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Article

A Randomized Crossover Study Comparing the Effects of Diabetes-Specific Formula with Common Asian Breakfasts on Glycemic Control and Satiety in Adults with Type 2 Diabetes Mellitus

by
Sing Teang Kong
1,*,
Dieu Thi Thu Huynh
1,
Weerachai Srivanichakorn
2,
Weerapan Khovidhunkit
3,
Chaiwat Washirasaksiri
2,
Tullaya Sitasuwan
2,
Chengrong Huang
4,
Swapnil Paunikar
5,
Menaka Yalawar
6 and
Siew Ling Tey
1
1
Abbott Nutrition Research and Development, Asia-Pacific Centre, Singapore 138668, Singapore
2
Division of Ambulatory Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
3
Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Bangkok 10330, Thailand
4
Abbott Nutrition Research and Development, Shanghai 200233, China
5
Biostatistics and Statistical Programming, Life Sciences-Digital Business Operations, Cognizant Technology Solutions India Private Limited, Pune 411057, India
6
Biostatistics and Statistical Programming, Life Sciences-Digital Business Operations, Cognizant Technology Solutions India Private Limited, Bengaluru 560092, India
*
Author to whom correspondence should be addressed.
Diabetology 2024, 5(4), 447-463; https://doi.org/10.3390/diabetology5040033
Submission received: 12 July 2024 / Revised: 6 September 2024 / Accepted: 11 September 2024 / Published: 19 September 2024
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Abstract

:
Postprandial hyperglycemia was shown to be an independent risk factor for microvascular and macrovascular complications in type 2 diabetes mellitus (T2D). We aimed to investigate the glucose, insulin, and subjective appetite at 0, 15, 30, 45, 60, 90, 120, 150, and 180 min of three treatments: diabetes-specific formula (DSF), noodle soup, and glutinous rice. This was a randomized, crossover study with a one-week interval between treatments. Sixty-four T2D adults with oral glucose-lowering medication and HbA1c between 7% and <10% were randomized. The glucose positive area under the curve from 0 to 180 min (pAUC) was significantly lower with DSF than with glutinous rice (LSM ± SE: DSF 354 ± 32 vs. glutinous rice 451 ± 32 mmol.min/L, p = 0.033). The insulin pAUC was significantly lower with DSF (median [IQR]: 2733 [1542, 4204]) compared to glutinous rice (3359 [2193, 4744] µIU.min/mL), p = 0.042). The insulinogenic index at 30 min was significantly higher in DSF (median [IQR], 8.1 [4.2, 19.7]) compared to glutinous rice (5.4 [2.7, 11.7], p < 0.001). No significant differences were found in subjective appetite between the three treatments (all, p ≥ 0.827). There were also no significant differences in hunger, fullness, desire to eat, and prospective consumption ratings between DSF and the other two breakfasts (all p ≥ 0.181). Noodle soup led to the shortest time for hunger to return to baseline (165 min), 21 min earlier than DSF (186 min) and 32 min earlier than glutinous rice (197 min). DSF significantly reduced postprandial glucose and insulin responses compared with glutinous rice and had a higher satiating value than noodle soup in T2D adults. Replacing common Asian breakfasts with DSF may improve glycemia and hunger control.

1. Introduction

The worldwide prevalence of diabetes is alarming and projected to increase significantly by 2045, particularly in the Southeast Asia region [1]. Characterized by insulin resistance and a progressive decline in insulin secretion, type 2 diabetes mellitus (T2D) is the most prevalent form of diabetes, comprising more than 90% of all cases [1,2].
Postprandial hyperglycemia, a common feature of T2D, reflects the challenge for patients to attain the American Diabetes Association (ADA) peak postprandial plasma glucose (PPG) target of less than 10.0 mmol/L (<180 mg/dL) within 1 to 2 h after ingesting a meal [3]. Postprandial hyperglycemia was shown to be an independent risk factor for microvascular and macrovascular complications in T2D [4]. In individuals with T2D, inadequate suppression of an excessive rise in PPG could be due to impaired postprandial insulin secretion and reduced insulin sensitivity in peripheral tissues [5].
Given that the postprandial glycemic response is intricately influenced by diet composition, specifically the composition and quantity of food consumed, the implementation of medical nutrition therapy (MNT) becomes imperative, providing a crucial framework for tailoring effective strategies to manage post-meal hyperglycemia in individuals with T2D [6]. MNT is recommended as a part of management strategies for individuals with diabetes in several international guidelines [7,8,9].
Diabetes-specific formulas (DSFs) are specially formulated combinations of macro- and micronutrients to provide complete and balanced nutrition for individuals with T2D. DSFs usually contain slowly digestible carbohydrates, beneficial fats including monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA), and a substantial quantity of protein and dietary fibers. These formulations can be integrated into MNT as meal replacements or snacks, providing palatable, calorie-controlled, and low glycemic index (GI) options [10,11]. Indeed, various mid- to long-term studies have shown that when used as part of MNT in diabetes management, DSF improved glycemic variability [12], HbA1c, weight, visceral adipose tissue, fat mass, and blood pressure [12,13]. DSF use is also associated with improved quality of life [14] and reduced healthcare resources and costs [15].
A multinational long-term cohort study (PURE cohort) had shown that higher GI diets were associated with a higher risk of diabetes (median [IQR], Quintile 5: 90.7 [90.2–91.4] vs. Quintile 1: 76.1 [73.8–77.7]; HR 1·15 [95% CI 1.03–1.29]) [16]. The same study reported that China consumed the highest GI diets, followed by Southeast Asia and Africa. Rice and noodles are common staple foods in Asia. Rice, such as white rice and glutinous rice, are seeds that can be cooked and eaten after the removal from the straw, while noodles are thin and long strips of dough made from wheat flour and water. A previous study evaluating the GI of Asian staples rice and noodles revealed that white rice (GI 80) and wheat-based noodles (GI 74) are classified as high GI food [17].
Asian breakfasts have been found to have higher GI than Western breakfasts [18]. It has been proposed that the high GI of Asian breakfasts, such as rice dosa and rice idli, is partly attributed to the high content of refined rice flour and the low contents of fat, protein, and dietary fiber [18]. The use of DSF as breakfast or meal replacement has been shown to improve postprandial glycemic and insulin responses in individuals with T2D when compared to other breakfasts, such as boiled white rice with chicken [19], oatmeal [20,21], cornflakes with milk [22], and white bread with margarine spread plus milk [23]. Significant reductions were shown in the positive glucose area under the curve (AUC) [19,20,21,22,23] and positive insulin AUC [20,22]. Satiety hormones, such as glucagon, peptide YY, or glucagon-like protein-1 (GLP-1), were significantly higher in the DSF group when compared to boiled rice with chicken [19] or oatmeal [21], while subjective appetite showed no significant differences when compared to cornflakes with milk or oatmeal breakfast [20,22].
To date, the majority of research has focused on comparing DSFs to standard nutritional formulas [24,25] or with isocaloric study breakfasts [19,20,21,22,23] and has shown better glycemic responses in DSFs with comparable satiety. However, regular standard breakfasts consumed by individual with T2D in Asia may vary in portion sizes and macronutrients. To understand the glycemic and satiety responses of DSF compared to commonly consumed breakfasts, this study explored the effects of DSF and two Asian breakfasts, at their actual serving sizes, on postprandial glucose, insulin, and satiety in individuals with T2D.

2. Materials and Methods

2.1. Study Population

Adult participants (≥21 and ≤65 years old) with T2D receiving stable oral glucose-lowering medications and doses for at least 2 months were eligible. Additional inclusion criteria were as follows: (1) body mass index (BMI) > 18.5 and ≤35 kg/m2; (2) male or non-pregnant, non-lactating female, at least 6 weeks postpartum prior to screening visit; (3) if on a chronic medication, no changes in the dosage for at least 2 months prior to screening visit; (4) willingness to adhere to study protocol and refrain from taking any non-study DSF over the study period.
The exclusion criteria were adults with a screening HbA1c level of <7% or ≥10%, type 1 diabetes, requiring insulin therapy, a history of end-stage organ disease, a history of gastrointestinal disease or surgery which can interfere with the consumption and digestion or absorption of the study product, a history of psychiatric disorder that may impair adherence to study protocol, active malignancy, chronic contagious or infectious disease, receiving systemic antibiotics in the last 3 weeks or systemic corticosteroids in the last 3 months, taking any herbals, supplements, or medications (other than allowed glucose-lowering medications) that could profoundly affect blood glucose or appetite, using any other DSF more than one serving per week for the last 3 months and allergy or intolerance (including due to religious restrictions) to any of the study breakfasts.
The study protocol was reviewed and approved by the institutional ethics committee (Faculty of Medicine, Chulalongkorn University IRB COA No. 0548/2023; Faculty of Medicine Siriraj hospital, Mahidol University IRB COA no. Si 278/2023) and registered at ClinicalTrials.gov as NCT05802927. All participants provided signed informed consent before any study procedure was conducted.

2.2. Study Procedures

This was a randomized, controlled, crossover study with three periods and three interventions, (1) DSF Glucerna (Abbott Nutrition), (2) noodle soup, and (3) glutinous rice, administered in a balanced order over a duration of approximately 4 weeks, with a one week washout period between the treatments. Randomization was conducted using a computer-generated sequence, known only to the research staff at the site. Study personnel, who were involved in data management, data analysis, and results interpretation, were blinded to the treatments.
Participants attended a screening visit where their capillary HbA1c and anthropometric measurements were obtained to ensure eligibility. Body weight and height were measured using a calibrated weighing scale and stadiometer to the nearest 0.1 kg and 0.1 cm, respectively. Waist and hip circumferences were measured in duplicates using Lufkin measuring tape W606PM (Apex Tool Group, Querétaro, Mexico) to the nearest 0.1 cm. BMI was calculated using weight (kg) divided by height (m) × height (m) (kg/m2). As part of the meal tolerance test preparation, participants were asked to keep a strict record of the food consumed and activity performed on the day prior to the test days. They were instructed to consume at least 150 g of carbohydrate, avoid alcohol and refrain from strenuous activity on the day prior to the test day. Eligible participants were scheduled to attend the study sites on three separate mornings after an overnight fasting of ≥8 h. At the study site, fasting capillary glucose must be <10 mmol/L before commencing study procedures. In the event that fasting capillary glucose was ≥10 mmol/L, study procedures were canceled, and participants were rescheduled within the next 3 days. A high fasting glucose level could be a sign of uncontrolled diabetes and would require medical attention.
Throughout the entire study duration, participants maintained their usual daily routine for dietary intake and physical activity.

2.3. Study Treatments

The DSF used in this study provided complete and balanced nutrition. It was a low-GI (GI 27) formula featuring a slow-release carbohydrate system with sucromalt, a dual fiber blend (soluble and insoluble fibers), healthy fat (MUFA and PUFA), high quality protein, and enhanced micronutrient blend. Each serving of the DSF provided 212 kcal, 4.5 g fiber, 800 mg myo-inositol, 264 IU vitamin D, 81 µg folic acid, 3.3 mg zinc, 224 mg calcium, 2.6 mg iron, and 40 µg chromium. A generic research study label was placed on the DSF bottle.
The two comparator breakfasts were chosen because noodles and rice are common staple foods in Asian breakfasts. In addition, these were popular local choices, with convenient availability and easy preparation. The energy and compositions of the three study treatments are tabulated in Supplementary Table S1.

2.4. Outcomes

The primary outcome was the differences in the glucose positive area under the curve from 0 to 180 min (pAUC) between the DSF and comparator breakfasts. The secondary outcomes were differences in the insulin positive AUC, glucose and insulin adjusted levels by timepoint, adjusted peak value and peak time, insulinogenic index at 30 min (IGI30), and subjective appetite between the three study treatments.

2.4.1. Glucose and Insulin Response

Prior to study treatment consumption, baseline blood glucose and insulin samples were collected. The morning doses of oral glucose-lowering medications were consumed only at the study site under the supervision of research staff. All participants started consuming each of the study treatment at timepoint zero (t = 0 min). Participants were asked to consume the study treatment together with 250 mL of plain water within 15 min. Subsequent venous blood samples were drawn at 15, 30, 45, 60, 90, 120, 150, and 180 min after t = 0 min for a total of 3 h.
Insulinogenic index (IGI), fasting Homeostasis Model Assessment—Beta-Cell Function (HOMA-β), and fasting Homeostasis Model Assessment—Insulin Resistance (HOMA-IR) were calculated using formulas [26,27] (Supplementary Table S2).

2.4.2. Subjective Appetite

Subjective appetite was collected using the 100 mm visual analog scale with 0 on the scale representing no feeling and 100 representing extreme feeling for 5 questions: hunger, thirst, desire to eat, prospective consumption, and fullness. At 5 min before study treatment consumption, baseline subjective appetite ratings were collected. At every blood sampling timepoint after t = 0 min, participants also rated their subjective appetite concurrently.
Subjective appetite was calculated using the formula [28]:
Desire   to   eat + hunger + ( 100 − fullness ) + prospective   consumption 4

2.4.3. Adverse Events

Treatment-emergent (an adverse event [AE] occurring after the start of study treatment consumption) non-serious and serious AEs are defined by the Medical Dictionary for Regulatory Activities (MedDRA) system organ class (SOC) and preferred term (PT). Participants were counted only once for each SOC and each PT. However, within a SOC, a participant could have more than one non-serious AE for different PTs.

2.4.4. Sensory and Hedonic Ratings

The ratings ranged from 1 to 9, with 1 denoting ‘dislike extremely’, 5 denoting ‘neither like nor dislike’, and 9 denoting ‘like extremely’. Participants rated the overall liking, aroma, flavor, and aftertaste of each treatment within 5 min of consuming the first few mouthfuls of the study treatment.

2.5. Analytical Method

Capillary HbA1c was determined using AfinionTM 2 Analyzer (Alere Technologies AS, Oslo, Norway) during the baseline visit, while fasting capillary glucose before the commencement of the meal tolerance test was determined using Accu-Chek® Active Meter (Roche, Mannheim, Germany). Blood samples from 0 to 180 min were analyzed at the study sites’ laboratories, by enzymatic method using Roche Cobas® GLUC3 Kit Assay (Roche, Mannheim, Germany) or Alinity ϲ Glucose Reagent Kit 07P55 (Abbott, Germany) for glucose levels, and by electrochemiluminescence immunoassay using Roche Cobas® Elecsys Insulin (Roche, Mannheim, Germany) for insulin levels.

2.6. Statistical Analyses

A total of 54 participants were required to have 80% power to detect a mean difference of 16% in glucose positive AUC0–180 between the study treatments [20], using a significance level of 0.05 in a 2-sided paired t-test for three groups adjusting for multiple comparison using the Bonferroni correction. To allow for equal enrollment into six sequences of the study treatment and 20% dropout rate, 66 participants were planned to be enrolled. The attrition rate was very low, and hence only 65 participants were enrolled. Using glucose, insulin, and subjective appetite data, the AUC, positive AUC (pAUC), negative AUC (nAUC), adjusted peak value, and adjusted value (at each timepoint after t = 0) were calculated. The postprandial AUC0–180 was calculated using trapezoidal rule. For hunger, the mean time to return to baseline was estimated with the 95% confidence interval derived from the Gompertz model [29].
Each continuous variable in the crossover design was analyzed using parametric (mixed model) or non-parametric (if declared non-normal) three-treatment three-period crossover analysis. The parametric analysis was performed using three-treatment three-period repeated measures analysis of variance with variance components, covariance structure, and Satterthwaite degrees of freedom with the treatment and period as fixed effects, and participants as the random effect. The histogram and normal probability plot of the residuals from the parametric analysis were examined for deviation from normality. If the parametric approach was determined to be inappropriate, then three pairwise treatment differences were analyzed using the Wilcoxon signed rank test. All hypothesis tests were performed using 2-sided, 0.05 level tests. The p-values were adjusted for the three comparisons using the adaptive Holm’s method to control the familywise error rate. p-values ≤0.05 were considered statistically significant while p-values >0.05 and <0.10 were reported as trends. All analyses were performed using SAS 9.4.

3. Results

A total of 65 participants were enrolled. Of these, 64 were randomized and completed all three treatments (Figure 1). One participant failed the pre-requisite criteria, as the fasting capillary glucose levels were ≥10 mmol/L on both the first visit and rescheduled visit, prior to randomization. No study treatment was given, and the participant exited the study. All 64 randomized participants completed all three treatment visits and had the primary outcome, and were included in the final analysis (100% completion rate). Almost two-thirds of the study participants were female (64.1%), with a mean ± standard error (SE) age of 54.5 ± 1.0 years. Mean HbA1c, BMI, and duration of diabetes were 7.75 ± 0.08%, 27.63 ± 0.48 kg/m2, and 7.9 ± 0.7 years, respectively (Table 1). The majority of the participants had hyperlipidemia (90.6%), followed by hypertension (67.2%) and other co-morbidities (32.8%), such as thyroid disorder, hyperuricemia, and osteoarthritis.

3.1. Glucose

The least squares mean (LSM) ± SE of the glucose pAUC was the lowest with the DSF (354 ± 32 mmol.min/L), followed by noodle soup (395 ± 32 mmol.min/L) and then glutinous rice (451 ± 32 mmol.min/L; Figure 2i). The glucose pAUC for the DSF was significantly lower than that of glutinous rice (p = 0.033). There were no significant differences in pAUC between glutinous rice and noodle soup (p = 0.216), or between the DSF and noodle soup (p = 0.365). There were no significant differences in glucose peak value, adjusted peak value, peak time, and values at 0 min between the three treatments (Supplementary Table S3).

3.2. Insulin

The median insulin pAUC for the DSF was significantly lower than glutinous rice (p = 0.042; Figure 2ii). There were no significant differences in the median pAUC insulin between the DSF and noodle soup, or between noodle soup and glutinous rice. There were no significant differences in peak insulin values, adjusted peak insulin values, and peak time among the three treatments (Supplementary Table S4). At baseline, there was a significantly higher median insulin value for noodle soup as compared to glutinous rice (p = 0.009).

Insulinogenic Index

DSF had a significantly higher median IGI30 compared to glutinous rice (median [IQR], DSF 8.1 [4.2, 19.7]; glutinous rice 5.4 [2.7, 11.7]; p < 0.001). There were no significant differences between noodle soup and glutinous rice or the DSF (both p ≥ 0.114).

3.3. Appetite

No significant differences were found in subjective appetite nAUC between the three treatments (all p ≥ 0.827; Figure 2iii). Fullness pAUC was significantly greater in glutinous rice (6310 ± 547 mm.min) compared to noodle soup (5008 ± 547 mm.min; p = 0.036; Supplementary Figure S1i). There were no significant differences in fullness between the DSF (5484 ± 547 mm.min) and glutinous rice or noodle soup (both p ≥ 0.181). There were no significant differences in the nAUC of prospective consumption and hunger (Supplementary Figure S1ii,iii). However, the Gompertz model estimated hunger returning to baseline at the shortest time for noodle soup (165 min), which was 21 to 32 min earlier than for the DSF (186 min) and glutinous rice (197 min) (Supplementary Figure S2). For thirst, there was a trend towards significantly greater thirst with noodle soup compared to the DSF (p = 0.053; Supplementary Figure S1v).

3.4. Sensory and Hedonic Ratings

There were no significant differences in overall liking scores between all three treatments (all, p = 1.000). In addition, no significant differences were found in liking for the aroma, flavor, and aftertaste between the DSF and glutinous rice or noodle soup (all, p ≥ 0.293). However, participants liked the aftertaste of glutinous rice significantly more than the noodle soup (median [IQR] glutinous rice 6.0 [5.0, 7.0]; noodle soup 5.0 [5.0, 6.0] mm; p = 0.036).

3.5. Adverse Events and Serious Adverse Events

Six treatment-emergent AEs, from six unique PTs across five SOCs, were reported. Three (4.7%) participants reported one AE each, after consumption of the DSF. Another three (4.7%) other participants reported one AE each, after the consumption of glutinous rice. Three PTs for the three AEs reported in the DSF group were vertigo positional (ear and labyrinth disorders SOC), diarrhea (gastrointestinal disorders SOC), and fatigue (general disorders and administration site conditions SOC). These three AEs were mild and resolved spontaneously, without any medication.
There were two PTs, i.e., gingivitis and pharyngitis, reported for the infections and infestations SOC, and one headache reported for the nervous system disorders SOC after consuming glutinous rice. Antibiotics were prescribed for the two infections, while paracetamol was given to relieve the headache. All three AEs were mild and unrelated to glutinous rice as determined by the principal investigators.
No serious adverse events were reported. There were no statistically significant or clinically relevant trends for any specific PTs reported during this study.

4. Discussion

Our study demonstrated that the consumption of a DSF resulted in significantly lower postprandial glucose and insulin responses than the consumption of a glutinous rice breakfast in individuals with T2D, while having a longer estimated time for hunger to return to baseline than noodle soup. The IGI30 was significantly higher with the DSF compared to glutinous rice.

4.1. DSF and Glutinous Rice

Various studies assessing the GI of glutinous rice-based foods have shown it to have moderate-to-high GI (GI range, 61–89) [30,31]. In contrast, the DSF in the current study has a low GI, which is attributable to the slow-release carbohydrate system. Low-GI carbohydrates have been associated with lower postprandial glucose and insulin responses [19,32]. In addition, each serving of DSF contains high levels of myo-inositol, MUFA, and fiber components that have been shown to improve glucose control, insulin sensitivity, and metabolic risk factors in meta-analyses of acute [24] and mid- to long-term studies [24,33,34]. Inositol supplementation (0.4 to 4 g) from 4 to 27 weeks lowered the fasting plasma glucose, 2-h oral glucose tolerance test and improved insulin sensitivity in people with diabetes [33]. Increasing dietary fiber intake in people with diabetes, for 6 to 12 weeks, was shown to reduce fasting glucose and HbA1c levels as compared to the control [34]. In addition, a high fiber intake was also associated with lower postprandial glucose levels [35]. When compared to standard nutritional formula, DSF, which has high MUFA content, was associated with a lower postprandial glucose and insulin response, and lower HbA1c [24]. Taken together, these could be contributing to the finding that DSF consumption yielded a lower glycemic response as compared to glutinous rice consumption.
IGI30 is a surrogate used in measuring the efficiency of glucose removal in the early phase of stimulated insulin secretion [36]. A decrease in the insulinogenic index was observed in individuals with T2D as compared to those without T2D [37]. The IGI30 was significantly higher for the DSF in this study compared to glutinous rice, indicating a greater early-phase insulin response with the DSF [36]. In healthy individuals, a higher early-phase insulin response (IGI30) was associated with lower fasting or 2-h PPG levels [38]. In individuals with T2D, those who achieved fasting plasma glucose <7 mmol/L (responders) after 8 weeks of low-calorie liquid diet-based intervention were observed to have higher IGI30 at baseline and at 8 weeks compared to those who did not (non-responders) [39]. Similarly, significant improvements in modified IGI with reduced postprandial glucose response were also observed in individuals with T2D after consuming 6 weeks of a carbohydrate-restricted, high-protein (CHRP) diet as compared to consuming a conventional diabetes (CD) diet (energy-percentage carbohydrate/protein/fat, CHRP 30/30/40 vs. CD 50/17/33) [40]. The authors suggested that the increased early insulin response might have contributed to the positive impact on postprandial glucose AUC [40,41]. Lastly, in a 24-week study using dorzagliatin (a glucokinase activator that improves glucose-stimulated insulin secretion) in individuals with T2D, among those who had 2-h PPG < 11.0 mmol/L, the restoration of impaired IGI30 from baseline was associated with a reduction in HbA1c [42]. These results suggest that improved early-phase insulin secretion, as measured by IGI30, in those with an impaired response at baseline, may be favorably associated with long-term glycemic control [42].
Subjective appetite responses showed no significant differences between the DSF and glutinous rice. Glutinous rice possesses a high satiating effect as a result of its sticky consistency and high amylopectin content, which slows down the process of digestion and is associated with a sensation of fullness [43]. The DSF in this study yielded a similar satiety response compared to glutinous rice. The slow-digesting carbohydrates in DSF, such as sucromalt and soluble and insoluble fibers, are likely to play a role in lowering appetite through increases in gastrointestinal hormones, such as glucagon and peptide-YY [44,45].

4.2. DSF and Noodle Soup

Comparing the DSF and noodle soup, the DSF elicited lower adjusted glucose and insulin values at various time points, although the differences in glucose and insulin pAUC did not reach statistical significance. Noodles have wheat flour as the main carbohydrate source and were shown to have high GI [17]. The noodles used for GI testing are usually fresh and cooked. The noodles used in this study were cooked, frozen, defrosted, and then microwaved before consumption. Prior research has demonstrated that the process in which food is stored and prepared can impact glycemic response [46]. The freezing and subsequent defrosting of starchy food, with or without additional toasting, reduced the glucose response compared to its fresh counterpart [47]. Another study corroborated this finding, showing that starchy food stored under low temperature (−20 °C) for 30 days led to higher resistant starch formation, which reduced the glucose pAUC and GI of certain food, depending on the characteristics of the carbohydrate [48]. Furthermore, the noodle soup used in this study contained 10.5 g of dietary fiber (Supplementary Table S1). The presence of certain dietary fibers could modify the glucose response of the meal [49]. These combined characteristics of the noodle soup may have contributed to its glycemic response observed in this study.
Subjective appetite responses showed no significant differences between the DSF and noodle soup. However, there was a trend towards lower thirst levels after consuming the DSF compared to noodle soup, possibly caused by the much higher sodium levels in noodle soup (209 mg per serving vs. 1910 mg per serving; Supplementary Table S1). It is noteworthy that the World Health Organization [50] and Thai Ministry of Public Health [51] have recommended less than 2000 mg of sodium intake per day to reduce the risk of non-communicable diseases. One serving of the noodle soup consisted of 1910 mg compared to 209 mg in one serving of DSF and 330 mg in one serving of glutinous rice. Of note, two-thirds of the study population had concomitant hypertension, and controlling daily sodium intake may be beneficial to their blood pressure control. There have been reports on the dose–response relationship between salt intake and blood pressure, where the lower the salt intake, the lower the blood pressure [52]. Furthermore, there is a recommendation by the American Heart Association for people with chronic coronary disease, including people with diabetes, to reduce their sodium intake, optimally at 1500 mg per day [53], which is also in line with the dietary reference intakes by the Food and Nutrition Board [54].
The study DSF provides complete and balanced nutrition with high levels of vitamins and minerals, such as vitamin D, zinc, calcium, folic acid, iron, and chromium to help manage the glycemic response and meet the nutritional needs of people with diabetes. These nutrients are often inadequately supplied in common breakfasts, as shown by the negligible amount of some of them in noodle soup and glutinous rice compared to the DSF used in this study (Supplementary Table S1). Therefore, aside from considering the effect of energy and macronutrient differences between the DSF and noodle soup on postprandial glucose, insulin, and satiety, other contents such as vitamins and minerals should also be considered when individuals with T2D are choosing a suitable meal.

4.3. Glutinous Rice and Noodle Soup

There was a baseline insulin difference between these two groups. However, this was a crossover study, where participants were their own control. The observed difference in the baseline insulin levels was small and could be incidental. Comparing glutinous rice and noodle soup, there were no significant differences in the majority of the findings. Glutinous rice and noodle soup had similar total energy, protein, and carbohydrate. Both meals were also cooked, frozen, defrosted, and heated prior to consumption. The effects from the similar food processing and preparation could also contribute to the comparable glycemic responses observed in this study [47,48,55]. Although there was no significant difference in subjective appetite, the sensation of fullness was significantly higher with glutinous rice compared with noodle soup, despite its smaller serving size (115 g vs. 226 g for noodle soup). Breakfasts with high satiating effects may lead to better appetite control and reduced calorie intake later in the day [56,57].

4.4. Sensory and Hedonic Ratings and AEs

The DSF utilized in this study had liking profiles similar to the local popular breakfasts (glutinous rice and noodle soup), suggesting its possibility as a dietary substitute for individuals with diabetes. In addition, the DSF was also well tolerated in this study. There was no trend observed from the six different incidences of AEs reported in this study. Overall, no safety concerns were noted with the consumption of the DSF.

4.5. Strength and Limitation

Our study possesses several strengths. Firstly, the research utilized a randomized, controlled, crossover design where participants were their own control, reducing inter-individual variations. Secondly, all 64 randomized participants completed the study without any dropouts or intolerable adverse events; it has a larger sample size compared to most of the other studies that have assessed acute outcomes of DSFs and normal breakfasts (sample sizes ranged from 11 to 32) [20,21,45,58,59]. Additionally, meals were consumed in their typical serving sizes, closely mimicking the real-life situation, rather than at calculated portions to match energy or macronutrient contents. Thus, our findings are relevant for dietary planning in individuals with T2D. Lastly, the study evaluated glucose, insulin, and subjective appetite responses, providing a comprehensive evaluation of the metabolic and satiety effects of different breakfasts.
The two comparator breakfasts used in this study were based on common Asian staple foods. The findings might differ if breakfasts from other geographic regions were examined. In addition, the study concluded at 180 min postprandially, potentially missing late changes in glucose and insulin concentrations which might occur after this period. However, a previous 4-h study comparing DSF with standard meals had demonstrated that glucose levels had already returned to baseline at 3 h, and at 4 h, the glucose levels fell below baseline [23]. The study duration of 180 min is also commonly used in meal tolerance studies, where both the mean or median levels of glucose and insulin were shown to be approaching baseline levels [20,21,22]. Therefore, the effect of glucose and insulin changes after 180 min is likely minimal.

5. Conclusions

The DSF significantly reduced postprandial glucose and insulin responses, while having comparable satiety with glutinous rice. The insulinogenic index at 30 min was also significantly higher with the DSF compared to glutinous rice. No significant differences were found in subjective appetite between any of the three treatments. The estimated time for hunger returning to baseline was the shortest for noodle soup, which was approximately 20 to 30 min faster than for the DSF and glutinous rice. In conclusion, the DSF significantly reduced postprandial glucose and insulin responses compared to glutinous rice and had a higher satiating value when compared to noodle soup in individuals with T2D. Replacing common Asian breakfasts with DSF may improve glycemia and hunger control.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/diabetology5040033/s1, Table S1. Energy and nutrient composition of study breakfasts; Table S2. Calculations of insulin sensitivity and resistance indices; Table S3. Glucose parameters on different test days (n = 64); Table S4. Insulin parameters on different test days (n = 64); Figure S1. Visual analog scale (VAS) for fullness, prospective consumption, hunger, desire to eat, and thirst from 0 to 180 min; Figure S2. Time elapsed before hunger sensation is back to baseline level.

Author Contributions

S.T.K.: data curation, formal analysis, project administration, supervision, visualization, writing—original draft, writing—review and editing. D.T.T.H.: conceptualization, data curation, methodology, supervision, writing—original draft, writing—review and editing. W.S.: investigation, project administration, resources, writing—review and editing. W.K.: investigation, project administration, resources, writing—review and editing. C.W.: investigation, project administration, resources, writing—review and editing. T.S.: investigation, project administration, resources, writing—review and editing. C.H.: data curation, writing—review and editing. S.P.: data curation, formal analysis, visualization, writing—review and editing. M.Y.: data curation, formal analysis, visualization, writing—review and editing. S.L.T.: conceptualization, data curation, formal analysis, methodology, project administration, supervision, writing—original draft, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research and medical writing support was funded by Abbott Nutrition.

Institutional Review Board Statement

The study protocol was reviewed and approved by the institutional ethics committee (Faculty of Medicine, Chulalongkorn University IRB COA No. 0548/2023; Faculty of Medicine Siriraj hospital, Mahidol University IRB COA no. Si 278/2023) in compliance with the Declaration of Helsinki and registered at ClinicalTrials.gov as NCT05802927.

Informed Consent Statement

All participants provided signed informed consent before any study procedure was conducted.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the corresponding author on request.

Acknowledgments

We would like to acknowledge the research staff from Siriraj Hospital and King Chulalongkorn Memorial Hospital, and the study team at Abbott Nutrition for their invaluable support in this study. We thank Apaporn Karin, Chanida Kanjanapha, and Pinyapat Ariyakunaphan for their continuous assistance in this study. We also thank Khi Khi Choo and Mittal Makhija of MIMS Pte. Ltd. for providing writing and editorial assistance for the manuscript, in compliance with Good Publication Practice 2022 ethical guidelines [60].

Conflicts of Interest

S.T.K., D.T.T.H., C.H. and S.L.T. are employees of Abbott. W.S. reports receiving honoraria for speaking engagements from Astra Zeneca, Abbott, Merck, and Boehringer. W.K. reports receiving honoraria for speaking engagements and advisory boards from Amgen, Novartis, Novo Nordisk, Astra Zeneca, Abbott, Meiji, and Daiichi Sankyo. C.W. reports no conflict of interest. T.S. reports receiving honoraria for speaking engagements from Servier. S.P. and M.Y. are employees of Cognizant Technology Solutions, a contract research organization that provides statistical services to Abbott Nutrition, and have no competing interests.

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Figure 1. Consort flow diagram for this study.
Figure 1. Consort flow diagram for this study.
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Diabetology 05 00033 g002aDiabetology 05 00033 g002bDiabetology 05 00033 g002cDiabetology 05 00033 g002d
Figure 2. Postprandial (i) adjusted glucose level changes, (ii) adjusted insulin level, and (iii) subjective appetite, in response to the study treatments over time (n = 64). Three-period three-treatment crossover analysis using repeated measures analysis of variance with treatment and visit as fixed effects and subject identifier as random effect using adaptive Holm p-value adjustments. AUC, area under curve; IQR, interquartile range; LSM, least squares mean; SE, standard error. ** = p > 0.05 and p < 0.10 for differences between diabetes-specific formula and noodle soup; † = p ≤ 0.05, †† = p > 0.05 and p < 0.10 for differences between diabetes-specific formula and glutinous rice; § = p ≤ 0.05, §§ = p > 0.05 and p < 0.10 for differences between noodle soup and glutinous rice.
Figure 2. Postprandial (i) adjusted glucose level changes, (ii) adjusted insulin level, and (iii) subjective appetite, in response to the study treatments over time (n = 64). Three-period three-treatment crossover analysis using repeated measures analysis of variance with treatment and visit as fixed effects and subject identifier as random effect using adaptive Holm p-value adjustments. AUC, area under curve; IQR, interquartile range; LSM, least squares mean; SE, standard error. ** = p > 0.05 and p < 0.10 for differences between diabetes-specific formula and noodle soup; † = p ≤ 0.05, †† = p > 0.05 and p < 0.10 for differences between diabetes-specific formula and glutinous rice; § = p ≤ 0.05, §§ = p > 0.05 and p < 0.10 for differences between noodle soup and glutinous rice.
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Table 1. Baseline characteristics for participants in the study.
Table 1. Baseline characteristics for participants in the study.
CharacteristicsTotal
(n = 64)
Gender, n (%)
          Male23 (35.9%)
          Female41 (64.1%)
Ethnic group, n (%)
          Thai64 (100%)
Age, years 54.5 ± 1.0
Capillary HbA1c, %7.75 ± 0.08
Body weight, kg72.15 ± 1.62
Height, cm161.33 ± 1.11
Body mass index, kg/m227.63 ± 0.48
Hip circumference, cm100.85 ± 1.17
Waist circumference, cm92.43 ± 1.28
Diabetes duration, years7.9 ± 0.7
HOMA index
          HOMA-β58.05 ± 6.31
          HOMA-IR3.05 ± 0.31
Co-morbidities, n (%)
          Hyperlipidemia58 (90.6%)
          Hypertension43 (67.2%)
          Others21 (32.8%)
Number of glucose-lowering medications, n (%)
          One22 (34%)
          Two25 (39%)
          Three10 (16%)
          Four or more7 (11%)
Medications, n (%)
Glucose-lowering medication64 (100%)
          Metformin61 (95%)
          Sulphonylureas32 (50%)
          Thiazolidinediones14 (22%)
          Dipeptidyl peptidase 4 (DPP-4) inhibitors13 (20%)
          Sodium-glucose co-transporter 2 (SGLT2) inhibitors11 (17%)
Blood pressure-lowering medication37 (58%)
Lipid-modifying agents57 (89%)
Results are presented as mean ± standard error, unless stated otherwise. HbA1c, glycated hemoglobin A1c; HOMA, homeostasis model assessment; HOMA-β, homeostasis model assessment–beta-cell function; HOMA-IR, homeostasis model assessment–insulin resistance.
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Kong, S.T.; Huynh, D.T.T.; Srivanichakorn, W.; Khovidhunkit, W.; Washirasaksiri, C.; Sitasuwan, T.; Huang, C.; Paunikar, S.; Yalawar, M.; Tey, S.L. A Randomized Crossover Study Comparing the Effects of Diabetes-Specific Formula with Common Asian Breakfasts on Glycemic Control and Satiety in Adults with Type 2 Diabetes Mellitus. Diabetology 2024, 5, 447-463. https://doi.org/10.3390/diabetology5040033

AMA Style

Kong ST, Huynh DTT, Srivanichakorn W, Khovidhunkit W, Washirasaksiri C, Sitasuwan T, Huang C, Paunikar S, Yalawar M, Tey SL. A Randomized Crossover Study Comparing the Effects of Diabetes-Specific Formula with Common Asian Breakfasts on Glycemic Control and Satiety in Adults with Type 2 Diabetes Mellitus. Diabetology. 2024; 5(4):447-463. https://doi.org/10.3390/diabetology5040033

Chicago/Turabian Style

Kong, Sing Teang, Dieu Thi Thu Huynh, Weerachai Srivanichakorn, Weerapan Khovidhunkit, Chaiwat Washirasaksiri, Tullaya Sitasuwan, Chengrong Huang, Swapnil Paunikar, Menaka Yalawar, and Siew Ling Tey. 2024. "A Randomized Crossover Study Comparing the Effects of Diabetes-Specific Formula with Common Asian Breakfasts on Glycemic Control and Satiety in Adults with Type 2 Diabetes Mellitus" Diabetology 5, no. 4: 447-463. https://doi.org/10.3390/diabetology5040033

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