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 the iPhone.

This paper aims at calibrating the accuracy of his estimated health age by varying one of its important parameters, amplification factor (AF), in his defined arithmetical formula:

Effective Health Age
= Real Biological Age *
(1+((MI-0.735)/0.735)/Amplification factor)

A healthy person or APP user should have lower values on the biomarkers and lifestyle details, which results in a lower MI score. This lower MI score (means healthier) would then make the health age below the real age, and vice versa. By maintaining a good lifestyle program with healthy medical examination outcomes, the overall metabolism status will be above standard; therefore, the immune system will be strong and effective. With strong immunity, their bodies will be able to defend against various diseases, including complications from chronic diseases (50% of death cases), cancers (29% of death cases), and infectious diseases (11% of death cases). As a result, heathy people will most likely become members of the “longevity club”.

When the author developed his arithmetical formula of health age, he inserted an AF inside the formula (see above). The reason is two-fold, first: AF could be used later for calibrating the accuracy of end results, and second, it would further raise the user’s awareness of metabolism importance on longevity. In this investigation, he chose AF values of 1, 2, and 4 to cover a reasonable range between the upper and lower bound. Based on the results of feasibility analysis in this article, he feels that the AF value of 2 seems to be the most suitable for real applications.

The following list demonstrates the age differences of these three groups:
The turning point date is 8/23/2014 where his MI reached the break-even line of 0.735.

Pre-8/23/2014(worse performance):
Health age = 74.5 & real age = 66.3
Post-8/23/2014(better performance): Health age = 63.6 & real age = 70.5
Total period: (average performance)
Health age = 66.7 & real age = 69.3

From the information above, it is obvious that his health condition has greatly improved; therefore, his body shows a younger age than his real age. As seen in Figure 4, it is clear that he has saved his own life, and hopefully, he can live a longer and healthier life.

This article describes his sensitivity analysis in order to achieve a better estimated health age using MI scores as his tool. He decided to use the AF value of 2 for the calculation of his estimated health age.

The difference between his health age and real age is -2.6 years using his “total average” daily data over 8.5 years from 1/1/2012 to 8/15/2020. However, by using his “annual” data for the calculation, then his age difference was +8 years in 2012 (health age was 72 with real age of 64) and -9 years in 2020 (health age is 64 with real age of 73).

This tool can be used by people with and without chronic diseases.

Metabolism is the fundamental building block for diabetes control, health maintenance, and longevity. The author developed this model, approach, and simple formula by himself; therefore, he must conduct research on this equation’s two vital influential factors, MI and AF. He spent 7 years on MI research and has a strong understanding of the MI’s applicability. AF is just a simple adjustment factor that makes the health age match closely to the user’s real medical and health conditions as much as possible. The author is not a fortune teller who uses a crystal ball to predict other people’s future life expectancy, but rather he is a scientist who applies solid scientific techniques with biomedical evidence to develop a simple arithmetic formula which can serve as a useful tool for the general population’s health maintenance and longevity purposes.

Keywords

geriatrics, medical conditions, diet, water, exercise, sleep, stress, chronic diseases, obesity, diabetes, hypertension, hyperlipidemia, cardiovascular disease, medical conditions, strong immunity, diabetes control, health maintenance, big vision, pure heart, integrity