Investigation of the triangular dual-correlations among weight, glucose, and blood pressure for 6.5 years using GH-method: math-physical medicine (No. 299)

Abstract

Gerald C Hsu

The author uses the math-physical medicine approach to investigate three sets of correlation between: (1) Weight vs. Glucose - Weight is measured in early mornings and Glucose consisting of daily average glucose, including both fasting plasma glucose (FPG) and three postprandial plasma glucose (PPG). (2) Weight vs. blood pressure (BP) - BP is measured in early mornings. (3) Glucose vs. BP. He utilized both time-series and spatial analysis of his “daily data” in comparison with his “annual data”. His selected study period is 6.5 years (2,394 days) from 1/1/2014 through 7/23/2020. The reason he chose this specific time period is due to his blood pressure (BP) data collection starting on 1/1/2014, while both weight and glucose data were collected since 1/1/2012. It is clear that, through statistical methods of time-series and spatial analysis, all of these three biomarkers, weight, glucose, and BP are correlated to each other. However, the following order ranking of correlation coefficients remain to be true between daily data and annual data: M1&M2 > M2&M3 > M1&M3 Daily: 81% > 54% > 50% Annual: 89% > 83% > 76% By reducing your body weight, your glucose values will then be lower. This strong relationship is the most obvious correlation. Similarly, your blood pressure will be lower when your glucose value is low. Finally, weight loss helps your blood pressure reduction as well. The author’s statistical analyses are based on his 100,000+ personal biomarker’s data within the last 6.5 years (2,394 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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