Abstract
[Purpose]
The increasing prevalence of metabolic syndrome poses significant health risks, particularly for cardiovascular diseases and type 2 diabetes. Exercise interventions have shown promise in improving the components of metabolic syndrome, including blood pressure, lipid profiles, and glucose metabolism. Kinect-based mixed-reality exercise provides real-time feedback and personalized guidance, making it suitable for unsupervised training. Deep-sea water has beneficial effects on lipid metabolism and insulin sensitivity. However, the effects of Kinect-based mixed-reality exercise and deep-sea water on metabolic syndrome remain unclear.
[Methods]
Fifty-six participants aged 30-65 years with a diagnosis of metabolic syndrome were randomly assigned to four groups for an 8-week intervention: control (CG), deep-sea water consumption (WG), Kinect-based mixed-reality exercise (EG), and combined deep-sea water consumption and Kinect-based mixed-reality exercise (WEG). The intervention comprised a 40-min Kinect-based mixed-reality circuit exercise three times per week and daily consumption of 440 mL of deep-sea water. The measurements included blood pressure, body composition, blood profiles, quality of life, physical activity, diet recall, and the metabolic syndrome score.
[Results]
Forty-eight participants completed the study, demonstrating high compliance with the EG (98.4%) and WG (99.2%). Waist circumference significantly decreased in all intervention groups (WG, p = 0.002; EG, p < 0.0001; WEG, p < 0.0001), with a significant difference between CG and EG (p = 0.020). The metabolic syndrome component score decreased significantly in the EG (p = 0.004) and WEG (p = 0.002) groups, falling below the diagnostic threshold for metabolic syndrome.
[Conclusion]
These findings indicate the potential benefits of combining deep-sea water consumption and Kinect-based mixed-reality exercise in metabolic syndrome management.
Keywords: metabolic syndrome, deep-sea water, Kinect-based mixed reality, exercise, exergaming
INTRODUCTION
Metabolic syndrome (MS) significantly increases the risk of cardiovascular disease, type 2 diabetes, and other chronic conditions [1]. It affects approximately one-quarter of the global population [2]. The prevalence of MS in Korea has risen from 27.1% in 2001 to 33.2% in 2020 [3]. This trend continues to increase, particularly among older adults, with approximately 50% of individuals aged 65 years or older affected by MS [3,4]. Although the precise cause of MS remains unclear, it is thought to result from a combination of genetic, metabolic, environmental, dietary, and lifestyle factors [5,6]. The International Diabetes Federation (IDF) highlights lifestyle modification as the primary treatment for MS [7]. Rapid modernization and economic development across the Asia-Pacific region, particularly in South Korea, have contributed to lifestyle changes that have substantially increased prevalence [8-10]. In line with these recommendations, the IDF advocates increased physical activity, dietary modifications, and a 5-10% reduction in body weight. Effective management of MS requires both exercise and proper nutrition, which together play essential roles in improving metabolic health [11]. Pharmacotherapy targeting dyslipidemia, hypertension, or insulin resistance should be considered only when lifestyle interventions are insufficient [12].
Recent research has underscored the importance of mineral water intake in managing metabolic disorders, given the essential roles minerals play in glucose metabolism, insulin sensitivity, and metabolic homeostasis [13]. Accordingly, interest has grown in the therapeutic potential of deepsea water (DSW) as a mineral-rich nutritional intervention for managing metabolic disorders [14]. DSW from depths greater than 200 m is rich in minerals, including magnesium, potassium, zinc, and trace elements such as vanadium and chromium [14,15]. Experimental studies suggest that DSW may improve metabolic health by regulating glucose and lipid metabolism and by modulating obesity- and diabetes-related molecular pathways [14-16]. These findings have fueled growing interest in DSW as a potential nutritional strategy for the prevention and management of MS.
For patients with MS, a combination of resistance and aerobic exercises is highly recommended17. Despite the well-established benefits of physical activity in managing MS, adherence to exercise programs remains a significant challenge [18]. The World Health Organization (WHO) reports that 25% of adults and 80% of adolescents are physically inactive, partly because of societal and lifestyle changes globally [19]. To address these challenges, researchers have explored innovative exercise interventions to enhance adherence and motivation. Recent advances in exergaming and virtual reality (VR) technologies offer new opportunities to engage individuals in physical activity [20]. Exergames, which combine physical activity with interactive gaming, have been shown to improve motivation and psychological and physical health outcomes [18]. Among these technologies, Kinect-based mixed reality (KMR) is particularly promising because it utilizes a Kinect sensor to track 25 body joints and creates an immersive mixed-reality environment that integrates VR and augmented reality [21]. Previous studies have demonstrated the effectiveness of KMR in various populations including cancer survivors, older adults with sarcopenia, and those with mobility limitations [21-24]. Regarding metabolic health, studies suggest that KMR exercise is effective in managing MS components such as blood glucose levels and blood pressure [25].
Although previous studies have demonstrated the individual effects of DSW consumption and KMR exercise on metabolic health, evidence for their combined effects in individuals with MS remains limited. Because DSW supplementation and exercise may improve metabolic health through distinct physiological mechanisms, their combined effects may offer a more comprehensive strategy for managing MS. Therefore, this study investigated the effects of an 8-week intervention involving KMR exercise and DSW consumption, administered individually or in combination, on the components of MS.
METHODS
Participants and Recruitment
Participants were recruited through social networks and online communities in South Korea. Before participating in the study, all participants were informed of its purpose and design and voluntarily provided written informed consent. The sample size was estimated using G*Power (version 3.1, Germany) for repeated-measures analysis of variance (ANOVA). Assuming a medium effect size (Cohen’s f = 0.25), an alpha level of 0.05, and 0.80 statistical power, the minimum required sample size was 48 participants. Accounting for the anticipated dropout rate, 83 participants were screened for eligibility.
The inclusion criteria were adults aged 30-65 years who met the diagnostic criteria for MS. MS was defined by the National Cholesterol Education Program Adult Treatment Panel III [26] and the Korean Society for the Study of Obesity criteria. MS was diagnosed when three or more of the following five criteria were present: (1) abdominal obesity (waist circumference of 90 cm in males and 85 cm in females); (2) elevated blood pressure (systolic ≥ 130 mmHg or diastolic ≥ 85 mmHg, or current antihypertensive treatment); (3) reduced HDL cholesterol (fasting levels below 40 mg/dL in males and 50 mg/dL in females, or ongoing lipid-lowering therapy); (4) elevated triglycerides (fasting levels ≥ 150 mg/dL or triglyceride-lowering medication); (5) impaired glucose regulation (fasting glucose ≥ 100 mg/dL, physician-diagnosed diabetes, or current antidiabetic medication/insulin therapy).
The exclusion criteria were as follows: (1) individuals with acute hepatitis or malignant tumors within 1 month before enrollment; (2) individuals who had experienced myocardial infarction within the previous 6 months; (3) individuals with peripheral vascular disease or dementia; (4) individuals who had engaged in regular moderate- to high-intensity exercise within the past 3 months; (5) individuals with a current or prior history of stroke; (6) individuals with serious medical conditions contraindicating exercise; (7) individuals who had participated in another clinical trial within 2 months before screening; (8) pregnant or lactating women; (9) individuals with local or systemic inflammatory conditions, including rheumatoid arthritis or other autoimmune diseases; (10) individuals who had experienced weight loss exceeding 10% within the past 3 months; and (11) regular consumers of mineral supplements.
Study Procedure
A schematic of the study design is shown in Figure 1. Before the pre-test, participants were fully informed about the experimental procedures. The pre-test comprised assessments of blood pressure, body composition, blood analysis, quality of life, MS score, diet recall, and physical activity. Participants were screened for eligibility based on pre-test results. Eligible participants were randomly assigned in a 1:1:1:1 ratio to one of four groups using a computer-generated random number sequence: (1) control (CG), (2) DSW consumption (WG), (3) KMR exercise (EG), and (4) DSW consumption and KMR exercise (WEG). All measurements and exercise sessions were conducted in a dedicated research laboratory at the Sports Science Building, Seoul National University, under controlled temperature (22-24°C) and relative humidity (45-55%). The exercise groups (EG and WEG) were asked to attend the exercise center three times a week for 8 weeks, and the water consumption groups (WG and WEG) were instructed to consume 440 mL of DSW daily for 8 weeks. All participants were instructed not to alter their regular lifestyle and dietary habits throughout the study period. Participants were also instructed to maintain their usual medication regimens during the intervention period. Participants who changed their medication type, dosage, or adherence during the study were excluded from the final analysis. A 3-d dietary recall was used to assess dietary habits, and participants received telephone reminders every 2 weeks to reinforce adherence to the study protocol. After the 8-week intervention, the post-test was conducted within 7 d of completing the intervention, using the same procedures as the pre-test. This study was performed in accordance with the principles of the Declaration of Helsinki and was approved by the Seoul National University Institutional Review Board (IRB No. 2309/004-025).
Figure 1. A flowchart of the study protocol.
CG = control group; WG = deep-sea water consumption group; EG = Kinect-based mixed reality exercise group; WEG = deep-sea water consumption and Kinect-based mixed reality exercise group; GPAQ = global physical activity questionnaire; BDI = beck depression inventory; QOL = quality of life questionnaire; MS score = metabolic syndrome score; FPG = fasting plasma glucose; TC = total cholesterol; HbA1c = Hemoglobin A1c; HDL = high-density lipoprotein; LDL = low-density lipoprotein.
Supplementation
The DSW was collected at a depth of 1,500 m near Dokdo Island, in the East Sea of Korea. The DSW underwent two filtration steps, was desalinated, and was processed into mineral-enriched drinking water manufactured and supplied by QBM Co., Ltd. (Gangwon-do, Korea). The major mineral compositions of the DSW are presented in Table 1. The total hardness of the DSW was 1,517 mg/L. The DSW was supplied to participants in 5 L pouches, and each participant received a standardized measuring cup for accurate daily consumption. Participants were instructed to consume 440 mL daily without exceeding or falling below the prescribed amount. To preserve the original properties of DSW, participants were instructed not to heat the water or mix it with other beverages. Based on a total magnesium concentration of 370 mg/L (Table 1), the prescribed DSW intake of 440 mL/d provided approximately 163 mg of magnesium/d, which was lower than the magnesium dose (350 mg/d) administered in a previous clinical trial of magnesium-enriched DSW27. To ensure compliance, participants were required to maintain daily consumption logs throughout the intervention period and document their intake on the provided log sheets.
Table 1.
Mineral components of the deep-sea water supplement
| Component | Mixing ratio (%) | Mineral | mg/L | |
|---|---|---|---|---|
| Main component | Mineral-enriched desalted deep-sea water | 99.95 | Magnesium (Mg) | 320 |
| Potassium (K) | 128 | |||
| Sodium (Na) | 144 | |||
| Minor component | Magnesium chloride | 0.05 | Magnesium (Mg) | 50 |
| Total hardness | 1517 | |||
Exercise Program
A KMR system (Virtual Mate; My Benefit, Seoul, Korea) was used for the exercise intervention (Figure 2). The training session consisted of a 40-min circuit workout with three phases: a 5-min warm-up with dynamic stretching and joint mobility exercises, a 30-min main exercise phase, and a 5-min cool-down with static stretching exercises. The main exercise phase comprised three consecutive circuit sets, each separated by 2-min recovery intervals. Each circuit included eight exercise tasks, each performed for 45 s, followed by 15 s of transition or recovery time. Representative exercises included arm walking, bird dog, split squat, highknee marching, two-arm dumbbell rows, and standing pike crunch. The exercise protocol was adapted from a previous pilot study [25].
Figure 2.
Exercising with Kinect-based mixed reality device.
The KMR system continuously monitored participants’ movements during the exercise using a Kinect-based motion-tracking system. Real-time exercise information, including repetition count, exercise duration, and movement instructions, was displayed on the monitor. Participants also received immediate visual and auditory feedback on task completion and exercise performance, enabling immediate correction of movement errors.
For upper-body resistance exercises, males used 5 kg dumbbells, and females used 3 kg dumbbells. Participants were instructed to maintain proper exercise technique throughout the session and complete at least 80% of prescribed repetitions. Adherence and movement quality were monitored in real time using the KMR system. Exercise intensity was prescribed at moderate to high levels, as measured by the Rating of Perceived Exertion scale.
Measurements
1. Nutrient intake
Dietary intake was assessed using a 3-d dietary recall during both pre- and post-tests. The collected dietary records were analyzed using Can Pro 6.0 software (The Korean Nutrition Society, Seoul, Korea) to evaluate total energy intake.
2. Blood pressure
After a 5-min seated rest, systolic and diastolic blood pressure were measured using a blood pressure device (BPBIO750, InBody Co., Seoul, Korea).
3. Body composition
Height was measured to the nearest 0.1 cm using an extensometer. Body composition parameters, including weight, skeletal muscle mass, fat mass, body mass index, and body phase angle, were assessed using bioelectrical impedance analysis (InBody770, InBody Co., Seoul, Korea). Measurements were performed according to standard protocols, including an overnight fast, minimal clothing, removal of metallic items, and proper standing posture. Waist circumference was measured at the midpoint between the lowest rib and the iliac crest using a flexible measuring tape (SECA201, SECA, Hamburg, Germany) during exhalation.
4. Physical activity
Physical activity was assessed using both subjective and objective measurements. The Global Physical Activity Questionnaire (GPAQ) was used to evaluate participants’ physical activity levels across three domains: work, transport, and recreational activities. Developed by the WHO, the GPAQ has been widely used in more than 100 countries [28]. The GPAQ was administered at baseline and after the 8-week intervention to all participants. Daily step counts were monitored throughout the 8-week intervention using an Amazfit smartwatch (Amazfit GTS4, Huami, China) only in the non-exercise groups (CG and WG) to verify that participants maintained their habitual physical activity during the intervention.
5. Blood samples and assays
Participants were instructed to abstain from alcohol and vigorous physical activity for 24 h before blood collection, and to fast for at least 8 h. Approximately 10 mL of fasting venous blood was collected in the morning by a certified medical technologist after participants rested comfortably. Blood glucose levels were measured by the UV hexokinase method (Cobas 8000; Roche Diagnostics, Basel, Switzerland). Serum triglyceride, HDL cholesterol, LDL cholesterol, and total cholesterol levels were measured using enzymatic colorimetric assays (Cobas 8000; Roche Diagnostics, Basel, Switzerland). HbA1c levels were measured using a turbidimetric inhibition immunoassay (Cobas c513, Roche Diagnostics).
6. Quality of life
Quality of life was assessed using the Korean version of the World Health Organization Quality of Life BREF (WHOQOL-BREF). This 26-item questionnaire assesses four domains of quality of life: physical health, psychological health, social relationships, and environmental health [29]. Developed by the WHO, the WHOQOL-BREF was designed for cross-cultural comparisons in population-based studies [30,31].
7. MS score
The MS score was calculated from five components defined by the inclusion criteria. One point was assigned to each component that met or exceeded the diagnostic threshold, yielding a total score ranging from zero to five. Changes in MS scores between the pre- and post-test assessments were used to evaluate the effects of each intervention on MS. The MS score served as an objective outcome measure for assessing both the severity of MS and the effects of the intervention.
Statistical Analysis
Data analysis was performed using GraphPad Prism version 10.1.2 (GraphPad Software Inc., San Diego, CA, USA). Results are presented as mean ± standard deviation. Statistical significance was set at P < 0.05. Before statistical analysis, normality was assessed using the Shapiro-Wilk test, and continuous variables satisfied the normality assumption. If normality was not met, appropriate non-parametric tests were applied. Group comparisons of baseline characteristics were conducted using one-way ANOVA, except for sex, which was analyzed using Fisher’s exact test. To evaluate differences across the four experimental groups, a two-way repeated-measures ANOVA was conducted to assess group × time interactions. Bonferroni-adjusted multiple comparisons were performed to evaluate within-group differences (pre- and post-test) for all variables. Between-group comparisons were performed when significant group × time interactions were observed. An additional non-parametric analysis using the Wilcoxon signed-rank test was performed to confirm within-group changes in MS scores. The extreme studentized deviation (ESD) method implemented in Graph-Pad Prism was prespecified for outlier detection before statistical analysis. Any outliers identified were excluded from the final analysis.
RESULTS
Forty-eight participants completed the 8-week intervention. To date, no adverse effects of DSW consumption have been reported. At baseline, participants had a mean age of 48.54 ± 9.46 years, height of 165.57 ± 8.85 cm, and weight of 78.44 ± 13.59 kg. There were no significant differences in baseline characteristics between the groups (Table 2). Additionally, there were no significant differences among the groups in dietary intake or physical activity levels (GPAQ) at either pre-test or post-test. The mean daily step counts remained stable throughout the 8-week intervention in both non-exercise groups, with no significant changes over time in either CG (P = 0.615) or WG (P = 0.762) (Supplementary Table 1A). The GPAQ results are presented in Supplementary Table 1B. Although the GPAQ scores showed a significant overall time effect (P = 0.013), neither the group effect (P = 0.898) nor the group × time interaction (P = 0.466) was significant. In the analysis of HbA1c values, one outlier was identified in the WG using the ESD method and subsequently excluded from the analysis (final n = 13 for HbA1c analysis in the WG). The intervention showed high adherence rates, with 98.4% and 99.2% adherence to exercise and DSW consumption, respectively.
Table 2.
Baseline characteristics of the study participants
| Characteristics | CG (n = 12) | WG (n = 14) | EG (n = 10) | WEG (n = 12) | P |
|---|---|---|---|---|---|
| Age (yr), mean ± SD | 50.75 ± 8.51 | 43.93 ± 8.70 | 48.90 ± 8.41 | 51.42 ± 11.02 | 0.16 |
| Sex, n (%) | |||||
| Male | 7 (58.3) | 7 (50.0) | 6 (60.0) | 6 (50.0) | 0.92 |
| Female | 5 (41.7) | 7 (50.0) | 4 (40.0) | 6 (50.0) | |
| Medications, n | |||||
| Anti-hypertensive drugs | 4 | 5 | 4 | 7 | |
| Anti-dyslipidemia drugs | 5 | 3 | 5 | 6 | |
| Hypoglycemic drugs | 2 | 1 | 1 | 3 | |
| Anthropometry, mean ± SD | |||||
| Height (cm) | 167.23 ± 8.19 | 164.24 ± 7.93 | 165.06 ± 8.92 | 165.90 ± 11.08 | 0.86 |
| Weight (kg) | 79.31 ± 9.98 | 79.26 ± 12.39 | 73.64 ± 14.86 | 80.62 ± 17.31 | 0.66 |
| Skeletal muscle mass (kg) | 28.49 ± 5.28 | 27.97 ± 5.96 | 27.31 ± 7.10 | 29.13 ± 7.76 | 0.93 |
| Fat mass (kg) | 27.90 ± 8.63 | 28.93 ± 9.67 | 24.37 ± 5.99 | 28.18 ± 9.43 | 0.63 |
| BMI (kg/m²) | 28.52 ± 4.59 | 29.41 ± 4.65 | 26.85 ± 3.91 | 29.05 ± 4.20 | 0.54 |
| Waist circumference (cm) | 98.85 ± 5.24 | 97.68 ± 9.49 | 93.75 ± 9.38 | 97.13 ± 9.23 | 0.56 |
| Hematology, mean ± SD | |||||
| Glucose (mg/dL) | 90.67 ± 28.54 | 113.64 ± 35.11 | 88.80 ± 10.75 | 103.67 ± 15.30 | 0.06 |
| Triglycerides (mg/dL) | 197.42 ± 88.83 | 165.14 ± 71.49 | 194.30 ± 108.72 | 148.25 ± 49.43 | 0.40 |
| HDL (mg/dL) | 46.33 ± 8.47 | 49.07 ± 11.04 | 52.10 ± 12.18 | 53.92 ± 9.69 | 0.31 |
| Blood pressure (mmHg), mean ± SD | |||||
| Systolic | 137.17 ± 18.73 | 136.86 ± 15.93 | 138.10 ± 5.88 | 139.42 ± 16.28 | 0.98 |
| Diastolic | 85.25 ± 12.45 | 86.50 ± 14.05 | 83.60 ± 8.00 | 88.00 ± 14.31 | 0.87 |
Mean ± standard deviation. P values represent between-group comparisons at baseline. Abbreviations: CG = control group; WG = deep-sea water consumption group; EG = Kinect-based mixed reality exercise group; WEG = deep-sea water consumption and Kinect-based mixed reality exercise group; BMI = body mass index; HDL = high-density lipoprotein.
Table 3 presents pre- to post-intervention changes in the measured parameters after 8 weeks. The CG showed no significant changes in any variables (P ≥ 0.05). In the WG, waist circumference decreased significantly from 97.68 ± 9.49 to 93.93 ± 10.63 cm (P = 0.002) (Figure 3A), and systolic blood pressure decreased significantly from 136.86 ± 15.93 to 128.43 ± 11.84 mmHg (P = 0.023) (Figure 3E). The EG showed a significant decrease in waist circumference, from 93.75 ± 9.38 to 86.90 ± 11.04 cm (P < 0.0001) (Figure 3A), and in MS score, from 3.50 ± 0.71 to 2.60 ± 1.58 (P = 0.004) (Figure 3G). However, additional non-parametric analysis using the Wilcoxon signed-rank test showed a trend toward improvement that did not reach statistical significance (P = 0.094). Neither within-group nor between-group comparisons revealed significant differences in glucose, triglyceride, or HDL-cholesterol levels (Figures 3B-D). In contrast, participants in the WEG showed significant improvements in several other metabolic outcomes, including body weight, waist circumference, HbA1c level, diastolic blood pressure, and MS score. Body weight was significantly reduced from 80.62 ± 17.31 to 79.36 ± 18.12 kg (P = 0.022), waist circumference reduced from 97.13 ± 9.23 to 91.38 ± 8.40 cm (P < 0.0001) (Figure 3A), HbA1c was significantly reduced from 6.34 ± 0.57 to 6.10 ± 0.49% (P = 0.009), and diastolic blood pressure decreased from 88.00 ± 14.31 to 81.33 ± 10.94 mmHg (P = 0.024) (Figure 3F). The MS score in this group also improved significantly from 3.75 ± 0.62 to 2.83 ± 1.03 (P = 0.002) (Figure 3G). Additional Wilcoxon signed-rank analysis confirmed a significant reduction in the MS score (P = 0.016). Furthermore, this group showed significant increases in body phase angle, from 5.47 ± 0.74 to 5.68 ± 0.69 (P = 0.002), and in quality of life scores, from 56.28 ± 7.47 to 60.86 ± 15.77 (P = 0.031).
Table 3.
Changes in measured parameters (post-pre differences) during an 8-week intervention of Kinect-based exercise and deep-sea water consumption
| Variable | CG (n = 12) | WG (n = 14) | EG (n = 10) | WEG (n = 12) | Group x time P |
|---|---|---|---|---|---|
| Weight (kg) | 0.24 ± 1.54 | 0.23 ± 1.44 | -0.27 ± 1.16 | -1.26 ± 2.89* | 0.155 |
| Skeletal muscle mass (kg) | 0.27 ± 1.08 | -0.09 ± 0.56 | -0.12 ± 0.87 | -0.11 ± 0.77 | 0.616 |
| Fat mass (kg) | -0.21 ± 1.42 | 0.36 ± 1.74 | 0.02 ± 1.51 | -0.99 ± 2.48 | 0.315 |
| BMI (kg/m²) | 0.11 ± 0.49 | 0.14 ± 0.58 | -0.18 ± 0.59 | -0.40 ± 1.12 | 0.236 |
| Waist circumference (cm) | -0.68 ± 3.69 | -3.75 ± 4.02** | -6.85 ± 3.36**** | -5.75 ± 5.54**** | 0.007## |
| Body phase angle (°) | 0.02 ± 0.25 | -0.04 ± 0.25 | 0.10 ± 0.28 | 0.22 ± 0.15** | 0.061 |
| Glucose (mg/dL) | 0.42 ± 16.78 | -5.86 ± 13.76 | -0.90 ± 7.14 | -6.00 ± 8.33 | 0.464 |
| Triglycerides (mg/dL) | -30.42 ± 58.94 | 9.93 ± 87.51 | -42.90 ± 79.99 | -19.00 ± 39.21 | 0.238 |
| HDL (mg/dL) | 2.00 ± 4.07 | -3.07 ± 10.53 | 2.60 ± 7.50 | 4.42 ± 9.96 | 0.152 |
| LDL cholesterol (mg/dL) | 0.92 ± 15.54 | 0.86 ± 22.32 | 9.00 ± 22.27 | 10.58 ± 22.16 | 0.527 |
| Total cholesterol (mg/dL) | -5.08 ± 11.71 | -7.79 ± 26.35 | 1.70 ± 24.89 | 8.75 ± 22.47 | 0.257 |
| HbA1c (%) | -0.02 ± 0.15 | 0.15 ± 0.45 | 0.06 ± 0.12 | -0.24 ± 0.33** | 0.013# |
| Systolic blood pressure (mmHg) | -7.58 ± 9.53 | -8.43 ± 16.63* | -7.00 ± 12.17 | -4.50 ± 13.39 | 0.502 |
| Diastolic blood pressure (mmHg) | -4.58 ± 9.74 | -2.93 ± 9.86 | -0.40 ± 12.50 | -6.67 ± 7.13* | 0.896 |
| Quality of life (score) | 1.29 ± 6.02 | -1.61 ± 6.32 | 0.05 ± 7.93 | 4.32 ± 6.81* | 0.170 |
| Metabolic syndrome score | -0.42 ± 0.67 | -0.21 ± 0.89 | -0.90 ± 1.29** | -0.92 ± 0.90** | 0.177 |
Mean ± standard deviation. Values indicated are significantly different from baseline (pre) values.
P < 0.05,
P < 0.01,
P < 0.0001 differences from baseline.
P < 0.05,
P < 0.01 between group difference.
HbA1c was analyzed in 13 participants in the WG after exclusion of one outlier identified using the extreme studentized deviate (ESD) method. Abbreviations: CG = control group; WG = deep-sea water consumption group; EG = Kinect-based mixed reality exercise group; WEG = deep-sea water consumption and Kinect-based mixed reality exercise group; BMI = body mass index; HDL = high-density lipoprotein.
Figure 3. Changes in metabolic syndrome components of CG, WG, EG, WEG before and after the intervention.
(A) waist circumference (B) glucose (C) triglycerides (D) HDL (E) systolic blood pressure (F) diastolic blood pressure (G) metabolic syndrome score. Statistical analysis was performed using two-way repeated-measures ANOVA followed by Bonferroni-adjusted multiple comparisons (*P < 0.05, **P < 0.01, ****P < 0.0001 vs. baseline. #P < 0.05 between-group difference). Data are presented as mean ± standard deviation (SD). Abbreviations: CG = control group; WG = deep-sea water consumption group; EG = Kinectbased mixed reality exercise group; WEG = deep-sea water consumption and Kinect-based mixed reality exercise group; HDL = high-density lipoprotein.
Two-way repeated-measures ANOVA revealed significant group × time interactions for waist circumference (P = 0.007) and HbA1c (P = 0.013). A trend toward statistical significance was observed for the body phase angle (P = 0.061), whereas no significant group × time interactions were observed for the remaining variables. Post hoc comparisons showed significant between-group differences in waist circumference between the CG and EG (P = 0.020) (Figure 3A).
DISCUSSION
This study examined the independent and combined effects of DSW consumption and KMR exercise on MS in individuals with MS over an 8-week intervention. The combined intervention of daily DSW consumption and thrice-weekly KMR exercise led to significant reductions in waist circumference and MS scores. High adherence to both DSW and KMR exercises was observed throughout the intervention.
Waist circumference and systolic blood pressure were significantly reduced in the WG. Although DSW consumption showed clear benefits for anthropometric indices and blood pressure, no significant changes were observed in hematologic parameters. These findings are consistent with a previous study by Katsuda et al. [32], which investigated the effects of DSW on cardiovascular hemodynamics in hypercholesterolemic rabbits. In their 6-month intervention, DSW consumption significantly reduced systolic, diastolic, and mean arterial pressures, while hematologic parameters remained unchanged. Collectively, evidence from both human and animal studies suggests that the beneficial cardiovascular effects of DSW may occur independently of short-term changes in hematologic parameters and that the underlying mechanisms, particularly those related to blood pressure regulation, warrant further investigation.
Our findings on the effectiveness of the KMR exercises align with those of Oginni et al. [33], who demonstrated that technology-based exercise programs can significantly improve metabolic health. In their 6-week intervention study, virtual exercise programming led to significant improvements in waist circumference (P < 0.01) and other metabolic outcomes. These findings are consistent with our results, in which the KMR exercise significantly improved waist circumference and MS scores, suggesting that technology-based exercise programs may be an effective strategy for improving metabolic health in individuals with MS.
The combined intervention led to improvements across a broader range of metabolic outcomes than either intervention alone. However, these findings should be interpreted with caution because no statistically significant between-group differences were observed between the combined-intervention and single-intervention groups. Therefore, the present findings should be considered preliminary and should not be interpreted as evidence of synergistic effects.
Notably, both the EG and WEG showed reductions in MS scores below 3, which has important clinical implications. An MS score of 3 or higher is one of the diagnostic criteria for MS. Therefore, reducing MS scores below this threshold suggests that these interventions not only improved individual components of MS but also that some participants no longer met the diagnostic criteria for MS. These findings suggest that these interventions have the potential to improve the metabolic health of patients with MS.
Body phase angle, a key indicator derived from bioelectrical impedance analysis, reflects cellular integrity and nutritional status in individuals with MS [34]. Together with the observed improvement in quality of life (QOL), a key patient-reported outcome that is frequently impaired in individuals with MS [35], these findings suggest that the combined intervention may confer benefits beyond conventional metabolic outcomes.
Although within-group improvements were observed after the combined intervention, the relatively small number of statistically significant between-group differences suggests that these findings should be interpreted cautiously. A longer intervention period and larger sample size may be needed to more firmly establish the potential benefits of the combined intervention.
The high adherence rate observed in this study supports the feasibility of these interventions. Adherence was monitored using multiple methods. Participants in the non-exercise group used smartwatches to track activity levels, and DSW consumption was verified through regular telephone calls and daily self-reports. The high adherence to the KMR exercise in our study aligns with previous findings. A pilot study conducted during the COVID-19 pandemic reported high compliance with a KMR exercise program, suggesting that KMR may provide sustained motivational benefits compared with traditional exercise modalities [25].
Despite these strengths, this study had several limitations. First, the absence of a placebo water group limited our ability to isolate the effects of DSW consumption. Second, allocation concealment was not feasible, and blinding of participants and investigators was difficult given the nature of the intervention. Third, participants were instructed to maintain their usual medication regimens throughout the study period, and any participant who changed medication type, dosage, or adherence was excluded from the final analysis. However, the potential influence of medications on metabolic outcomes cannot be ruled out. Fourth, baseline heterogeneity among the participants, including differences in sex distribution and sample size across groups, may have influenced the study outcomes. Fifth, although multiple strategies were employed to monitor adherence, DSW consumption was assessed primarily through self-reported records, which may have introduced a reporting bias. Finally, although the four-group study design was intended to permit a 2 × 2 factorial analysis, it was not performed because of the limited sample size. Future studies with larger sample sizes are needed to evaluate potential additive or synergistic effects.
Future research should include placebo controls and stratified analyses with homogeneous participant groups to clarify intervention effects across demographics and health profiles. Studies with longer intervention periods (12-24 weeks) should better capture the full range of physiological adaptations. Integrating regular body composition assessments and detailed physical activity tracking provides comprehensive insights into intervention effects.
This study demonstrated that the combined intervention of DSW consumption and the KMR exercise improved MS parameters. The combined intervention resulted in improvements in multiple metabolic health parameters. However, further studies are needed to confirm its potential advantages over single interventions. The high compliance rates observed in this study indicate that the intervention was feasible. Additionally, improvements in waist circumference, HbA1c levels, body phase angle, and MS score are promising therapeutic outcomes for metabolic health management. Our results provide a basis for future research on MS treatments.
Footnotes
ACKNOWLEDGMENTS
The study sponsor/funder was not involved in the design of the study, nor in the collection, analysis, and interpretation of data or writing of the report, and did not impose any restrictions on the publication of the report. We express our sincere appreciation to our colleagues at the Health and Exercise Science Laboratory of Seoul National University for their support and assistance with this research.
FUNDING
This research was supported by a grant from the Korean Institute of Marine Science and Technology Promotion (20220027).
PREVIOUS PRESENTATION
Part of this study was presented at the 2024 International Congress on Obesity and Metabolic Syndrome (ICOMES 2024), held at Conrad Seoul, Seoul, Republic of Korea, on September 7, 2024.
The authors declare that they have no conflicts of interest related to QBM Co., Ltd., the supplier of the test product, or My Benefit, the manufacturer of the Kinect-based mixed-reality exercise system.
Supplementary Material
Physical activity monitoring during the intervention
REFERENCES
- 1.Blüher M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol. 2019;15:288–98. doi: 10.1038/s41574-019-0176-8. [DOI] [PubMed] [Google Scholar]
- 2.Máthéné Köteles É, Rafael B, Korom A, Vágvölgyi A, Ábrahám JE, Domján A, Szűcs M, Nemes A, Barnai M, Lengyel C, Kósa I. Physiological and psychological effects of a 12-week home-based telemonitored training in metabolic syndrome. Front Cardiovasc Med. 2023;9:1075361. doi: 10.3389/fcvm.2022.1075361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Lobene AJ. The increasing prevalence of metabolic syndrome in Korea: a multifarious disease with a multifactorial etiology. J Am Coll Cardiol. 2023;81:503–5. doi: 10.1016/j.jacasi.2023.05.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Huh JH, Kang DR, Kim JY, Koh KK. Metabolic syndrome fact sheet 2021: executive report. Cardiometab Syndr J. 2021;1:125–34. [Google Scholar]
- 5.Elder SJ, Lichtenstein AH, Pittas AG, Roberts SB, Fuss PJ, Greenberg AS, McCrory MA, Bouchard TJ, Jr, Saltzman E, Neale MC. Genetic and environmental influences on factors associated with cardiovascular disease and the metabolic syndrome. J Lipid Res. 2009;50:1917–26. doi: 10.1194/jlr.P900033-JLR200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Poulsen P, Vaag A, Kyvik K, Beck-Nielsen H. Genetic versus environmental aetiology of the metabolic syndrome among male and female twins. Diabetologia. 2001;44:537–43. doi: 10.1007/s001250051659. [DOI] [PubMed] [Google Scholar]
- 7.Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A consensus statement from the international diabetes federation. Diabet Med. 2006;23:469–80. doi: 10.1111/j.1464-5491.2006.01858.x. [DOI] [PubMed] [Google Scholar]
- 8.Kim MH, Lee SH, Shin KS, Son DY, Kim SH, Joe H, Yoo BW, Hong SH, Cho CY, Shin HS, Cho YJ, Oh JE. The change of metabolic syndrome prevalence and its risk factors in Korean adults for decade: Korea national health and nutrition examination survey for 2008-2017. Korean J Fam Pract. 2020;10:44–52. [Google Scholar]
- 9.Lee HJ, Chang JS, Ahn JH, Kim MY, Park KS, Ahn YS, Koh SB. Association between low muscle mass and non-alcoholic fatty liver disease diagnosed using ultrasonography, magnetic resonance imaging derived proton density fat fraction, and comprehensive NAFLD score in Korea. J Prev Med Public Health. 2021;54:412–20. doi: 10.3961/jpmph.21.387. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kim HJ, Lee KH, Lee JH, Youk H, Lee HY. The effect of a mobile and wearable device intervention on increased physical activity to prevent metabolic syndrome: observational study. JMIR Mhealth Uhealth. 2022;10:e34059. doi: 10.2196/34059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Aoi W, Naito Y, Yoshikawa T. Dietary exercise as a novel strategy for the prevention and treatment of metabolic syndrome: effects on skeletal muscle function. J Nutr Metab. 2011;2011:676208. doi: 10.1155/2011/676208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Scuteri A, Laurent S, Cucca F, Cockcroft J, Cunha PG, Rodríguez Mañas L, Mattace Raso FU, Muiesan ML, Ryliskyte L, Rietzschel E, Strait J, Vlachopoulos C, Völzke H, Lakatta EG, Nilsson PM. Metabolic syndrome across Europe: different clusters of risk factors. Eur J Prev Cardiol. 2015;22:486–91. doi: 10.1177/2047487314525529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Alghamdi M, Gutierrez J, Komarnytsky S. Essential minerals and metabolic adaptation of immune cells. Nutrients. 2023;15:123. doi: 10.3390/nu15010123. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Hwang HS, Kim HA, Lee SH, Yun JW. Anti-obesity and antidiabetic effects of deep-sea water on ob/ob mice. Mar Biotechnol. 2009;11:531–9. doi: 10.1007/s10126-008-9171-0. [DOI] [PubMed] [Google Scholar]
- 15.He S, Peng WB, Zhou HL, Fu XJ, Sun YH, Wang ZG. A combination of deep-sea water and fucoidan alleviates T2DM through modulation of gut microbiota and metabolic pathways. Pharmaceuticals (Basel) 2023;16:462. doi: 10.3390/ph16030462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Hwang HS, Kim SH, Yoo YG, Chu YS, Shon YH, Nam KS, Yun JW. Inhibitory effect of deep-sea water on differentiation of 3T3-L1 adipocytes. Mar Biotechnol. 2009;11:161–8. doi: 10.1007/s10126-008-9131-8. [DOI] [PubMed] [Google Scholar]
- 17.Earnest CP, Johannsen NM, Swift DL, Gillison FB, Mikus CR, Lucia A, Kramer K, Lavie CJ, Church TS. Aerobic and strength training in concomitant metabolic syndrome and type 2 diabetes. Med Sci Sports Exerc. 2014;46:1293–301. doi: 10.1249/MSS.0000000000000242. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Sato K, Kuroki K, Saiki S, Nagatomi R. The effects of exercise intervention using Kinect on healthy elderly individuals: a quasi-experimental study. Open J Ther Rehabil. 2014;2:38–44. [Google Scholar]
- 19.Qian J, McDonough DJ, Gao Z. The effectiveness of virtual reality exercise on individual’s physiological, psychological and rehabilitative outcomes: a systematic review. Int J Environ Res Public Health. 2020;17:4133. doi: 10.3390/ijerph17114133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Woessner MN, Tacey A, Levinger-Limor A, Parker AG, Levinger P, Levinger I. The evolution of technology and physical inactivity: the good, the bad, and the way forward. Front Public Health. 2021;9:655491. doi: 10.3389/fpubh.2021.655491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ahn SY, Sung YH, Bae JH, Lim BG, Li X, Kim DH, Seo DI, Park JJ, Kang HJ, Lee HJ, Lee CG, Ahn YS, Song W. Effect of unsupervised Kinect-based mixed reality fitness programs on health-related fitness in men during COVID-19 pandemic: randomized controlled study. J Mens Health. 2023;19:104–12. [Google Scholar]
- 22.Ahn SY, Sung YH, Bae JH, Lim BG, Song W. Reliability and validity of the Kinect-based mixed reality device: pilot study. Asian J Kinesiol. 2022;24:2–11. [Google Scholar]
- 23.Sung Y, Seo JW, Lim B, Jiang S, Li X, Jamrasi P, Ahn SY, Ahn S, Kang Y, Shin H, Kim D, Yoon DH, Song W. Machine learning for movement pattern changes during Kinect-based mixed reality exercise programs in women with possible sarcopenia: pilot study. Ann Geriatr Med Res. 2024;28:427–36. doi: 10.4235/agmr.24.0033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lim B, Li X, Sung Y, Jamrasi P, Ahn S, Shin H, Song W. Kinect-based mixed reality exercise program improves physical function and quality of life in breast cancer survivors: a randomized clinical trial. Cancer Res Treat. 2025;57:478–91. doi: 10.4143/crt.2024.758. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Ahn SY, Lee SW, Shin HJ, Lee WJ, Kim JH, Kim HJ, Song W. Effects of a 2-week Kinect-based mixed-reality exercise program on prediabetes: a pilot trial during COVID-19. J Obes Metab Syndr. 2024;33:54–63. doi: 10.7570/jomes23040. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.National Cholesterol Education Program Expert Panel . Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) NIH; 2002. [Google Scholar]
- 27.Ham JY, Shon YH. Natural magnesium-enriched deep-sea water improves insulin resistance and the lipid profile of prediabetic adults: a randomized, double-blinded crossover trial. Nutrients. 2020;12:515. doi: 10.3390/nu12020515. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Alghafri TS, Alharthi SM, Al-Farsi YM, Bannerman E, Craigie AM, Anderson AS. Correlates of physical activity and sitting time in adults with type 2 diabetes attending primary health care in Oman. BMC Public Health. 2018;18:85. doi: 10.1186/s12889-017-4643-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.De Willige GV, Wiersma D, Nienhuis FJ, Jenner JA. Changes in Syndr Relat Disord. 2022;20:532-42. quality of life in chronic psychiatric patients: a comparison between EuroQol (EQ-5D) and WHOQoL. Qual Life Res. 2005;14:441–51. doi: 10.1007/s11136-004-0689-y. [DOI] [PubMed] [Google Scholar]
- 30.WHOQOL Group Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychol Med. 1998;28:551–8. doi: 10.1017/s0033291798006667. [DOI] [PubMed] [Google Scholar]
- 31.Skevington SM, Lotfy M, O’Connell KA. The World Health Organization’s WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. Qual Life Res. 2004;13:299–310. doi: 10.1023/B:QURE.0000018486.91360.00. [DOI] [PubMed] [Google Scholar]
- 32.Katsuda SI, Yasukawa T, Nakagawa K, Miyake M, Yamasaki M, Katahira K, Mohri M, Shimizu T, Hazama A. Deep-sea water improves cardiovascular hemodynamics in Kurosawa and Kusanagi-hypercholesterolemic rabbits. Biol Pharm Bull. 2008;31:38–44. doi: 10.1248/bpb.31.38. [DOI] [PubMed] [Google Scholar]
- 33.Oginni J, Otinwa G, Gao Z. Physical impact of traditional and virtual physical exercise programs on health outcomes among corporate employees. J Clin Med. 2024;13:694. doi: 10.3390/jcm13030694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Bučan Nenadić D, Radić J, Kolak E, Vučković M, Novak I, Selak M, Radić M. Phase angle association with dietary habits and metabolic syndrome in diabetic hypertensive patients: a cross-sectional study. Nutrients. 2022;14:5058. doi: 10.3390/nu14235058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Badr HE, Saunders T, Carter A, Reyes Castillo L, Bayoumy O, Barrett M. Impact of lifestyle modification on quality of life in patients with metabolic syndrome: findings from the CHANGE program intervention study in Prince Edward Island, Canada. Metab Syndr Relat Disord. 2022;20:532–42. doi: 10.1089/met.2022.0056. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Physical activity monitoring during the intervention