This article is Part 17 of the author’s linear elastic glucose behavior study. It summarizes key conclusions from the first 16 segments of his research work regarding the data range of GH.p-modulus values [9 through 23]. This research report includes the following: (1) The author’s personal data and GH.p-modulus values; (2) The data and GH.p-modulus values of three US patients and two Myanmar patients; (3) The low-bound and high-bound analysis from eight hypothetical standard cases of different carbs/sugar intake amounts and post-meal walking steps; (4) The data with high quite GH.p-modulus values from a special investigation case using 285 egg meals with neuroscience influences. The following paragraphs describe his key variable definitions and mathematical operations of obtaining the GH.p-modulus: (1) Baseline PPG equals to 97% of fasting plasma glucose (FPG) value, or 97% * (weight * GH.f-Modulus). (2) Baseline PPG plus increased amount of PPG due to food, i.e., plus (carbs/sugar intake amount * GH.p-Modulus). (3) Baseline PPG plus increased PPG due to food, and then subtracts reduction amount of PPG due to exercise, i.e., minus (post-meal walking k-steps * 5). (4) The Predicted PPG equals to Baseline PPG plus the food influences, and then subtracts the exercise influences. The linear elastic glucose equation is: Predicted PPG = (0.97 * GH.f-modulus * Weight) +(GH.p-modulus * Carbs&sugar) - (post-meal walking k-steps * 5) Where, (1) Incremental PPG = Predicted PPG - Baseline PPG + Exercise impact (2) GH.f-modulus = FPG / Weight (3) GH.p-modulus = Incremental PPG / Carbs intake Therefore, GH.p-modulus = (PPG - (0.97 * FPG) + (post-meal walking k-steps * 5)) / (Carbs&Sugar intake) This study is a summarized report of the author’s previous 16 segments of research articles on linear elastic glucose theory. He focuses on the GH.p-Modulus using four different data groups which cover patients of different nationalities, varying time periods, comparison between pre-virus vs. COVID-19 periods, finger glucoses vs. sensor glucoses, hypothetical boundary analysis (upper bound and lower bound), and a special neuroscience study of egg meals to arrive at the following observed conclusion. In summary, the author presumes that most patients still having a reasonable normal lifestyles, their GH.p-Modulus value should be located between 1.0 and 6.0. In this study of linear elastic glucose theory, the GH.p-modulus indeed reflects the actual general health conditions and lifestyle details of a patient. Practical advice of GH.p-Modulus to patients (1) If you have a record for some of your glucoses, carbs/sugar intake amount, and post-meal walking steps, then you may use this equation to calculate your GH.p-Modulus: GH.p-Modulus = ((0.97*FPG) + (post-meal k-steps*5)) / (Carbs&sugar amount) (2) If you don’t have your data stored, then you may apply the following suggestions: If your diabetes conditions is moderate (HbA1C ~7.0 & glucose ~150 mg/dL), then use 1.8 to 2.2 for your GH.p-Modulus; and if your diabetes conditions is more serious (HbA1C >8.0 & glucose >180 mg/dL), then use 2.5 to 3.3 for your GH.p-Modulus. (3) Normally, the GH.p-Modulus should be within 1.5 to 2.5; however, if you want to be more conservative in predicting your PPG, then you may use the GH.p-Modulus greater than 3.0 in the following equation: Predicted PPG = (0.97 * FPG) + (GH.p-Modulus * carbs& sugar) - (post-meal walking k-steps * 5)