Body weight versus PPG, FPG, fluctuations of PPG and FPG and applying the viscoplastic energy model of GH-Method: mathphysical medicine (No. 949, VMT #348, 11/4/2023)

Abstract

Gerald C Hsu

The author utilizes statistical techniques to compute correlation coefficients (R) between two variables: his body weight (BW) and four measures of his glucose levels, namely fasting plasma glucose (FPG) in the early morning, postprandial plasma glucose (PPG) from three meals, maximum PPG minus minimum PPG (PPG fluctuations), and maximum FPG minus minimum FPG (FPG fluctuations). The Timedomain (TD) analysis is conducted for two sub-periods, yielding the following subsequent findings:

8/1/2018 - 11/3/2023:

FPG vs. PPG = 95% FPG fluctuations vs. PPG fluctuations = 24% (low)

1/1/2021 - 11/3/2023:

FPG vs. PPG = 79%

FPG fluctuations vs. PPG fluctuations = 65%

Y18-Y23 annual data correlations of BW vs. 4 biomarkers:

PPG = 94%

FPG = 90%

PPG fluctuations = 91%

FPG fluctuations = -4% (none)

All of the aforementioned correlations surpass 90%, signifying the presence of significant similarities in curve-shape between BW and PPG, FPG, as well as PPG fluctuations. However, there is no correlation (-4%) observed between BEW and FPG fluctuations. This indicates that not only does his FPG fluctuation exhibit a higher average value (36 mg/dL, exceeding the threshold of normal value of 30 mg/ dL), but it also lacks shape similarity (correlation) with his body weight curve. Consequently, the biomarker of his FPG fluctuation warrants special attention.

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