Viscoelastic or viscoplastic glucose theory (VGT #36): Applying the VEGT or VPGT to study the cancer risk probability percentage versus medical conditions and lifestyle details over a 10+ year period from Y2012 to Y2022 based on the GH-Method: math-physical medicine (No. 617)

Abstract

Since 2012, the author has collected his body weight and fingerpiercing
glucose values each day. Next, he accumulated medical
conditions data including blood pressure (BP), heart rate (HR),
blood lipids along with lifestyle details of diet, exercise, sleep,
stress, water intake and daily routine details. Based on these
collected big data, he organized them into two main categories.
The first is medical conditions (MC) with 4 categories: weight,
glucose, BP, and lipids. The second is lifestyle details (LD) with
6 categories: food, exercise, water intake, sleep, stress, and daily
routines. Furthermore, he summarized and calculated the two
separate individual category scores of MC and LD. In this article, the author applies the viscoelasticity and viscoplasticity theories to conduct his research to discover some hidden behavior or relationship between the Cancer risk probability (as an output or strain) versus either MC score or LD score (as inputs or stresses). The hidden behaviors and relationships
between the output biomarker of Cancer Risk and the two input
biomarkers, MC score and LD score, are time-dependent and
change from time to time.