FPG in early morning versus body weight, body temperature, and sleep score and applying the viscoplastic energy model of GHMethod: math-physical medicine (No. 947, VMT #346, 10/27/2023)

Abstract

Gerald C Hsu

The author employs statistical methods to calculate correlation coefficients (R) between his fasting plasma glucose (FPG) in the early morning and three key biomarkers: body weight (BW), body temperature (BT), and sleep score (SS). The author's time-domain (TD) analysis reveals the following three findings:

• The correlation (R) between FPG and BW is 84% over the period from 1/1/13 to 10/27/23. - FPG and BT exhibit a 75% correlation over the period from 1/1/21 to 10/27/23.

• FPG and SS are correlated at 76% over the period from 1/1/15 to 10/27/23.

All of these three correlations exceed 75%, indicating significant shape similarities existed between FPG curve and these three influential waveforms. It's worth noting that these correlations are based on different data collection periods with different starting dates and the same ending date.

Consequently, these three influential factors are chosen as input stresses, while FPG is considered as the output strain, for the analysis of a space-domain viscoplastic medicine theory (SD-VMT).

In this SD-VMT analysis, he constructs a stress-strain (input-output) diagram and quantifies the enclosed area within the stressstrain curve as the corresponding energy value.

The resulting SD-VMT energy ratios are as follows:

• FPG vs. BW = 40%
• FPG vs. BT = 39%
• FPG vs. SS = 21%

Interestingly, when using the VMT prediction method, the predicted FPG versus the measured FPG demonstrates an impressive 99.8% prediction accuracy and a 69% correlation.

In summary, these findings suggest that both body weight and body temperature exhibit stronger associations with FPG compared to the sleep score. However, even the sleep score maintains a noticeable and reasonably strong relationship with FPG.

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