Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Sir Run Run Shaw Hospital | OTHER |
Not provided
Not provided
Not provided
Not provided
In this single-blind, randomized trial, 395 eligible volunteers, who have higher metabolic syndrome (MetS) risk and aged 20-65 years, will be assigned to one of two smartphone-based lifestyle intervention arms: 1) Programmed-smartphone intervention or 2) Programmed-smartphone plus dietitian intervention. Before and after 6-month intervention, "PhenFlex test" (PFT) was performed to examine and quantify improved metabolic flexibility.
This intervention trial will be conducted by researchers in Shanghai Institute of Nutrition and Health of the Chinese Academy of Sciences (CAS) collaborating with Zhejiang University affiliated Sir Run Run Shaw Hospital. The study protocol was approved by the Ethics Committees in Shanghai Institutes of Nutrition and Health, and in Sir Run Run Shaw Hospital.
The main aims of this study are to determine 1) efficacy of lifestyle interventions with different intensity in reducing MetS and its risk factors; 2) improved metabolic responses or flexibility defined by PFT-based homeostasis index; and 3) major genetic and nongenetic determinants for the efficacy of interventions among high MetS risk Chinese.
Metabolic syndrome, a cluster of multiple metabolic disturbances, including central obesity, dyslipidemia, hypertension, and hyperglycemia, is associated with 2-5-fold heightened risks of CVD and T2D. Compelling evidence showed that lifestyle intervention is one of effective approaches for preventing and controlling cardiometabolic diseases. However, there were considerably variations among different interventions and different persons. With widely available smartphone and APP-connected wearable devises, it is possible to provide programmed nutrition and lifestyle education to help participants achieve intervention targets, and closely monitor compliance. However, few studies investigated the efficacy of lifestyle interventions with programmed smartphone and APP-connected wearable devises in MetS management. Moreover, since present disease-based diagnoses and biomarkers may not adequately define health status, the concept of "re-redefining health" has attracted growing attention. The phenotypic flexibility and "PhenFlex test" are one of approaches to measure individuals' adaptive capacity to maintain hemostatic condition after having a standardized challenge drinker. To date, the PFT has been studied among 10,000 subjects in western countries and few studies, if any, have conducted in Chinese who have different genetic background and dietary patterns. It remains to be established whether and to what extent that the PFT-based hemostatic index system can precisely evaluate the metabolic health in Chinese.
In the current trial, 395 subjects with MetS risks were randomly assigned to either smartphone-based lifestyle intervention arms: 1) Programmed-smartphone intervention; or 2) Programmed-smartphone plus dietitian intervention. The intervention duration will be 6-month and then have 2-year follow-up. During starting and end of 6-month intervention, we included PFT during the physical examination hold in the Sir Run Run Shaw Hospital. All the subjects were given a standardized challenge drinker (75g glucose, 60 fat and 20g protein). Fasting and multiple postprandial time points samples (blood, t=0,1,3h) and urine and feces were collected to measure clinical and omics markers like metabolomics, gut microbiota and SNPs. Finally, the homeostasis index will be built to estimate improvement of individual metabolic health after the intervention. In conclusion, this study will provide scientific evidence and novel insights about the effectiveness of new intervention strategies and precise diagnostic and assessment system for cardiometabolic management.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Programmed smartphone intervention group | Active Comparator | Subjects will receive programmed-smartphone lifestyle intervention |
|
| Programmed smartphone plus dietitian intervention group | Experimental | Subjects will receive programmed-smartphone plus dietitian lifestyle intervention |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Programmed smartphone intervention | Behavioral | Interactive programmed lifestyle education based on smartphone for six month |
|
| Measure | Description | Time Frame |
|---|---|---|
| Weight | Weight will be assessed by Seca-255 (ScalesGalore) during each visit ,weight will also be assessed by Bluetooth scale at home | Baseline and month 6 |
| Measure | Description | Time Frame |
|---|---|---|
| Body mass index (BMI) | Body mass index (BMI) will be assessed by Seca-201(ScalesGalore) during each visit | Baseline and month 6 |
| Waist circumference | Waist circumference will be assessed by Seca-201(ScalesGalore) during each visit |
| Measure | Description | Time Frame |
|---|---|---|
| E-selectin concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| P-selectin concentration | Concentration at fasting and postprandial 60min and 3hours will be measured |
Inclusion Criteria:
Volunteers at high metabolic risk aged 20-65 who didn't participate in other studies in 3 months before the current research, having a certain level of education and normal cognitive ability, taking good care of himself/herself. MetS risk factors were identified by the definition proposed by the International Diabetes Federation criteria for Chinese adults. Participants should have central obesity (waist circumference ≥90 cm in men or ≥80 cm in women).
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Xu Lin, PhD | Shanghai Institute of Nutrition and Health, Chinese Acadamy of Sciences | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Sir Run Run Shaw Hospital;Hangzhou Dianzi University;China Jiliang University; Zhejiang Sci-Tech University | Hangzhou | Zhejiang | 310016 | China |
Not provided
| ID | Term |
|---|---|
| D024821 | Metabolic Syndrome |
| D009765 | Obesity |
| ID | Term |
|---|---|
| D007333 | Insulin Resistance |
| D006946 | Hyperinsulinism |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Programmed smartphone plus dietitian intervention | Behavioral | Interactive programmed lifestyle education based on smartphone plus dietitians support for six month |
|
| Baseline and month 6 |
| Blood pressure | Both systolic pressure and diastolic pressure will be assessed using electronic blood pressure monitor (Omron J750)during each visit and at home | Baseline and month 6 |
| Triglyceride | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Total cholesterol | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| LDL-C | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| HDL-C | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Glucose | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Metabolic Homeostasis Score | A metabolic homeostasis score is a composite score that includes aggregated changes in blood biomarkers (metabolites or biomarkers or index involved in carbohydrates metabolism such as glucose, C-peptide, Matsuda index etc.; metabolites or biomarkers involved in lipid metabolism such as high-density lipoprotein cholesterol, total cholesterol, triglyceride etc.; metabolites or biomarkers involved in protein/vitamin metabolism such as creatinine; inflammatory or cytokines such as interleukin-6 etc.; hormones; anthropometric measures etc.). The metabolic homeostasis score is a composite score, that is calculated by the average of the scores of above-mentioned features using a certain computational algorithm. The larger the metabolic homeostasis score is, the worse the homeostatic resilience of the person, and vice versa. | Baseline and month 6 |
| Body composition | Body composition will be assessed by InBody-720 multi-frequency bioelectrical impedance device. | Baseline and month 6 |
| Compliance | Behavioral compliance will be assessed by wearable devices and bluetooth devices. | Whole 6-month intervention |
| Baseline and month 6 |
| Vascular cell adhesion molecule-1(VCAM-1) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Intercellular adhesion molecule-1 (ICAM-1) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Amyloid A1(SAA1) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Tumor Necrosis Factor-α (TNF-α) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Interleukin-10(IL-10) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Interleukin-1b(IL-1b) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| C-reactive protein(CRP) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Retinol binding protein(RBP4) concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Adiponectin concentration | Concentration at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Metabolomics including profiling of free fatty acids and other metabolites | Metabolomics will be measured by LC-MS | Baseline and month 6 |
| Single nucleotide polymorphism (SNPs) | Mutations at specific sites will be detected by gene chip | Baseline |
| Gut microbiota 16S rDNA sequencing | Gut microbiota 16S rDNA will be sequenced | Baseline and month 6 |
| HbA1c | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Insulin | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Glucagon | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Glucagon-like peptide-1 | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Aspartate transaminase | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Gastric inhibitory peptide | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Alanine aminotransferase | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Serum creatinine | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| γ-glutamyl transpeptidase | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Urine creatinine | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Urea nitrogen | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| Uric acid | Values at fasting and postprandial 60min and 3hours will be measured | Baseline and month 6 |
| D009750 |
| Nutritional and Metabolic Diseases |
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |