Calibrating the estimated health age via metabolism index using GH-Method: math-physical medicine (No. 313)

Abstract

The author became interested in geriatrics in 2019, especially in regard to longevity. Prior to that in 2010, he studied and researched metabolism, endocrinology, and chronic diseases. In 2014, he applied topology concept and engineering finite element method to develop a mathematical model for estimating the state of human metabolism. The collected massive data amount of ~2 million on metabolism and diseases allowed him to extend his research work into longevity. In January 2020, he published his first paper on geriatrics regarding effective health age (No. 223). In July 2010, he further developed a simplified APP (application software) on the iPhone for estimating patients’ effective health age ( “ Health Age”) with or without chronic diseases to compare against their biological real age ( “ Real Age”). He then published his findings in paper, No. 292. By using data from four key medical conditions based on the health examination reports (4 biomarkers: weight, glucose, blood pressure, and lipids), and six lifestyle details input by the user (diet, water, exercise, sleep, stress, and daily life routines), this APP could instantly calculate and show both metabolism index (MI) score, and Health Age on