Since 2012, the author has collected his body weight and finger-piercing 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 which change from time to time. The following two defined equations are used to establish the stress-strain diagram in a space-domain (SD): strain = ε = individual Cancer risk value at present year Stress = σ = η * (dε/dt) = η * (d-strain/d-time) = (viscosity factor η using individual MC score or LD score at present year) * (Cancer risk at present year - Cancer risk at previous year) / 1 year To offer a simple explanation to readers who do not have a physics or engineering background, the author includes a brief excerpt from Wikipedia regarding the description of basic concepts for elasticity and plasticity theories, viscoelasticity and viscoplasticity theories from the disciplines of engineering and physics in the Method section. In summary, the following three observations outline the findings from this research work: 1. From the TD waveforms, the correlation between Cancer risk and MC is 96%, while the correlation between Cancer risk and LD is also 96%. This means that the Cancer risk is highly correlated with both MC and LD, but lifestyle is more like a “root-cause” for Cancer risk even though many patients with cancer also suffer from other chronic diseases such as obesity, diabetes, hypertension, and hyperlipidemia. 2. From the SD stress-strain diagrams between CVD risk vs. MC and CVD risk vs. LD, these two curves are similar in shapes and appearance except for their stress scale (y-axis scale) which has a ratio of 1.75 to 1 (-1.4% for stress of MC and -0.8% for stress of LD; or an average MC score of 88% to the average LD score of 50%). This 1.75/1=1.75 ratio also influences the hysteresis loop area ratio of 0.005/0.003 = 1.72. In addition, both of these two stress-strain curves demonstrate viscoplastic behavior. Their largest strain change rate (Cancer risk change rate) occurs during the period between Y2012 and Y2017. 3. The comparisons for the calculated Cancer risk waveform versus two predicted Cancer risk waveforms due to both MC and LD using a viscoelastic perturbation model has shown an extremely high 98% to 99% prediction accuracy. However, the calculated Cancer risk versus the predicted Cancer risk based on LD has a 96% correlation, while the calculated Cancer risk versus the predicted Cancer risk based on MC has also a 96% correlation. This 96% of correlations further demonstrates the importance of MC and LD for Cancer risk reduction.
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