Fighting weight problems and insulin resistance with the metabolic health monitor app for patients in the setting of limited access to health care in rural America

The primary objective is self-treating weight problems and insulin resistance with the guidance of a metabolic health monitor app. A mathematical model of the energy metabolism has been developed to estimate daily changes of fat mass and insulin resistance by the R-ratio through biweekly serial measurements of body composition using waist circumference and resting metabolic rate, daily measurement of physical energy expenditure, and biweekly input of macronutrient intake. The model is self adaptive and uses the Kalman filer. A simulation study using the data of the Minnesota starvation and overfeeding experiment has confirmed that the model's prediction of daily fat weight change has an error of 0.44±1.16 g/day. The correlation coefficient between the R-ratio and HOMA-IR was found to be -0.8383 with P value of 0.0093 by using data from the Dietary Weight Loss and Exercise Effects on Insulin Resistance in Postmenopausal Women. The high accuracy of calculations and the easy applicability suggest that this method could be used for both tracking and self treatment of weight related problems along with insulin resistance. The metabolic health monitor app offers personalized nutrition and exercise by prediction of daily fat mass change and insulin resistance change. The feedback of information from the metabolic health monitor app allows for daily adjustment of dietary and exercise lifestyle. The metabolic health monitor fully supports concepts of tele-medicine, tele-consultation, tele-monitoring, and treatment by a remotely placed healthy lifestyle team.