Investigation the importance of metabolism on body weight and glucose for 8.5 years using GH-Method: math-physical medicine (No. 300)

Abstract

Gerald C Hsu

The author uses GH-method: math-physical medicine (MPM) approach to investigate three sets of correlation between: (1) Weight vs. Metabolism Index (2) Glucose vs. Metabolism Index (3) Weight vs. Glucose - Weight is measured in early mornings and Glucose consists of daily average glucose, including both fasting plasma glucose (FPG) and three postprandial plasma glucose (PPG). He utilized time-series analysis on both his “daily data” and his “annual data” for comparison. His selected study period was 8.5 years (3,124 days) from 1/1/2012 through 7/23/2020. The reason for this specific time period was due to his weight (M1) and glucose (M2) data collection starting on 1/1/2012 along with the calculation of his metabolism index (MI) values. It is clear that, through his sophisticated math-physical medicine of metabolism and then statistical method of time-series analysis, all of these three biomarkers, weight, glucose, and metabolism index are proven to be highly correlated to each other. The following order ranking of correlation coefficients remained to be true between daily data and annual data: M1&MI > M2&MI > M1&M2 Daily: 84% > 72% > 61% Annual: 91% > 81% > 67% In other words, if you manage your metabolism (4 medical conditions and 6 lifestyle details) by controlling your disease conditions and monitoring your lifestyle details, your body weight and glucose will reduce accordingly. The author’s analyses is based on his personal biomarkers of two million data within 8.5 years (3,124 days) has further proven a simple and clean conclusion that has already been observed by many clinical physicians and healthcare professionals from their patients.

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