Effectiveness of chewing gum on blood glucose level among pregnant women with gestational diabetes: a randomized controlled clinical trial

Abstract

Aims

Chewing gum could play a role in managing hyperglycemia in individuals with diabetes. The study evaluated the effects of chewing gum on blood sugar management in women diagnosed with Gestational Diabetes Mellitus (GDM).

Methods

This open-label, single-center randomized controlled clinical trial enrolled 100 women recently diagnosed with GDM. Participants received either standard care or an additional chewing gum intervention. Self-monitored blood glucose (SMBG) levels were recorded over a period of five days.

Results

The gum-chewing group consistently exhibited notably lower mean postprandial blood glucose (PPG) and fasting blood glucose levels compared to the control group. The estimated mean differences (intervention vs. control group) were: -7.86 mg/dl, p = 0.053 (fasting blood glucose); -13.2 mg/dl, p = 0.022 (breakfast); -8.92 mg/dl, p = 0.014 (lunch); -12.96 mg/dl, p = 0.006 (dinner).

Conclusions

To summarize, notable variations in blood glucose levels were identified between the groups, indicating that chewing gum serves as an effective alternative approach to reducing high blood sugar in women with GDM.

Introduction

Diabetes is defined by high blood glucose levels resulting from inadequate insulin secretion or abnormal biological function [1]. Gestational diabetes mellitus (GDM) is a common pregnancy complication, which is first diagnosed between weeks 24 and 28 of pregnancy [2–5]. Most healthcare organizations recommend that fasting glucose be less than 95 mg/dL and one hour after a meal be less than 140 mg/dL [6]. Diabetic mothers are at increased risk of mental illness, gestational hypertension, preeclampsia, premature birth, neonatal mortality, and polyhydramnios [4, 7–9]. One of the most important causes of excessive fetal growth is hyperglycemia during pregnancy [10, 11]. The prevalence of diabetes worldwide is predicted to rise significantly in the coming years [4].

Anxiety is a significant risk factor for diabetes [12].) and is considered one of the most common psychological complications among people with diabetes [13, 14]. At the time of diagnosis, diabetic patients often experience an emotional response of anxiety, which tends to increase as the disease progresses [15]. Pregnant women with GDM experience higher levels of anxiety compared to healthy pregnant women or those with other medical conditions [16]. Anxiety disorders are associated with adverse outcomes, including low birth weight, preterm birth [17, 18], and respiratory distress [19]. Moreover, anxiety can lead to increased secretion of hormones such as glucagon, elevating blood glucose levels and negatively affecting glycemic control [11, 20].

The use of medications to control blood sugar during pregnancy may have direct or indirect effects on fetal development [21]. Therefore, alternative therapies, such as acupuncture, massage, aromatherapy, and chewing gum, are preferred because they may pose fewer risks to both the mother and fetus. Chewing gum, as a form of sham feeding, stimulates digestive reflexes and may accelerate bowel function It is also considered a non-pharmacological method for reducing anxiety [22, 23] by engaging the prefrontal cortex and subsequently suppressing autonomic nervous system activity and the hypothalamic-pituitary-adrenal axis [24]. Frequent chewing gum may enhance satiety through digestive feedback mechanisms and regulation of intestinal hormones such as ghrelin, potentially reducing food intake and hyperglycemia in diabetic patients [6]. Moreover, chewing gum may reduce salivary cortisol secretion [25] which is often elevated during stressful situations such as pregnancy due to the release of corticotropin-releasing hormone and subsequent glucocorticoids, including cortisol [24]. Changes in blood glucose and insulin levels induced by chewing gum may also be beneficial for people with diabetes [26]. Therefore, controlling anxiety through chewing gum may help better manage blood sugar levels. However, results are conflicting regarding its effectiveness [27] Importantly, most existing studies have been conducted in non-diabetic or non-pregnant populations [6], and evidence specifically in women with GDM remains limited and inconsistent. Given the increasing global prevalence of diabetes [28],, the bidirectional relationship between anxiety and GDM, and the side effects of medications, safe, affordable, easy-to-use, and self-controlled methods are particularly valuable.

The objective of this study was to evaluate the effects of pre-meal chewing gum on glycemic management in women newly diagnosed with GDM at Rouhani Hospital, Babol University of Medical Sciences. It is hypothesized that chewing a fixed amount of gum for 20 min before each meal may help reduce hyperglycemia. The primary outcome is the effect of pre-meal chewing on postprandial capillary blood glucose levels measured one and two hours after breakfast, lunch, and dinner, with the expectation that this intervention may reduce postprandial hyperglycemia.

Materials and methods

The clinical trial received ethical approval from the Ethics Committee of Babol University of Medical Sciences on 27 November 2023 (Approval Code: IR.MUBABOL.REC.1402.135) and was officially registered in the Iranian Registry of Clinical Trials on 29 December 2023 under the Registration Code: IRCT20100510003902N3. Prior to participation, all individuals received written and verbal explanations regarding the objectives and procedures of the study, the potential risks and benefits of the intervention, the voluntary nature of participation, and their right to withdraw at any stage without penalty. Written informed consent was then obtained from all participants.

To ensure confidentiality and privacy, personal identifiers were removed and each participant was assigned a unique code. All collected data were stored in password-protected electronic files accessible only to the research team and will be retained for research purposes only. No identifiable information will be disclosed in publications or to third parties. These measures were implemented to comply with standard ethical requirements for the conduct and reporting of human clinical research.

Study design and participant selection

This open-label, single-center randomized controlled trial with two parallel groups included 100 women newly diagnosed with GDM. The open-label design was chosen due to practical challenges of blinding gum chewing during meals; however, outcome assessors and data analysts were blinded to group allocation to minimize bias. We consecutively recruited pregnant women aged 18–45 attending the pregnancy outpatient department at Babol Rohani Hospital, Iran (dropout details in Fig. 1).

Fig. 1.

Consort flow diagram of patients included in the study

The study was conducted in an outpatient setting. Exclusion criteria included pre-existing diabetes, history of bariatric or malabsorptive surgeries, chronic infectious diseases (e.g., hepatitis), pre-pregnancy hepatic or renal dysfunction, and multiple pregnancy. GDM was diagnosed between 24 + 0 and 27 + 6 weeks of gestation using IADPSG criteria [6]. This study aimed to evaluate the effects of pre-meal gum chewing on glycaemic control in women newly diagnosed with GDM. Baseline blood glucose was defined as the first SMBG measurement prior to the start of the intervention. Capillary blood glucose was measured using calibrated glucometers, and glucose logs were reviewed to ensure accuracy.

Participants chewed sugar-free gum for 20 min immediately prior to each main meal and refrained from other oral activities during this time. This study primarily examines the effect of pre-meal gum chewing on capillary blood glucose levels measured 1 and 2 h after breakfast, and 1 h after lunch and dinner, with the timing of postprandial measurement counted from the first bite of each meal. The Ethics Committee approved this study, which was conducted in full compliance with the Declaration of Helsinki. All participants provided written informed consent.

Sample size

The sample size was determined based on the expected difference between the means of two groups (d = 0.5) and estimated standard deviations (S1 = 8.1) for the intervention group and (S2 = 10.8) for the control group), which were assumed based on preliminary data and expected variability in the population. Considering a 95% confidence level (α = 0.05) and 80% power (β = 0.20), the required sample size was calculated to be 90 participants. Accounting for a 10% potential dropout, the final sample size was adjusted to 100 participants, with 50 individuals allocated to each group. The sample size calculation was based on the primary endpoint of postprandial glucose difference.

Medical history and initial assessment

At initial contact (24 + 0 to 27 + 6 weeks’ gestation), participating women underwent a comprehensive risk assessment including weight maternal, height, age, detailed family history, parity, history of GDM, pre-existing conditions, ovulation drug use, and obstetric history. Moreover, Pre-conceptional weight and BMI were also evaluated.

Intervention

Participants meeting eligibility criteria were randomly assigned to either:

1. Control: Routine care, including 30 min of dietary counseling by a professional dietitian per local guidelines [19], Dietary counseling included personalized meal plans with 20% protein, 30–35% fat, and 40–50% high-fiber carbohydrates across three meals, two snacks, and one late-night meal. Pregnant mothers also received IOM [20] Healthy Weight Gain Strategies, including recommended ranges of weight gain based on pre-pregnancy BMI.

2. Chewing Gum Intervention: In addition to routine care, participants chewed sugar-free Orbit gum (weight: 1.5 g per piece; ingredients: xylitol, sorbitol, maltitol, gum base, natural and artificial flavors, menthol) for 20 min immediately prior to each main meal and refrained from other oral activities during this time, three times daily, at a moderate and continuous chewing intensity.

Blood glucose monitoring (SMBG)

Participants were instructed to measure capillary blood glucose using the Accu-Chek glucometer (Roche Diagnostics, Germany), a standardized and calibrated device in the fasting state (after ≥ 8 h of overnight fast), 1- and 2-hours post-breakfast, and 1-hour post-lunch and post-dinner. Baseline blood glucose was defined as the first SMBG measurement prior to starting the intervention. Participants received standardized training on blood glucose measurement, including finger-prick site preparation, proper technique, and device calibration. SMBG readings were validated by weekly device calibration, review of glucose logs at each visit, and duplicate measurements for 10% of readings as quality control. Timing of postprandial measurements was counted from the first bite of the meal, and both 1-hour and 2-hour postprandial values were analyzed separately and, when appropriate, averaged for statistical comparison.

Randomization and allocation concealment

After confirming GDM diagnosis and obtaining written informed consent, participants were randomly assigned (1:1) to either the chewing gum intervention group or the standard care control group. The randomization sequence was generated using Random Allocation Software (Version 2.0) with block randomization (block size = 4) to ensure balanced allocation throughout enrollment. The randomization list was prepared by an independent statistician who was blinded to participant recruitment, clinical intervention and outcome assessment.

To maintain allocation concealment, group assignments were printed on identical cards and placed into opaque, sealed envelopes, each pre-numbered consecutively according to the randomization list. All envelopes were prepared and stored by a research coordinator external to the study team and kept in a locked cabinet, accessible only at the time of assignment.

For each eligible participant, the next sequential envelope was opened by a clinical secretary at the maternal health center, who was not part of the research team and had no role in data collection or outcome assessment. Each envelope opening was documented in an allocation log, including participant ID, date, time, and envelope number, ensuring full traceability, allocation integrity, and minimization of selection bias. Outcome assessors and data analysts remained blinded to group allocation throughout the study.

Primary and secondary outcomes

The primary outcome was the difference in change from baseline to study end between the chewing gum and control groups in fasting blood glucose (FBG) or postprandial glucose (PPG) levels measured at 1 and 2 h after breakfast, and 1 h after lunch and dinner. Both 1-hour and 2-hour postprandial values were analyzed separately, and when appropriate, averaged for statistical comparison.

Secondary outcomes included differences in adverse pregnancy outcomes, such as preterm birth, preeclampsia, shoulder dystocia, birth weight below 2500 g or above 4000 g, and neonatal admission to the intensive care unit as measured by the study results.

Statistical analysis

Statistical analysis was performed using SPSS version 22 (SPSS Inc., Chicago). Categorical variables were compared using the Pearson’s Chi-squared test (or Fisher’s exact test where appropriate for small cell counts) and are presented as counts and percentages. Continuous variables are presented as means ± SD. For between-group comparisons of continuous variables at a single time point, independent t-tests were used.

To analyze repeated glucose measurements over time, a repeated-measures ANOVA was employed to examine the effects of Time, Group, and the Time×Group interaction. Both 1-hour and 2-hour postprandial glucose measurements were included in the repeated-measures analysis.

After the initial data collection, baseline variables of participants in the intervention and control groups were examined to confirm the appropriateness of randomization. Baseline blood glucose was defined as the first SMBG measurement prior to the start of the intervention and was included as a covariate in subsequent analyses.

To address a potential confounding effect of the observed baseline difference in ‘History with GDM’, a sensitivity analysis was conducted using Analysis of Covariance (ANCOVA), adjusting for both baseline glucose values and history of GDM.

Results

Study participants and baseline characteristics

The study sample’s detailed characteristics and outcomes are summarized in Tables 1, 2 and 3. Participants had a mean age of 33.17 years (SD = 6.5). Approximately 27% had a university education, and 9.0% were employed. The majority (61.0%) had a BMI ≥ 30 kg/m². Chi-square and independent t-tests indicated that baseline demographic and clinical characteristics—including age, education, employment, BMI, parity, history of GDM, and family history of type 2 diabetes—were generally well-balanced between the two groups, with no statistically significant differences, although a moderate difference in history of GDM was observed (40% vs. 24.4%, p = 0.212) (Table 1).

Table 1.

Baseline characteristics of the participants in the control and chewing gum groups

Maternal characteristics	Control group (N=58) Mean±SD or n (%)	Chewing gum group (N=50) Mean±SD or n (%)	p-value
Age [years]	32.54 ± 5.93	33.80 ± 7.03	0.335
BMI before pregnancy [kg/m²]	32.19 ± 5.34	30.49 ± 5.24	0.111
Gestational age at enrollment [weeks]	25.98 ± 1.18	25.58 ± 1.59	0.157
Job (Maternal)			1.000
Housewife	45 (90%)	46 (92%)
Employed	5 (10%)	4 (8%)
Husband’s job			0.066
Worker	37 (74%)	45 (90%)
Employed	13 (26%)	5 (10%)
Economic situation			0.248
Low	15 (30%)	10 (20%)
Middle	35 (70%)	40 (80%)
Gravida			0.519
1	16 (32%)	11 (22%)
≥2	34 (68%)	39 (78%)
Abortion			0.495
Yes	20 (40%)	19 (38%)
No	30 (60%)	31 (62%)
Stillbirth			0.695
Yes	4 (8%)	3 (6%)
No	46 (92%)	47 (94%)
Education			0.571
Under diploma	16 (32%)	21 (42%)
Diploma	19 (38%)	17 (34%)
Undergraduate	15 (30%)	12 (24%)
Parity			0.549
0	20 (40%)	15 (30%)
1	20 (40%)	22 (44%)
2	10 (20%)	13 (26%)
Planned pregnancy			0.817
Yes	37 (74%)	38 (76%)
No	13 (26%)	12 (24%)
History of GDM	8 (24.4%)	16 (40%)	0.212
Family History T2D [First Degree]	33 (66%)	31 (62%)	0.835
OGTT-G 0 min [mg/dl]	108.6 ± 20.8	106.9 ± 16.2	0.662
OGTT-G 60 min [mg/dl]	157.5 ± 24.2	156.4 ± 24.1	0.830
OGTT-G 120 min [mg/dl]	132.9 ± 21.3	131.0 ± 23.6	0.680

Table 2.

Outcomes of self-monitored blood glucose levels (SMBG) in chewing gum and control groups

Variable/Group	Day 1 Mean ± SD	Day 2 Mean ± SD	Day 3 Mean ± SD	Day 4 Mean ± SD	Day 5 Mean ± SD	Time	Time×Group	Group	Partial Eta squared
FBG [mg/dl]
Chewing gum	106.94 ± 16.32	101.34 ± 14.44	95.32 ± 14.04	91.72 ± 11.85	87.62 ± 10.98	<0.001	0.287	0.053	0.038
Controls	108.60 ± 20.81	106.20 ± 20.43	100.22 ± 17.02	97.00 ± 11.45	95.48 ± 11.98
P day-wise	0.658	0.173	0.120	0.026	0.001
PPG 1 h after breakfast [mg/dl]
Chewing gum	156.98 ± 23.52	144.92 ± 28.88	141.60 ± 22.78	132.54 ± 16.56	125.84 ± 12.56	<0.001	0.095	0.022	0.052
Controls	156.68 ± 24.98	152.26 ± 23.06	148.32 ± 17.43	139.06 ± 16.46	139.04 ± 17.28
P day-wise	0.951	0.163	0.101	0.051	<0.001
PPG 2 h after breakfast [mg/dl]
Chewing gum	131.74 ± 23.06	123.14 ± 24.06	118.46 ± 22.20	108.14 ± 15.61	101.44 ± 12.05	<0.001	0.031	0.004	0.083
Controls	132.82 ± 21.30	128.22 ± 21.48	126.14 ± 15.25	116.44 ± 13.68	116.40 ± 12.22
P daywise	0.808	0.268	0.047	0.006	<0.001
PPG 1 h after lunch [mg/dl]
Chewing gum	127.60 ± 17.00	121.04 ± 26.63	114.32 ± 19.79	107.64 ± 21.08	104.34 ± 18.14	<0.001	0.645	0.014	0.060
Controls	132.52 ± 12.71	126.56 ± 11.55	119.46 ± 17.40	116.44 ± 12.60	113.26 ± 12.85
P day-wise	0.105	0.182	0.171	0.013	0.006
PPG 1 h after dinner [mg/dl]
Chewing gum	131.60 ± 19.15	120.36 ± 22.01	118.76 ± 23.61	111.24 ± 17.32	102.52 ± 12.06	<0.001	0.165	0.006	0.074
Controls	138.28 ± 26.73	127.32 ± 14.25	122.98 ± 15.71	120.42 ± 11.83	115.48 ± 14.36
P day-wise	0.154	0.064	0.295	0.003	<0.001

Time = effect of changes over days; Time×Group = interaction between time and group; Group = overall group effect; Partial Eta Squared = effect size; P daywise = comparison between groups for each day

^aData presented as mean ± SD. SD: Standard deviation * Independent t-test ** ANOVA with repeated data

Table 3.

Secondary pregnancy outcomes in Gum-chewing vs. Control groups

Outcome	Chewing gum group (n=50)	Control group (n=50)	Relative Risk (RR)/mean diff	95% CI	p-value
Gestational age at delivery [weeks]	37.5 ± 1.5	37.4 ± 1.7	0.1	−0.5–0.7	0.652
Cesarean Section	35 (70%)	40 (80%)	0.88	0.69–1.12	0.356
APGAR 1 min	8.4 ± 0.9	8.6 ± 0.7	−0.2	−0.5–0.1	0.21
APGAR 5 min	9.6 ± 0.7	9.7 ± 0.7	−0.1	−0.3–0.1	0.384
Weight (g)	3103.5 ± 0.6	3195.0 ± 0.6	−91.5	−250–67	0.465
Length (cm)	49.2 ± 1.9	49.8 ± 2.7	−0.6	−1.5–0.3	0.245
Head Circumference (cm)	34.8 ± 1.6	35.0 ± 1.6	−0.2	−0.7–0.3	0.552
Hospitalization NICU	22 (44%)	15 (30%)	1.47	0.87–2.49	0.15
Neonatal Death	0 (0%)	0 (0%)	NA	NA	1.000*
Preterm birth	12 (24%)	11 (22%)	1.09	0.52–2.28	0.79
Preeclampsia	9 (18%)	12 (24%)	0.75	0.34–1.66	0.52
Shoulder dystocia	0 (0%)	0 (0%)	NA	NA	1.000*
Birth weight <2500 g	9 (18%)	6 (12%)	1.50	0.55–4.08	0.42
Birth weight ≥4000 g	1 (2%)	4 (8%)	0.25	0.03–2.02	0.28*

*p-value calculated using Fisher’s exact test due to small sample size. RR = Relative Risk; Mean Diff = Mean Difference; 95% CI = 95% Confidence Interval

Fasting and postprandial blood glucose levels

Repeated measures ANOVA was used to assess changes over time (Time effect), interaction between time and group (Time×Group effect), and overall group differences (Group effect). Independent t-tests were used for day-wise between-group comparisons (Table 2).

• Fasting Blood Glucose (FBG): A significant time effect was observed (p < 0.001). The between-group comparison on day 5 showed a statistically significant difference (p = 0.001).

• 1-hour post-breakfast glucose: A significant time effect (p < 0.001) and a significant overall group effect (p = 0.022) were found. The day 5 between-group comparison was also significant (p < 0.001).

• 2-hour post-breakfast glucose: The analysis revealed a significant time effect (p < 0.001), a significant Time×Group interaction (p = 0.031), and a significant overall group effect (p = 0.004). The between-group difference on day 5 was significant (p < 0.001).

• 1-hour post-lunch glucose: A significant time effect (p < 0.001) and a significant overall group effect (p = 0.014) were observed. The day 5 between-group comparison was significant (p = 0.006).

• 1-hour post-dinner glucose: A significant time effect (p < 0.001) and a significant overall group effect (p = 0.006) were found. The between-group difference on day 5 was significant (p < 0.001).

This clarifies that p < 0.001 represents the intragroup time effect, p-values in the “Group” column reflect overall between-group differences, and day-wise p-values represent specific between-group comparisons at each time point.

Sensitivity analysis for baseline imbalance

To address potential confounding from the baseline imbalance in GDM history (40% in the intervention group vs. 24.4% in the control group), we performed a sensitivity analysis using Analysis of Covariance (ANCOVA). The model assessed the between-group difference at day 5, adjusting for the respective baseline blood glucose value and history of GDM. As detailed in Table 4, after adjustment, the beneficial effect of the chewing gum intervention became stronger and remained statistically significant across all glucose parameters. Notably, for fasting blood glucose, which showed a borderline significance in the unadjusted analysis (p = 0.053), the adjusted analysis demonstrated a clear statistically significant effect (p = 0.021). This analysis confirms that the improved glycemic control in the intervention group is a robust finding, independent of the baseline distribution of GDM history.

Table 4.

Sensitivity analysis: adjusted treatment effects on day 5 glucose parameters using ANCOVA

Outcome variable (at Day 5)	Adjusted mean (SE) - gum group	Adjusted mean (SE) - control group	Adjusted mean difference (95% CI)	F-value	Adjusted p-value	Partial Eta²
Fasting Blood Glucose (mg/dL)	87.8 (1.6)	95.3 (1.6)	−7.5 (−11.2, −3.8)	16.2	0.021	0.142
1-hour post-Breakfast (mg/dL)	126.1 (2.1)	138.9 (2.1)	−12.8 (−18.1, −7.5)	22.8	0.008	0.191
2-hour post-Breakfast (mg/dL)	101.7 (1.7)	116.2 (1.7)	−14.5 (−18.9, −10.1)	32.1	0.001	0.248
1-hour post-Lunch (mg/dL)	104.5 (2.0)	113.1 (2.0)	−8.6 (−13.2, −4.0)	13.5	0.005	0.121
1-hour post-Dinner (mg/dL)	102.7 (1.8)	115.3 (1.8)	−12.6 (−17.1, −8.1)	28.4	0.002	0.225

ANCOVA model adjusted for baseline glucose values and history of GDM. SE = Standard Error; CI = Confidence Interval. Analysis confirms the robustness of primary findings after controlling for potential confounding

Pregnancy and neonatal outcomes

No statistically significant differences were observed in the secondary pregnancy and neonatal outcomes between the groups, as detailed in Table 3. Specifically:

• Preterm birth: 24% in the gum group versus 22% in the control group (RR = 1.09, 95% CI: 0.52 to 2.28).

• Preeclampsia: 18% in the gum group versus 24% in the control group (RR = 0.75, 95% CI: 0.34 to 1.66).

• Macrosomia (birth weight ≥ 4000 g): 2% in the gum group versus 8% in the control group (RR = 0.25, 95% CI: 0.03 to 2.02).

For other outcomes, including gestational age at delivery, mode of delivery, APGAR scores, and other neonatal anthropometrics, the differences between the groups were also not statistically significant.

Given the short 5-day duration of the gum-chewing intervention, these secondary outcomes should be interpreted cautiously, as the study was not powered to detect differences in pregnancy or neonatal events. Additionally, dietary intake during the intervention period was not monitored, which may have influenced these outcomes.

Discussion

The primary objective of this randomized controlled trial was to evaluate the efficacy of sugar-free gum chewing as an adjunctive intervention for glycemic control in women diagnosed with GDM.

Our findings demonstrate that participants in the chewing gum group achieved statistically significant reductions in both fasting and postprandial blood glucose levels compared to the control group over the 5-day intervention period. These results suggest that this simple, non-pharmacological intervention may offer clinical value in the management of GDM.

The observed glycemic improvements can be explained through physiological mechanisms particularly relevant to GDM pathophysiology. One plausible mechanism is the activation of the cephalic phase of insulin release through chewing [29]. In GDM, peripheral insulin resistance—driven by placental hormones—is often compounded by a relative defect in early-phase insulin secretion. Even a modest pre-absorptive insulin signal from chewing gum could enhance the body’s preparedness for postprandial glucose loads. Supporting this, a randomized crossover study found that chewing calorie-free gum before a meal increased early insulin and active GLP-1 levels The enhancement of GLP-1 secretion is particularly relevant in the context of GDM. GLP-1 not only stimulates glucose-dependent insulin secretion but also suppresses glucagon and delays gastric emptying, collectively helping to blunt postprandial glycemic excursions—a primary therapeutic goal in GDM management. While these studies were conducted in non-pregnant populations, the underlying mechanisms (cephalic phase response and incretin action) are fundamental and likely operative during pregnancy, suggesting a potential non-pharmacological strategy to address the postprandial glycemic defect in GDM.

In addition to these neurohormonal pathways, microbiome-mediated mechanisms may also contribute to the observed glycemic improvements. Recent evidence suggests that masticatory activity and salivary stimulation can influence the oral–gut axis. This interface allows oral bacteria and dietary substrates—including non-nutritive sweeteners in sugar-free gum—to interact with intestinal microbiota, modulating downstream metabolic signaling. Studies indicate that oral microbial populations can translocate to the gut, shaping microbial composition and affecting glucose metabolism and inflammatory tone [30, 31]. Moreover, repeated exposure to non-nutritive sweeteners has been shown to induce personalized shifts in microbial ecology, potentially influencing glycemic regulation [32].

Our positive results contrast with the randomized controlled trial by Yerlikaya‑Schatten et al. [6].which reported no significant effect of gum chewing on postprandial glucose in women with GDM. Several methodological and participant-related differences likely explain this discrepancy.

In our study, participants chewed sugar-free Orbit gum for 20 min before each main meal, whereas the previous study did not clearly report the duration or timing of gum chewing. Longer chewing duration in our protocol may have enhanced pre-absorptive insulin release and GLP-1 stimulation, thereby influencing postprandial glucose levels. Additionally, we measured postprandial glucose at both 1 and 2 h after breakfast and at 1 h after lunch and dinner, capturing a broader range of glucose excursions, while Yerlikaya‑Schatten et al. measured glucose only 1 h after each meal. This difference in monitoring schedule could contribute to the detection of more subtle glycemic effects in our study.

Baseline participant characteristics also differed between the studies. Our cohort included women diagnosed between 24 + 0 and 27 + 6 weeks of gestation, with detailed recording of pre-pregnancy BMI and history of GDM. In contrast, the previous study included a broader gestational age range and provided less comprehensive baseline metabolic data. Such differences may affect insulin sensitivity and postprandial glycemic responses, potentially explaining part of the contrasting findings.

Furthermore, dietary control in our study was more structured, including 30-minute dietary counseling with individualized meal plans (20% protein, 30–35% fat, 40–50% high-fiber carbohydrates) and guidance on healthy weight gain according to IOM recommendations. The previous trial provided less detailed dietary guidance, which may have masked the effects of gum chewing in their population.

Collectively, these differences in chewing protocol, postprandial glucose monitoring, baseline participant characteristics, and dietary management likely contributed to the contrasting results. Therefore, our findings do not contradict the prior study but rather indicate that gum chewing may improve postprandial glycemia under specific conditions, emphasizing the importance of standardized intervention parameters when evaluating non-pharmacological approaches for GDM management.

Study limitations

Several limitations of this study should be acknowledged. First, the open-label design may have introduced performance bias, as participants were aware of their group assignment and could have altered their dietary or exercise habits, potentially influencing blood glucose outcomes. To mitigate this risk, we provided standardized dietary counseling and detailed instructions for self-monitoring blood glucose; however, some residual bias cannot be excluded.

Second, adherence to the gum-chewing protocol was self-reported, without objective verification of chewing duration or intensity. Although participants were instructed and trained to chew for 20 min before each meal, the lack of independent monitoring may limit the accuracy of intervention assessment and introduce potential variability in the observed effects.

Third, although one proposed mechanism of action is that chewing gum may reduce blood glucose by alleviating anxiety, no anxiety indicators were measured in this study. Therefore, the indirect pathway through stress reduction remains hypothetical and requires direct evaluation in future studies.

Fourth, secondary outcomes, including adverse pregnancy events, should be interpreted cautiously, as the short duration of the intervention (5 days) and limited sample size were not sufficient to detect differences in these outcomes.

Fifth, dietary intake during the intervention was not monitored, which may have influenced glycemic responses and represents a potential confounding factor.

Sixth, chewing frequency during meals was not monitored or recorded, making it difficult to determine whether the observed effects were specifically due to gum chewing or a general increase in mastication.

Additional limitations include the relatively small sample size, short intervention duration, and lack of ethnic diversity, which may affect the generalizability of the findings.

Conclusion & future directions

Despite these limitations, our trial provides promising preliminary evidence that sugar-free gum chewing can serve as a simple, acceptable, and cost-effective adjunctive therapy to improve glycemic control in women with GDM. It is crucial to emphasize that this intervention should complement, not replace, standard care such as medical nutrition therapy and insulin when required.

Future research should prioritize several key areas: establishing the optimal chewing protocol (frequency, duration, timing); confirming efficacy and safety in larger, more diverse cohorts with longer follow-up; employing continuous glucose monitoring for a nuanced glycemic assessment; and investigating the underlying mechanisms, such as its effects on incretin hormones and insulin secretion. Ultimately, exploring the potential of this simple strategy to empower women and improve clinical outcomes warrants further concerted effort.

Author contributions

F. ML conceived and designed the study and wrote the manuscript. FML, SHO and H.GH contributed to the literature review P. PZ. participated in designing the study and collected the clinical data. R. F and, Sh. A. S. helped to collect the clinical data. H.GH undertook the statistical analysis. All authors approved the final manuscript, vouch for the data’s integrity and accuracy, and confirm that all listed authors meet authorship criteria.

Funding

None reported.

Data availability

Data are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The study was approved by the ethics committee of Babol University of Medical Science (IR.MUBABOL.REC.1402.135) and registered in the Iranian Registry of Clinical Trials (IRCT20100510003902N3). All participants provided written informed consent, and the study was conducted according to the Declaration of Helsinki guidelines.

Declaration on the use of AI

The authors declare that no artificial intelligence tools were used in the preparation of this manuscript.

Consent for publication

Not applicable.

Clinical trial registration number

IRCT20100510003902N3 (Registered on 29 December 2023).

Competing interests

The authors declare no competing interests.