Abstract Nutrition is essential for the maintenance of metabolic health, especially in individuals at risk of glucose dysregulation. This study aimed to determine the glycemic index (GI) and glycemic load (GL) of a soy-based protein beverage (D-care from Ma-Jusmin Co., Ltd.). The GI assessment followed ISO 26642:2010 guidelines and was conducted in 10 healthy adults (equal number of males and females). Postprandial blood glucose responses were measured over 120 minutes after consuming the test beverage and a glucose reference solution, both containing 50 g of available carbohydrates. The soy-based beverage resulted in significantly lower blood glucose levels at 15, 30, 45, 60, and 90 minutes (P < 0.001) compared to the glucose solution. The peak glucose level for the glucose solution occurred at 45 minutes (161.55 ± 5.79 mg/dL), while the soy beverage peaked earlier at 30 minutes (109.90 ± 2.87 mg/dL). The highest incremental area under the curve (IAUC) was observed between 60–90 minutes for the glucose solution (1,272.75 ± 171.06 mg × min/dL), whereas the soy beverage showed a much lower peak (309.00 ± 81.68 mg × min/dL). The total IAUC at 120 minutes was also significantly lower for the soy beverage (1,273.74 ± 218.31 vs. 4,583.05 ± 433.99 mg × min/dL; P < 0.001). Accordingly, the GI and GL were calculated to be 26.36 ± 2.95 and 8.09 ± 0.91, respectively. The beverage is classified as low-GI and low-GL based on these findings, which suggest that it may be an acceptable choice for postprandial glycemic control.

Keywords: Glycemic index, Glycemic load, Soy-based protein beverage, D-care

Funding: This research was financially supported through a collaborative funding initiative between Ma-Jusmin Company Limited and Chiang Mai University.

Citation:  Parklak, W., Ounjaijean, S., Phimolsiripol, Y., and Boonyapranai, K. 2026. Assessment of in vivo glycemic index, glycemic load, and postprandial glycemic response of a soy-based protein beverage. Natural and Life Sciences Communications. 25(2): e2026039.

Graphical Abstract:

INTRODUCTION

Insulin resistance and type 2 diabetes mellitus (T2DM) are among the most common and rapidly increasing metabolic disorders worldwide. According to the World Health Organization (WHO), over 500 million people are currently living with diabetes, the majority of whom are affected by T2DM—a condition strongly associated with modifiable lifestyle factors such as poor dietary habits, physical inactivity, and obesity (Chen et al., 2011; Jaacks et al., 2016; Basu et al., 2019). Insulin resistance, characterized by an impaired biological response of peripheral tissues (including skeletal muscle, liver, and adipose tissue) to circulating insulin, represents a key pathophysiological feature of T2DM and typically precedes the clinical manifestation of the disease (Jansson, 2007; Nolan and Prentki, 2019). This progressive impairment in insulin action results in the deterioration of glycemic control, manifested as elevated fasting and postprandial blood glucose levels. Without appropriate intervention, chronic hyperglycemia contributes to the development of both microvascular and macrovascular complications, including nephropathy, retinopathy, neuropathy, and cardiovascular disease (Kosmas et al., 2023; Zakir et al., 2023). Early dietary intervention is therefore essential for preventing the progression of insulin resistance to overt diabetes and for minimizing long-term health consequences in individuals already diagnosed with the disease (Shi et al., 2008; Ley et al., 2014; Papakonstantinou et al., 2022).

Medical nutrition therapy, including the use of specialized medical foods, plays a critical role in moderating postprandial glucose excursions in patients with impaired glucose regulation (Ch'ng et al., 2019; Barrea et al., 2023; Parklak et al., 2024a; Parklak et al., 2024b). One widely adopted dietary strategy involves the consumption of foods with a low glycemic index (GI) and glycemic load (GL), which have been shown to attenuate postprandial glycemic responses and improve metabolic outcomes (Venn and Green, 2007). The GI categorizes carbohydrate-containing foods based on their impact on blood glucose levels: high GI (≥70), medium GI (56–69), and low GI (≤55). Similarly, GL is categorized as high (≥20), medium (11–19), and low (≤10), and reflects both the quality (GI) and quantity of carbohydrates in a given portion of food. It is generally recommended that total daily GL intake should not exceed 100 (Venn and Green, 2007). A high-GI diet acutely raises blood glucose and triggers compensatory insulin secretion. Over time, chronic intake may overburden pancreatic β-cells, leading to their dysfunction and reduced insulin production (Cavaghan et al., 2000; Herawati et al., 2020). However, evidence from clinical and epidemiological studies suggests that low-GI and low-GL diets can improve insulin sensitivity, reduce postprandial glucose excursions, lower cardiovascular risk factors, and support more effective weight management (Jenkins et al., 2002; Chiavaroli et al., 2021; Papakonstantinou et al., 2022; Perin et al., 2022). These findings underscore the importance of evaluating the GI and GL of functional and medical food products intended for individuals with insulin resistance and T2DM (Bator et al., 2014; Acker and Cash, 2017).

The soy-based protein beverage was developed for individuals who require blood glucose control, including those with T2DM. It is provided in powder form for reconstitution and is also suitable for use as an enteral nutrition formula in diabetic patients who require complete nutritional support. The key components of this formulation include soy protein isolate, fat powder, and dietary fiber. The protein content comprises 23% of the product, sourced entirely from soy protein isolate. Soy protein is rich in essential amino acids and isoflavones, compounds that have been associated with improved insulin sensitivity and reduced postprandial glucose levels (Kashima et al., 2016; Faria et al., 2018). A meta-analysis of randomized controlled trials demonstrated that soy protein supplementation significantly lowered fasting plasma glucose levels and improved markers of insulin resistance in individuals with T2DM (Zhang et al., 2016). In addition, soy-based foods generally possess a low-GI, leading to a gradual postprandial rise in blood glucose, a characteristic particularly beneficial for glycemic regulation in diabetic individuals (Blair et al., 2006). Isoflavones in soy have also been shown to influence glucose metabolism, with studies indicating enhanced insulin secretion and improved insulin sensitivity as key outcomes (Barańska et al., 2021).

Incorporating soy protein into the diet may serve as a beneficial adjunct to conventional therapy for individuals with T2DM who are managing their blood glucose levels, as suggested by the findings of this study. However, further research is needed to validate these effects and optimize practical applications. Therefore, the objective of this study was to evaluate the postprandial glycemic response of a soy-based protein beverage, including its in vivo GI and GL, in order to establish evidence-based intake recommendations for therapeutic use.

MATERIALS AND METHODS

Materials

Test food

The test product used in this study was a soy-based protein beverage commercially marketed under the trade name D-care, distributed by Ma-Jusmin Co., Ltd., Thailand. D-care is a specialized nutritional formula enriched with soluble dietary fiber and specifically developed for individuals with diabetes. Its key characteristics include a high protein content and a low level of carbohydrates. Moreover, D-care is suitable for patients with cow's milk protein allergy.

The composition and macronutrient distribution of D-care are presented in Table 1. On the test day, 108 grams of D-care (equivalent to 50 grams of available carbohydrates) were reconstituted in 250 mL of warm water at approximately 40°C for consumption during the experiment.

Table 1. The composition and macronutrient distribution of soy-based protein beverage.

Reference food

Glucose powder from Utopian Company Limited (Samut Prakan, Thailand) was used as the reference food for glycemic index assessment. On the day of testing, 50 grams of glucose powder were prepared by dissolving in 250 mL of warm water at a temperature of approximately 40°C for use in the test.

Ethics statement

This study was approved by the Research Ethics Committee of the Research Institute for Health Sciences, Chiang Mai University (Approval No. 67/2024). Prior to participation, all subjects were informed of the study details, including its objectives, duration, study procedures, potential benefits, and associated risks. Written informed consent was obtained from all participants, who voluntarily agreed to take part in the study.

Study subjects

This research was conducted at the Laboratory of Nutritional Research and Innovation (NUTRI) and the Glycemic Index Center (GIC) at Chiang Mai University in Chiang Mai, Thailand. Poster advertisements were implemented to attract healthy participants. The study included a total of ten healthy individuals who satisfied all of the inclusion criteria. Participants were required to meet the following criteria for inclusion: sustain normal fasting blood glucose (FBG) levels, have a normal body mass index (BMI) between 18.5 and 24.9 kg/m², and be between the ages of 20 and 50. In addition, participants were required to be free of chronic diseases, including hypertension, diabetes, metabolic disorders, and gastrointestinal conditions that could potentially impact nutrient absorption or assimilation. Furthermore, individuals who were known to have allergies to any of the components of the test formula (e.g., soy, isomaltulose, Fibersol, or prebiotic dietary fiber) were excluded. Exclusion criteria included the following: recent use of medications and/or dietary supplements, engagement in strenuous physical activity within 24 hours prior to testing, alcohol consumption within the preceding 24 hours, adherence to certain dietary practices (e.g., vegetarianism), and pregnancy or lactation in female participants.

Study procedure

The GI of the test product was determined in accordance with the standardized protocol ISO 26642:2010. On Day 7 following participant screening, individuals were required to undergo an overnight fast for at least 12 hours before consuming a glucose solution (reference food) within 12–15 minutes. Capillary blood samples were collected at fasting (0 min) and at 15, 30, 45, 60, 90, and 120 minutes post-consumption. On Day 12, the reference food was administered again to the same participants for a duplicate test. Blood glucose levels during the fasting state and at each postprandial time point over a 2-hour period were plotted to calculate the incremental area under the blood glucose response curve (IAUC). According to ISO standards, the average within-subject coefficient of variation (CV) for the reference food should not exceed 30% (ISO 26642:2010). In this study, the CV was 16.21%, indicating acceptable inter-individual variability within the sample population.

Subsequently, on Day 17, participants, after fasting for at least 12 hours, consumed the soy-based protein beverage (test food) under the same conditions and time points as used for the reference food. Prior to each test session, participants underwent a general health assessment, including blood pressure measurement and body composition analysis using a bioelectrical impedance analyzer (InBody H20^®; InBody Co., Seoul, Korea). The experimental timeline and procedures are summarized in Figure 1. The GI and GL were calculated using the following formulas (Venn and Green, 2007):

GI = (IAUC of test food) / (IAUC of reference food) × 100                    (1)

GL = (GI × Available carbohydrates (g) per serving) / 100                     (2)

Figure 1. The experimental timeline and procedures.

Statistical analysis

SPSS for Windows, version 16.0 (SPSS Inc., Chicago, IL, USA; 2007), was employed to analyze the baseline characteristics of the participants, which were represented as means and standard deviations (SD). The categorical and continuous variables were evaluated using Fisher's exact test and the independent samples t-test, respectively. Following the consumption of the glucose solution and the soy-based protein beverage, the IAUC was determined using GraphPad Prism 5 Demo (GraphPad Software Inc., San Diego, CA, USA). Means ± standard error of the mean (SEM) were used to present glucose response parameters, such as blood glucose levels, IAUC, and the calculated GI and GL of the soy-based protein beverage.

RESULTS

Baseline characteristics of participants

The baseline demographic and physiological characteristics of the participants prior to the administration of the reference food (glucose solution) and the test product (soy-based protein beverage) are presented in Table 2. All ten healthy participants, with an equal number of males and females, underwent both reference and test food assessments. The mean age of the participants was 25.30 ± 2.41 years. No statistically significant differences were observed between the glucose and soy-based beverage test days in terms of height (166.50 ± 8.00 vs. 166.50 ± 8.00 cm; P = 1.000), body weight (64.36 ± 12.69 vs. 64.22 ± 12.88 kg; P = 0.664), BMI, waist and hip circumference, systolic blood pressure, heart rate, body fat percentage, or basal metabolic rate (P > 0.05 for all comparisons). However, a statistically significant difference was found in diastolic blood pressure, which was slightly higher on the glucose test day compared to the soy-based beverage test day (68.65 ± 6.76 mmHg vs. 64.60 ± 9.70 mmHg; P = 0.049).

Table 2. Participant characteristics prior to reference and test food administration.

Note: Values are expressed as mean ± standard deviation. An * indicates statistical significance at P ≤ 0.05.

Postprandial glycemic response of a soy-based protein beverage

Figure 2 illustrates the postprandial blood glucose responses following ingestion of a glucose solution and a soy-based protein beverage over a 120-minute period. Both interventions began at similar fasting glucose levels (94.83 ± 0.85 mg/dL for the glucose solution and 94.15 ± 1.04 mg/dL for the soy-based protein beverage), confirming comparable baseline conditions. However, distinct differences in glycemic response patterns were observed between the two groups throughout the postprandial period.

The glucose solution induced a rapid and significant increase in blood glucose, peaking at 45 minutes (161.55 ± 5.79 mg/dL), followed by a gradual decline to near-fasting levels by 120 minutes (101.50 ± 4.01 mg/dL). In contrast, the soy-based protein beverage elicited a markedly attenuated glycemic response, with a modest peak at 30 minutes (109.90 ± 2.87 mg/dL), followed by a stable plateau and a return to baseline by 120 minutes (103.20 ± 1.52 mg/dL).

Statistical analysis revealed that blood glucose levels were significantly lower in the soy-based protein beverage group compared to the glucose solution at all postprandial time points from 15 to 90 minutes. Specifically, the differences reached P < 0.01 at 15, 30, 45, 60, and 90 minutes (indicated by double asterisks in Figure 1), reflecting a robust and statistically significant attenuation of glycemic response in the soy-based beverage group. No significant difference was observed at 0 and 120 minutes, indicating that both products returned to similar glycemic levels by the end of the test period.

Figure 2. Postprandial blood glucose concentrations were monitored from fasting (0 min) to 120 minutes after ingestion of a glucose solution (n = 10, two replicates per subject) and a soy-based protein beverage (n = 10). Data are presented as mean ± standard error of the mean (SEM). Asterisks (*) denote statistically significant differences between the two treatments at each respective time point: **P < 0.001, indicating a significantly lower glycemic response following the soy-based protein beverage compared to the glucose solution.

To compare the effects of a glucose solution and a soy-based protein beverage over a 120-minute period, the postprandial blood glucose response was calculated as IAUC. This analysis included 10 participants per group, with two replicate measurements for each participant in the glucose solution condition. Figure 3a illustrates the IAUC values segmented by specific postprandial intervals. The IAUC values for the glucose solution increased steadily throughout each time segment, reaching a maximum during the 60–90-minute interval (1,272.75 ± 171.06 mg × min/dL). Conversely, the soy-based protein beverage exhibited significantly lower IAUC values across all intervals, with a modest peak also occurring during the 60–90-minute interval (309 ± 81.68 mg × min/dL). At all measured intervals (0–15, 15–30, 30–45, 45–60, 60–90, and 90–120 minutes), the IAUC differences between the two test products were statistically significant, with p-values less than 0.001. The total IAUC from 0 to 120 minutes is summarized in Figure 3b. The glucose solution's mean total IAUC was 4,583.05 ± 433.99 mg × min/dL, which was substantially higher than that of the soy-based protein beverage (1,273.74 ± 218.31 mg × min/dL). This difference was also highly significant (P < 0.001), indicating a substantially lower overall glycemic exposure following consumption of the soy-based protein beverage.

Figure 3. The incremental area under the curve (IAUC) of blood glucose concentrations following the consumption of a glucose solution (n = 10, with two replicates per participant) and a soy-based protein beverage (n = 10). In panel (a), the IAUC is displayed at each individual time point, while panel (b) displays the total IAUC, which was calculated from the fasting state (0 minutes) to 120 minutes post-consumption. The data are presented as the mean ± standard error of the mean (SEM). In comparison to the glucose solution, statistically significant differences are denoted by ** (P < 0.001).

Glycemic index and glycemic load of a soy-based protein beverage

In order to assess the soy-based protein beverage's effect on postprandial blood glucose levels, the GI and GL were determined. Equation (1) was employed to determine the GI of the test product in relation to the glucose reference solution, as determined by the IAUC. The soy-based protein beverage was classified as a low-GI product (GI < 55) based on its GI value of 26.36 ± 2.95 (mean ± SEM). Equation (2) was employed to calculate the GL in order to further evaluate its glycemic impact in relation to the typical dietary intake. The standard serving quantity of the soy-based protein beverage is 66 grams, and it contains 46.51 grams of available carbohydrates per 100 grams of product. The calculated GL was 8.09 ± 0.91 (mean ± SEM) based on these values. This value is classified as low glycemic load (GL < 10).

DISCUSSION

Diet plays a critical role in the management of various health conditions, particularly for individuals requiring blood glucose control, such as those with insulin resistance or T2DM (Ch'ng et al., 2019; Barrea et al., 2023). Nutritional therapy, including the use of appropriate medical foods, is essential for achieving glycemic stability (Gerontiti et al., 2024; Parklak et al., 2024a; Parklak et al., 2024b). In this study, a soy-based protein beverage was developed to serve as a nutritional supplement for individuals with diabetes and others who require blood glucose regulation. Therefore, it is essential to evaluate the product’s impact on glycemic response and to analyze its GI and GL.

The evaluation of GI in food products was conducted in accordance with the ISO 26642:2010 standard protocol, which requires the use of healthy participants. Healthy individuals exhibit stable glucose metabolism, thereby minimizing variability in glycemic responses. This consistency is critical for producing reliable and reproducible data (Riccardi et al., 2008). Moreover, metabolic conditions such as diabetes, insulin resistance, or other metabolic disorders that could confound glycemic outcomes are generally absent in healthy populations. This ensures that any observed changes in blood glucose are primarily attributable to the test food itself (O'Dea et al., 1980; Riccardi et al., 2008).

In this study, the mean age of the healthy participants was 25.30 ± 2.41 years. No significant differences were found between the reference food and test product days in baseline characteristics, including body weight, BMI, waist and hip circumference, resting heart rate, body fat percentage, basal metabolic rate, and fasting blood glucose levels. However, a statistically significant difference was observed in diastolic blood pressure, which was slightly higher on the glucose solution test day compared to the soy-based beverage day (68.65 ± 6.76 mmHg vs. 64.60 ± 9.70 mmHg; P = 0.049). Despite this finding, the values remained within the normal range for healthy individuals (60–80 mmHg) (Li et al., 2021), and such minor fluctuations may result from factors such as insufficient sleep, psychological stress, physical exertion, or natural circadian variation in blood pressure (Kawano, 2011; Foster, 2020). Therefore, based on the screening results, the participants were confirmed to be in good health, which supports the validity of the glycemic testing. The standardized baseline characteristics provide a solid foundation for interpreting the observed postprandial glycemic responses, allowing for meaningful insights into the potential effects of the soy-based protein beverage on blood glucose regulation in the general population.

The evaluation of postprandial glycemic response following consumption of the soy-based protein beverage revealed that mean blood glucose levels peaked at 30 minutes after ingestion, followed by a gradual decline through 120 minutes. In contrast, the reference glucose solution maintained elevated blood glucose levels for a longer duration, with peak levels observed at 45 minutes before a more rapid decline thereafter. Notably, blood glucose concentrations at 15, 30, 45, 60, and 90 minutes post-consumption were significantly lower following the soy-based protein beverage compared to the glucose reference (P < 0.001).

Similarly, the IAUC, which quantifies the total increase in blood glucose over the postprandial period relative to baseline, was markedly lower for the soy-based protein beverage. The IAUC is commonly used as a standard metric in glycemic index testing, as it reflects the overall glycemic impact of a food by integrating both the magnitude and duration of the postprandial glucose excursion (Le Floch et al., 1990; Wolever, 2004). It is particularly important in evaluating glycemic response because it captures the cumulative glycemic burden imposed by a test food, beyond single time-point measurements (Le Floch et al., 1990; Wolever, 2004).

The attenuated postprandial glycemic response observed following the consumption of the soy-based protein beverage may be attributed to the synergistic effects of its multiple bioactive components, each of which plays a role in glucose metabolism and insulin sensitivity. Soy protein isolate, the primary protein source in the formulation, is rich in essential amino acids and isoflavones—bioactive compounds that have been shown to enhance insulin secretion and improve glycemic control (Barańska et al., 2021). Previous studies have demonstrated that preloading with soy protein isolate can significantly reduce both the IAUC and the peak postprandial glucose levels, highlighting its efficacy in modulating glycemic responses (Kashima et al., 2016). In addition to its protein content, the fat component of the beverage—composed primarily of soy oil and oleic acid—may also contribute to improved insulin sensitivity (Nunes et al., 2007). Oleic acid, a monounsaturated fatty acid abundant in soy oil, has been reported to stimulate glucose uptake in adipocytes and regulate genes involved in insulin signaling, thus aiding glucose homeostasis (Tsuchiya et al., 2014).

The carbohydrate matrix of the beverage further supports its glycemic benefits. Isomaltulose, a low-glycemic disaccharide digested at a slower rate, leads to a more gradual and sustained increase in blood glucose levels compared to conventional sugars (de Souza et al., 2022). Its GI value is approximately 32, and several studies have confirmed its ability to elicit a significantly lower glycemic response than sucrose (Maresch et al., 2017). Conversely, maltodextrin, which is also present in the formulation, has a high GI and is known for its rapid digestibility (Hofman et al., 2016). However, its potential impact on postprandial hyperglycemia in this case appears to be offset by the inclusion of other low-GI ingredients, as well as by the presence of dietary fiber. It is important to note, nonetheless, that maltodextrin with a high dextrose equivalent (DE) can elevate blood glucose rapidly and should be carefully managed in products intended for individuals with glycemic concerns (Hofman et al., 2016).

Soluble dietary fibers, such as Fibersol, play a complementary role by increasing the viscosity of intestinal contents, thereby slowing carbohydrate digestion and glucose absorption (Chen et al., 2021; Giuntini et al., 2022). Clinical evidence has shown that such fibers can significantly lower postprandial glucose excursions and enhance insulin sensitivity (Weickert and Pfeiffer, 2018; Giuntini et al., 2022). In addition, the product contains prebiotic dietary fibers, including inulin and oligofructose, which may further enhance glycemic regulation through intestinal and metabolic mechanisms. These prebiotics selectively promote beneficial gut microbiota, leading to increased production of short-chain fatty acids (SCFAs), which have been shown to improve insulin sensitivity by enhancing peripheral glucose uptake, modulating hepatic glucose production, and stimulating gut-derived hormones such as glucagon-like peptide-1 (GLP-1) (Roberfroid, 1993; Kim et al., 2018). Collectively, these mechanisms are associated with lower fasting and postprandial blood glucose levels. Clinical and experimental evidence further suggests that inulin and oligofructose supplementation is linked to reduced glycemic responses and improved insulin sensitivity, particularly in individuals with impaired glucose tolerance or T2DM, through both delayed carbohydrate absorption and enhanced glucose disposal in peripheral tissues (Cani et al., 2005; Aliasgharzadeh et al., 2015; Wang et al., 2019).

Furthermore, the inclusion of fructose—a monosaccharide with a low glycemic index—may contribute additional glycemic benefit (Erejuwa et al., 2012; Qi and Tester, 2019). Fructose is primarily metabolized in the liver and, in small amounts, can facilitate hepatic glucose uptake and glycogen synthesis, resulting in a net reduction in circulating blood glucose levels (McGuinness and Cherrington, 2003). Research suggests that low-dose fructose intake may improve glycemic profiles, particularly in individuals with T2DM (Jalilvand et al., 2020).

These results suggest that the combined effects of high-quality soy protein, unsaturated fats, slowly digested carbohydrates, and soluble fibers contribute to the favorable glycemic profile of the soy-based protein beverage. This product's potential for use as part of a nutritional strategy to enhance postprandial glucose regulation, particularly in populations with insulin resistance or T2DM, is strongly supported by its multifaceted nutrient composition.

In addition, the analysis of the GI and GL of the soy-based protein beverage revealed values of 26.36 ± 2.95 and 8.09 ± 0.91, respectively. According to established classifications, these values place the product within the low-GI category (GI < 55) (Venn and Green, 2007) and low-GL category (GL < 10) (Venn and Green, 2007). These findings indicate that the product induces a minimal postprandial glycemic response, making it suitable for individuals requiring glycemic control, including those with impaired glucose tolerance or T2DM. The low glycemic characteristics observed may be attributed to the synergistic action of the product’s components, as discussed previously—particularly the combination of soy protein (Kashima et al., 2016; Barańska et al., 2021), isomaltulose (Maresch et al., 2017; de Souza et al., 2022), dietary fiber (Weickert and Pfeiffer, 2018; Giuntini et al., 2022), and unsaturated fats (Nunes et al., 2007; Tsuchiya et al., 2014), which contribute to slower glucose absorption and improved insulin sensitivity.

The growing demand for health-oriented foods and medical nutrition products has become a notable trend in the global functional food market (Karelakis et al., 2019). Recent reports indicate a significant rise in consumer interest in products that support chronic disease management, especially among patients with diabetes, cardiovascular disease, and metabolic disorders (Mozaffarian, 2016; Karelakis et al., 2019). Within this context, the findings from the present study offer valuable insights that can be used to support product positioning and development strategies. The soy-based protein beverage, and other formulations with similar nutrient profiles, may be considered for use as part of medical nutrition therapy or as a specialized medical food. However, as the product is primarily based on soy protein, it may not be suitable for individuals with soy allergy, including some patients with diabetes who require glycemic control. Future product development may therefore explore alternative plant-based protein sources to broaden applicability and provide additional options for diverse consumer needs. Such products can provide complete and balanced nutrition for patients while minimizing the risk of glycemic fluctuations, thereby supporting both metabolic control and overall health outcomes.

CONCLUSION

This study indicates that the soy-based protein beverage is a low-GI and low-GL product, suggesting its suitability for individuals requiring blood glucose regulation, including those with insulin resistance or T2DM. The findings support its potential use as part of medical nutrition therapy. From a food product perspective, the soy-based protein beverage (D-care from Ma-Jusmin Co., Ltd.), developed as a vanilla-flavored formulation, represents a base formulation intended for further product development. Future studies may focus on optimizing sensory attributes, such as taste and aroma, and exploring alternative formulations to broaden consumer applicability.

ACKNOWLEDGEMENTS

The authors would like to express their sincere gratitude to the Food Innovation and Packaging Center, Chiang Mai University, for the continuous support that made this research project possible. We also extend our appreciation to the Glycemic Index Center (GIC) and the Nutraceutical Research and Innovation Laboratory (NUTRI) at Chiang Mai University for providing the research facilities, equipment, and personnel essential for data collection and overall research execution.

AUTHOR CONTRIBUTIONS

Wason Parklak: Conceptualization (Supporting), Methodology (Equal), Software (Lead), Validation (Lead), Formal Analysis (Equal), Investigation (Equal), Resources (Lead), Data Curation (Lead), Writing – Original Draft (Lead), Visualization (Lead); Sakaewan Ounjajean: Conceptualization (Supporting), Methodology (Equal), Writing – Review & Editing (Supporting); Yuthana Phimolsiripol: Conceptualization (Equal), Methodology (Equal), Supervision (Supporting); Kongsak Boonyapranai: Conceptualization (Equal), Methodology (Equal), Software (Supporting), Validation (Supporting), Formal Analysis (Equal), Investigation (Equal), Writing – Review & Editing (Lead), Supervision (Lead), Project Administration (Lead), Funding Acquisition (Lead).

CONFLICT OF INTEREST

The research funders and supporting institutions had no role in the study design, data collection, data analysis, interpretation of results, or the preparation of the manuscript for publication. The authors declare that they have no conflicts of interest regarding this study.

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