This clinical study is designed to evaluate the providing of a computational prediction engine for optimization of personalized nutrition Personalized recommendations for effective diet, lifestyle and activities based on the patient's parameters measurements and reactions will be provided on a bi-weekly basis, all Lab tests and dietician control will be performed twice a month.
Pre-diabetic and pre-metabolic syndrome patients will be recruited to the study for a period of one year. After measurement of individual's parameters changes as blood tests, gut microbiome, urine tests, blood pressure, heart performance, body circumferences, mood and mental status as well as monitoring each individual's food intake - a model to predict individual's body reaction according to lifestyle, eating and activity habits will be built. Personalized recommendations for effective diet, lifestyle and activities based on the patient's parameters measurements and reactions will be provided on a bi-weekly basis, all Lab tests and dietician control will be performed twice a month.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
PREVENTION
Masking
NONE
Enrollment
500
Personalized recommendations for effective diet, lifestyle and activities based on the patient's parameters measurements and reactions
To determine number of participants with reduced BMI
Change at 12 months
Time frame: One year
To determine number of participants with reduced hA1C
Change at 12 months
Time frame: One year
To determine number of participants with reduced cholesterol
Change at 12 months
Time frame: One year
Type of intestinal microorganisms
The participants microbiome will be analyzed before and after the trial. The type of microorganisms will be determined by microbiological measurements.
Time frame: One year
Number of intestinal microorganisms
The participants microbiome will be analyzed before and after the trial. The number of microorganisms will be determined by microbiological measurements.
Time frame: One year
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