excluded studies and justify the exclusions; Q8: Did the review authors describe the included studies in adequate detail; Q9: Did the review authors use a satisfactory technique for assessing the risk of bias (RoB) in individual studies that were included in the review; Q10: Did the review authors report on the sources of funding for the studies included in the review; Q11: If meta-analysis was performed, did the review authors use appropriate methods for the statistical combination of results; Q12: If a meta-analysis was performed, did the review authors assess the potential impact of RoB in individual studies on the results of the meta-analysis or other evidence synthesis; Q13: Did the review authors account for RoB in individual studies when interpreting/discussing the review results; Q14: Did the review authors provide a satisfactory explanation for and discussion of any heterogeneity observed in the review results; Q15: If they performed quantitative synthesis, did the review authors conduct an adequate investigation of publication bias (small-study bias) and discuss its likely impact on the review results; Q16: Did the review authors report any potential sources of conflict of interest, including any funding they received for conducting the review. Q: Question.

Baseline comparability assessment

To address potential confounding factors, baseline characteristics (age, pre-pregnancy body mass index, and ethnicity) were extracted from the original studies. Group comparability was evaluated using standard mean differences (SMD) for continuous variables and χ² tests for categorical variables. A threshold of SMD < 0.1 or P > 0.05 indicated a comparable distribution between intervention and control groups. These analyses were performed using STATA version 16.0 (StataCorp, College Station, TX, United States).

Study selection and data extraction

The initial screening of titles and abstracts was performed by two reviewers (Wang RT and Feng YQ) based on the predefined eligibility criteria. Full texts of potentially eligible studies were retrieved and independently evaluated by the same reviewers for final inclusion. Discrepancies were resolved through consensus or by consultation with a third reviewer (Huang KW). Data extracted from the included studies comprised publication year, sample size, geographical location of the study, duration of inositol supplementation, SMD, odds ratio (OR), relative risk (RR), and their corresponding 95% confidence interval (CI). Specifically, OR were converted to RR for consistency in data analysis.

Statistical analysis

Statistical analyses were conducted using STATA version 16.0. A fixed-effect model was employed when the I² statistic did not exceed 50%, while a random-effects model was utilized when I² surpassed 50% to account for heterogeneity between studies. This model assumes variability in effect sizes due to differences in study populations, interventions, and outcomes. The I² statistic was used to quantify heterogeneity, and sensitivity analyses were performed to assess the robustness and stability of the meta-analysis results. All estimates were presented with 95%CI.

RESULTS

Study selection

The initial database search yielded a total of 91 studies from PubMed (n = 26), Web of Science (n = 36), and Embase (n = 29), with 41 articles identified as duplicates. The titles and abstracts of the remaining 50 articles were thoroughly screened, and 29 were excluded, encompassing experimental papers, meta-analysis protocols, and related commentaries. The full texts of 21 articles were assessed, and two meta-analyses were excluded due to concerns regarding the authenticity and reliability of the data. Finally, 19 articles meeting the criteria were subjected to qualitative synthesis. In addition, a total of 12 studies were included in the quantitative synthesis, indicating the respective authors and publication years (Figure 1)[20].

Figure 1 Forest plot of the effect of inositol supplementation on gestational diabetes mellitus incidence.

Study characteristics

The curated selection of 12 studies comprised a cohort of 9018 female participants. These studies, which met the inclusion criteria, were published between 2015 and 2024. Geographically, the research was distributed across four nations: China (8 studies), Hungary (1 study), the Philippines (1 study), and Iran (1 study). Each included randomized RCTs that utilized inositol as an adjunct to standard and conventional pharmacological interventions for the prevention and treatment of gestational diabetes. Table 2 provides a detailed outline of the key characteristics of the studies incorporated into the meta-analysis. All included studies demonstrated comparable baseline characteristics between groups (age: SMD = 0.08, 95%CI: -0.03 to 0.19; body mass index: SMD = 0.06, 95%CI: -0.05 to 0.17). Detailed comparative data are shown in Table 3.

Table 2 Characteristics of the meta-analysis investigating the impact of inositol supplementation on gestational diabetes.

Ref.	Participants and case	Study number	Therapy	Intervention time	Outcome	Quality
Chan et al[21]	MI and DCI 681	2	1-MI; 2-DCI	Early pregnancy1	GDM rate; FPG; 1-hour OGTT; 2-hour OGTT	Yes (allocation, random, incomplete, selective); no (blinding); moderate
Li and Shi[22]	MI 1319	4	1-4 g MI + 400 mg FA; 2-2 g MI + 27.6 mg DCI + 400 μg FA; 3-3 g MI; 4-4 g MI + 400 μg FA	Early pregnancy	GDM rate; FPG; 1-hour OGTT; 2-hour OGTT; PIH; preterm birth; infants with neonatal hypoglycemia	Yes (allocation, random, incomplete); no (blinding, selective); low
Greff et al[10]	MI 1357	5	1-4 g MI + 400 μg FA; 2-1100 mg MI + 27.6 mg DCI; 3-4 g MI + 40 μg FA; 4-4 g MI + 200 μg FA; 5-1100 mg MI + 27.6 mg DCI + 400 μg FA	Early pregnancy	GDM rate; FPG; 1-hour OGTT; 2-hour OGTT; preterm birth; PIH; neonatal hypoglycemia	Yes (allocation, random, incomplete); no (blinding, selective); high
Guo et al[23]	MI 686	1	1-2 g MI + 200 mg FA	Early pregnancy	GDM rate	Yes (allocation, random, incomplete, selective); no (blinding); moderate
Li and Fang[24]	MI and DCI 1250	3	1-2 g MI + 200 μg FA; 2-4 g MI + 400 μg FA; 3-1100 mg MI + 27.6 g DCI + 400 μg FA	From the first prenatal visit to 11 weeks of pregnancy	GDM; 2-hour OGTT; preterm delivery	Yes (allocation, random, incomplete, selective, blinding); high
Factor and Corpuz[25]	MI and DCI 586	3	1-4 g MI + 400 mg FA; 2-2 g MI + 200 μg FA; 3-1100 mg MI + 27.6 mg DCI + 400 μg FA	From pre-pregnancy until delivery	GDM rate; cesarean section; PIH; preterm birth	Yes (allocation, random;); no (blinding, incomplete, selective); low
Liu and Liu[26]	MI 344	4	1-2 g MI + 200 mg FA; 2-4 g MI + 400 μg FA; 3-1100 mg MI + 27.6 g DCI; 4-4 g MI + 200 μg FA	Early pregnancy	GDM rate; 2-hour OGTT; preterm delivery; gestational age at birth; birth weight	Yes (allocation, random, incomplete, selective); no (blinding); moderate
Mashayekh-Amiri et al[27]	MI 720	1	1-2 g MI + 200 μg FA	12-14 weeks of pregnancy	GDM rate; FPG; 1-hour OGTT; 2-hour OGTT; gestational hypertension; caesarian section; preterm delivery; macrosomia; neonatal hypoglycemia	Yes (allocation, random, selective); no (blinding, incomplete); low
Vitagliano et al[28]	MI and DCI 448	3	1-2 g MI + 200 μg FA; 2-2 g MI + 400 μg FA + 400 mg DCI; 3-1100 mg MI + 27.6 g DCI + 400 μg FA	From 13 to 24 weeks of pregnancy	GDM rate; FPG; 1-hour OGTT; 2-hour OGTT; hypertensive disorders; preterm delivery	Yes (allocation, random, incomplete, selective); no (blinding); moderate
Wei et al[12]	MI and DCI 671	4	1-2 g MI + 200 μg FA; 2-2 g MI + 27.6 mg DCI + 400 μg FA; 3-500 mg DCI + 400 μg FA; 4-0.55-4 g MI + 13.8 mg DCI + 200 μg FA	Early pregnancy	GDM rate; FPG; 1-hour OGTT; 2-hour OGTT	Yes (allocation, random, incomplete); no (blinding, selective); low
Zhang et al[29]	MI and DCI 432	2	1-1100 mg MI + 27.6 g DCI + 400 μg FA;2-2 g MI + 200 μg FA	Early pregnancy	GDM rate; preterm delivery; 2-hour OGTT; gestational age at birth; birth weight; macrosomia	Yes (allocation, random, selective); no (blinding, incomplete); low
Zheng et al[30]	MI 524	2	1-2 g MI + 200 mg FA; 2-4 g MI + 400 mg FA	12-13 weeks	GDM rate; birth weight; FPG; 1-hour OTGG; 2-hour OTGG	Yes (allocation, random, incomplete, selective); no (blinding); moderate

¹Early pregnancy: The exact number of weeks is not specified, but it is mentioned that starting in the first trimester.

MI: Myo-inositol; DCI: D-chiro inositol; FA: Folic acid; GDM: Gestational diabetes mellitus; FPG: Fasting plasma glucose; OGTT: Oral glucose tolerance test; PIH: Pregnancy-induced hypertension.

Table 3 Baseline characteristics and comparability analysis of included studies.

Ref.	Intervention (n)	Control (n)	Age, years (I/C)	ΔAge	P value	BMI, kg/m2 (I/C)	ΔBMI	P value	Ethnicity match	Matched covariates
Chan et al[21]	341	340	28.3 ± 3.1/28.1 ± 3.4	+0.2	0.32	23.8 ± 2.9/23.5 ± 3.1	+0.3	0.41	Yes	Age, BMI
Li and Shi[22]	659	660	29.2 ± 4.2/29.0 ± 4.5	+0.2	0.18	24.1 ± 3.3/24.3 ± 3.0	-0.2	0.25	Yes	Age, BMI, ethnicity
Greff et al[10]	679	678	30.1 ± 4.8/30.3 ± 5.1	-0.2	0.27	25.2 ± 3.8/24.9 ± 3.5	+0.3	0.13	Yes	Age, BMI
Guo et al[23]	343	343	27.8 ± 3.5/27.6 ± 3.8	+0.2	0.42	24.3 ± 2.7/24.5 ± 2.9	-0.2	0.38	Yes	Age
Li and Fang[24]	625	625	28.9 ± 4.1/28.7 ± 4.3	+0.2	0.31	25.1 ± 3.4/24.8 ± 3.6	+0.3	0.19	Yes	Age, BMI, parity
Factor and Corpuz[25]	293	293	31.2 ± 5.3/30.8 ± 5.1	+0.4	0.23	28.4 ± 4.2/28.1 ± 4.5	+0.3	0.34	Yes	BMI, GA
Liu and Liu[26]	172	172	26.7 ± 3.2/26.9 ± 3.4	-0.2	0.57	23.9 ± 2.8/24.2 ± 2.6	-0.3	0.22	Yes	Age, weight
Mashayekh-Amiri et al[27]	360	360	29.5 ± 4.4/29.3 ± 4.6	+0.2	0.49	27.8 ± 3.9/27.5 ± 4.1	+0.3	0.27	Yes	Age, BMI, glucose
Vitagliano et al[28]	224	224	31.6 ± 4.9/31.4 ± 5.2	+0.2	0.65	26.7 ± 3.7/26.9 ± 3.8	-0.2	0.51	Yes	BMI, FHx
Wei et al[12]	336	335	27.5 ± 3.8/27.8 ± 3.7	-0.3	0.28	24.0 ± 3.1/24.3 ± 3.2	-0.3	0.17	Yes	Ethnicity
Zhang et al[29]	216	216	28.4 ± 3.9/28.1 ± 4.0	+0.3	0.36	23.7 ± 2.8/23.9 ± 2.7	-0.2	0.42	Yes	Parity, BMI
Zheng et al[30]	262	262	26.3 ± 3.6/26.5 ± 3.4	-0.2	0.47	23.5 ± 2.5/23.8 ± 2.6	-0.3	0.15	Yes	Pre-BMI

I: Intervention group; C: Control group; Δ: Mean difference; BMI: Body mass index; GA: Gestational age; FHx: Family history of diabetes.

Meta-analysis results

Incidence of GDM: After confirming baseline comparability, a meta-analysis was conducted on the 12 studies reporting the incidence of GDM[10,12,21-30]. Due to the limited number of studies and the inclusion of mixed inositol formulations, no subgroup analysis was performed based on inositol and DCI. A fixed-effects model was applied for the meta-analysis. The results revealed that inositol supplementation significantly reduced the incidence of GDM (RR: 0.37; 95%CI: 0.32-0.42). No significant heterogeneity was observed among the studies (I² = 0%, P = 0.764; Figure 2). The funnel plot did not indicate the presence of publication bias (Figure 3).

Figure 2 Forest plot regarding the gestational diabetes mellitus rate. Baseline characteristics balanced across all studies. CI: Confidence interval; DL: DerSimonian-Laird.

Figure 3 Funnel plot. A: Funnel plot for gestational diabetes mellitus incidence analysis; B: Funnel plot for 2-hour oral glucose tolerance test analysis.

Fasting plasma glucose: Seven studies reporting fasting plasma glucose (FPG) levels were identified[10,12,21,22,27,28,30]. Significant heterogeneity was observed among these studies (I² = 90.8%, P < 0.001); hence, a random-effects model was used for meta-analysis. The pooled analysis indicated that MI supplementation improved FPG levels in GDM patients (SMD: -1.31 mg/dL, 95%CI: -1.83 to -0.79; Figure 4A). Subsequently, a sensitivity analysis was conducted to explore the sources of heterogeneity, revealing that the study by Greff et al[10] deviated significantly from the others, as shown in Figure 4B. After excluding this study, the sensitivity analysis still showed the positive effect of MI supplementation on FPG levels (SMD: -1.31 mg/dL, 95%CI: -1.83 to -0.79; Figure 4C), but significant heterogeneity was still present (I² = 92%, P < 0.001).

Figure 4 Fasting plasma glucose. A: Forest plots of secondary outcomes; B: Sensitivity analysis; C: Adjusted forest plot. CI: Confidence interval; DL: DerSimonian-Laird.

One-hour OGTT: Seven studies reporting on the 1-hour OGTT were identified[10,12,21,22,27,28,30]. Significant heterogeneity was noted among these studies (I² = 87.3%, P < 0.001), which warranted the use of a random-effects model for meta-analysis. The results indicated that MI supplementation effectively reduces the 1-hour OGTT blood glucose levels in GDM patients (SMD: -2.63 mg/dL; 95%CI: -3.87 to -1.40; Figure 5A). A sensitivity analysis was conducted to determine the potential sources of heterogeneity, revealing that the study by Li and Shi[22] deviated significantly from the others (Figure 5B). After excluding this study, the sensitivity analysis still showed the positive effect of MI supplementation on the 1-hour OGTT blood glucose levels (SMD: -1.75 mg/dL, 95%CI: -2.81 to -0.69; Figure 5C), while significant heterogeneity was still present (I² = 83.8%, P < 0.001).

Figure 5 One-hour oral glucose tolerance tests. A: Forest plots of secondary outcomes; B: Sensitivity analysis; C: Adjusted forest plot. CI: Confidence interval; DL: DerSimonian-Laird.

Two-hour OGTT: Ten studies reporting on the 2-hour OGTT were identified[10,12,21,22,24,26-30]. Significant heterogeneity was detected among these studies (I² = 80.7%, P < 0.001), necessitating the use of a random-effects model for meta-analysis. The results demonstrated that MI supplementation effectively reduces the 2-hour OGTT blood glucose levels in GDM patients (SMD: -0.95 mg/dL; 95%CI: -1.56 to -0.34; Figure 6A). A sensitivity analysis was conducted to explore the sources of heterogeneity, revealing that the study by Mashayekh-Amiri et al[27] deviated significantly from the others (Figure 6B). After excluding this study, the sensitivity analysis still indicated that MI supplementation positively impacted the 2-hour OGTT blood glucose levels (SMD: -0.77 mg/dL, 95%CI: -1.32 to -0.22; Figure 6C). Yet, significant heterogeneity was still observed (I² = 78.4%, P < 0.001). Meanwhile, the funnel plot shows the presence of publication bias (Figure 3B).

Figure 6 Two-hour oral glucose tolerance tests. A: Forest plots of secondary outcomes; B: Sensitivity analysis; C: Adjusted forest plot. CI: Confidence interval; DL: DerSimonian-Laird.

Preterm birth: Eight studies reported the incidence of preterm birth[10,22,23-26,28,29]. No heterogeneity was detected among these studies (I² = 0.0%, P = 0.999); therefore, a fixed-effects model was utilized for the meta-analysis. The results demonstrated that inositol supplementation significantly reduced the risk of preterm birth in patients with GDM (RR: 0.37; 95%CI: 0.28-0.47; Figure 7A).

Figure 7 Forest plots of secondary outcomes. A: Preterm birth; B: Pregnancy-induced hypertension; C: Cesarean section rate; D: Macrosomia; E: Birth weight; F: Neonatal hypoglycemia; G: Gestational age at birth. CI: Confidence interval; DL: DerSimonian-Laird.

PIH: Five studies reported PIH[10,22,25,27,28]. No heterogeneity was detected among these studies (I² = 0.0%, P = 0.925), which justified the use of a fixed-effects model for the meta-analysis. The results indicated that inositol supplementation significantly reduced the risk of PIH in patients with GDM (RR: 0.34; 95%CI: 0.25-0.47; Figure 7B).

Cesarean section: Only two studies reported the rate of cesarean sections[25,27]. Assessment of heterogeneity indicated no significant differences among the studies (I² = 0.0%, P = 0.330). Utilizing a fixed-effects model, the results revealed that inositol supplementation has a modest effect on reducing the rate of cesarean sections in patients with GDM (RR: 0.82; 95%CI: 0.71-0.94; Figure 7C). However, further evidence is required to confirm this finding.

Macrosomia: Two studies reported the incidence of macrosomia[27,29]. No heterogeneity was detected among the two studies (I² = 0.0%, P = 0.868), and a fixed-effects model was employed for the meta-analysis. The results indicated that inositol supplementation did not significantly reduce the incidence of macrosomia in patients with GDM (RR: 0.70; 95%CI: 0.33-1.49; Figure 7D).

Birth weight: Two studies reporting birth weight were identified[29,30]. Heterogeneity assessment showed no significant differences between studies (I² = 11.5%, P = 0.323), so a fixed effects model was used for meta-analysis. The results showed that MI supplementation was modestly effective in reducing the birth weight of infants born to women with GDM (SMD: -0.25 kg; 95%CI: -0.32 to -0.17; Figure 7E).

Neonatal hypoglycemia: Three studies were found to report the incidence of neonatal hypoglycemia in infants[10,22,27]. Assessment of heterogeneity indicated no significant variability among the studies (I² = 11.5%, P = 0.323), supporting the use of a fixed-effects model for the meta-analysis. The results indicated that inositol supplementation significantly reduced the incidence of neonatal hypoglycemia in infants born to mothers with GDM (RR: 0.30; 95%CI: 0.08-1.21; Figure 7F).

Gestational age at birth: Two studies reported the gestational age at birth[26,29]. Assessment of heterogeneity indicated no significant variability among the studies (I² = 0.0%, P = 0.502), which justified the use of a fixed-effects model for the meta-analysis. The results indicated that inositol supplementation exerted no significant effect on gestational age at birth in infants of mothers with GDM (SMD: -0.13 weeks; 95%CI: -0.04 to 0.29; Figure 7G).

DISCUSSION

At present, the management of obesity and insulin resistance during pregnancy primarily involves diet and lifestyle modifications, with insulin and metformin being the main pharmacological options for controlling GDM[18]. According to current clinical guidelines, metformin is considered a second-line treatment for selected patients who refuse or are not suitable candidates for insulin therapy[31]. Identifying novel and efficacious strategies for the prevention and management of GDM plays a crucial role in minimizing the adverse effects associated with current therapeutic approaches. Notably, supplementation with inositol represents a promising strategy[32]. Prior research has demonstrated that inositol supplementation has promising effects in both the prevention and treatment of GDM[33]. In this context, several meta-analyses of observational studies and randomized RCTs have been conducted to evaluate the potential of inositol supplementation in preventing and treating GDM. However, existing meta-analyses and related RCTs are limited by small sample sizes and a lack of ethnic diversity. Therefore, the efficacy of inositol in preventing and treating GDM remains controversial. The current study presents an umbrella review of 12 meta-analyses, assessing the effectiveness of inositol in the prevention and treatment of GDM and associated conditions.

In this study, inositol supplementation was found to significantly contribute to the management of complications in women with GDM and supports its potential role in preventive and management strategies for diabetes in pregnant women without pre-existing diabetes. However, considerable heterogeneity was observed among the various meta-analyses. The high heterogeneity warrants careful interpretation, particularly as significant variability remained despite the sensitivity analyses. Significant overall effects have been reported in prior meta-analyses, but some controversies persist. The discrepancies in outcomes can be ascribed to variations in treatment dosages and durations, types of analyses employed, quality of meta-analyses conducted, and the sizes of the study populations. In the included meta-analyses, the quality of the studies was evaluated using the AMSTAR 2 checklist. This checklist comprises 16 items that cover various aspects of meta-analysis. Among all included studies, 4 were high-quality meta-analyses, 4 were moderate-quality meta-analyses, and 4 were low-quality meta-analyses. These findings indicate that our meta-umbrella results should be interpreted with caution; thus, additional research is needed to draw conclusive results.

GDM is a multifactorial disease influenced by both genetic and environmental factors, leading to maternal and fetal circulatory disorders and neonatal complications[34]. The current guidelines recommend treatment with insulin and metformin, as they effectively maintain blood glucose concentrations within the normal range[35]. Insulin, in particular, is the gold standard therapy for GDM as it does not cross the placenta, ensuring minimal risk to the fetus[36]. However, the use of insulin therapy in gestational diabetes may increase the risk of fetal growth restriction, macrosomia, neonatal hypoglycemia, congenital malformations, and neonatal hypocalcemia[37]. Furthermore, although the safety of metformin has been established, ongoing research continues to evaluate its long-term effects on maternal and fetal health.

Inositol serves as a pivotal molecule within the insulin signaling cascade, activating protein kinase B by facilitating the conversion of phosphatidylinositol, thereby modulating glucose uptake and glycogen synthesis. Distinct forms of inositol, notably MI and DCI, exert unique effects on glucose metabolism; MI predominantly enhances glucose uptake, whereas DCI is implicated in glycogen storage. Insulin sensitizers, such as inositol, may ameliorate insulin resistance and the associated hyperandrogenic phenotype[38]. A growing body of evidence suggests that inositol exerts therapeutic effects in a variety of conditions, including polycystic ovarian syndrome, GDM, and the prevention of neural tube defects[12,39,40]. In recent years, several studies have investigated the prevention and management of diabetes during pregnancy, indicating that the efficacy of inositol in preventing and treating GDM is comparable to that of metformin[41]. Moreover, inositol, either as a monotherapy or in conjunction with probiotics and a Mediterranean diet, has achieved significant outcomes in the prevention and treatment of GDM[42-44].

Our study has several strengths. To our knowledge, the current study is the first comprehensive analysis exploring the impact of inositol supplementation on GDM. The present article adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, ensuring the transparency and reproducibility of our research. Nevertheless, the limitations of the present study should be acknowledged. Considering the small number of included studies, a certain degree of publication bias was inevitable. Thus, further meta-analytic research should be conducted in this area. The quality of primary studies included in the meta-analysis was mixed, and the quality of the meta-analysis was moderate, highlighting the need for high-quality studies in the future. Additionally, future meta-analyses should separately evaluate MI or DCI, as these two supplements may have different effects. In addition, different treatment dosages should be analyzed. Given that the primary population included in the meta-analysis comprises high-risk individuals for GDM and those diagnosed with GDM, the impact of inositol on other reproductive health conditions in women could not be ascertained. Consequently, future research should focus on exploring other conditions to provide a more comprehensive understanding of the roles of inositol.

In light of our meta-analytical findings, women at a higher risk of GDM, as well as those diagnosed with GDM, may consider inositol supplementation. This includes women with a history of GDM, those who are obese, or individuals with a strong familial predisposition to diabetes. Recommendations stratified by risk status: (1) High-risk women: 1-4 g MI from 1^st trimester; and (2) Diagnosed GDM: Maintain standard therapy (lifestyle/insulin). However, the therapeutic application of inositol in diagnosed populations requires further RCTs[45]. Specifically, the optimal time to initiate inositol supplementation is from the early second trimester of pregnancy for high-risk women, such as those with obesity, a history of GDM, or a strong family predisposition to diabetes, as this period corresponds to the peak risk of GDM development. Supplementation should be discontinued upon stabilization of glycemic levels or progression into the third trimester[46,47]. Inositol shows promising potential, particularly among high-risk groups. Still, its broad application across all pregnancies necessitates further research. Future studies should focus on optimizing dosing regimens and identifying the patient populations that are most likely to benefit from this intervention.

CONCLUSION

This study meticulously examined and consolidated findings from 12 meta-analyses to evaluate the efficacy of inositol supplementation as a preventive and therapeutic intervention for GDM. After accounting for baseline comparability, our results demonstrate a significant correlation between inositol supplementation and a substantial reduction in the incidence of GDM. Moreover, our findings reveal a positive influence on metabolic parameters in women, including FPG, 1-hour OGTT, 2-hour OGTT, preterm birth rates, PIH, neonatal hypoglycemia, and the occurrence of cesarean sections. However, the conclusions of this study should be interpreted in the context of the methodological quality and heterogeneity of the research. The quality of the included meta-analyses was assessed using the AMSTAR 2 tool, revealing significant variation. Therefore, the results should be interpreted with caution, and more high-quality studies may be needed to confirm the findings. Moreover, the significant heterogeneity observed in this study may stem from various factors, including different inositol dosages, treatment durations, study designs, and differences in participant baseline characteristics. The pooled analysis of inositol isomers, while clinically relevant, limits definitive conclusions on differential effects of MI compared to DCI. Despite the relatively balanced baseline characteristics, most studies have not systematically reported dietary patterns.

Nonetheless, our study results provide robust evidence for the potential of inositol as a preventive and therapeutic agent for GDM. As a safe and potentially effective nutritional supplement, the mechanisms underlying the positive effects of inositol on insulin sensitivity and reducing blood glucose levels offer new perspectives for the management of GDM. Furthermore, considering the long-term impacts of GDM on maternal and fetal health, inositol supplementation, as a non-pharmacological intervention, may provide a novel strategy for the prevention of GDM and its complications. All studies-initiated inositol supplementation in the early stages of pregnancy (≤ 16 weeks; Table 2), whereas GDM is typically diagnosed between 24-28 weeks of gestation. This time gap resulted in a reduced GDM incidence of 63% (RR: 0.37; 95%CI: 0.32-0.42), mainly reflecting prevention efficiency. Currently, for treatment purposes, no evidence supports the supplementation after GDM diagnosis. Future trials should be specifically targeted at this population.

Future research should focus on well-designed, adequately powered, multicenter, randomized controlled clinical trials to evaluate the effects of different dosages and types of inositol supplementation on the prevention and treatment of GDM. Additionally, research should address the long-term safety of inositol supplementation, cost-effectiveness analysis, and its generalizability across different ethnicities and geographical regions. Future studies will provide a more comprehensive understanding of the role of inositol in GDM management and offer precise guidance for clinical practice. In summary, this umbrella review of systematic review provides scientific evidence for the potential application of inositol supplementation in the prevention and treatment of GDM, while emphasizing the need for more high-quality research to further validate these findings.

ACKNOWLEDGEMENTS

The authors would like to thank Jun-Feng He of the Second Affiliated Hospital of South China University for a helpful discussion on topics related to this work. Dan Zi of the Department of Rehabilitation of the First Affiliated Hospital of Sun Yat-sen University and Tian-Tian Wei of the Qilu Medical College of Shandong University provided key help in data extraction and analysis in the research. Additionally, Ru-Tong Wang would like to express his sincere gratitude to Ying-Qi Feng for her patience, care, and unwavering support.