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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

机译:在美国农村地区难以获得医疗服务的情况下,通过代谢健康监视器应用程序为患者解决体重问题和胰岛素抵抗

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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.
机译:主要目标是在新陈代谢健康监控器应用程序的指导下自我治疗体重问题和胰岛素抵抗。已经开发了能量代谢的数学模型,通过使用腰围和静止代谢率的身体成分每两周两次连续测量,每天测量身体能量消耗和每两周输入一次,通过R比率估算脂肪量和胰岛素抵抗的每日变化大量营养素的摄入量。该模型是自适应的,并使用Kalman过滤器。使用明尼苏达州饥饿和过度喂养实验的数据进行的模拟研究已经证实,该模型对每日脂肪重量变化的预测误差为0.44±1.16 g /天。通过使用绝经后妇女饮食中的体重减轻和运动对胰岛素抵抗的影响,发现R值与HOMA-IR的相关系数为-0.8383,P值为0.0093。计算的高准确性和易用性表明,该方法可用于跟踪和自我治疗体重相关问题以及胰岛素抵抗。代谢健康监测器应用程序通过预测每日脂肪量变化和胰岛素抵抗变化,提供个性化的营养和锻炼。来自代谢健康监视器应用程序的信息反馈允许每天调整饮食和锻炼生活方式。代谢健康监控器完全支持远程医疗健康生活方式团队的远程医疗,远程咨询,远程监控和治疗的概念。

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