Appendix F. Data Science Case Study: Intermittent Fasting

Back in the early 1990s I attended Cal Poly San Luis Obispo and majored in nutritional science. I picked this degree because I was obsessed with being a professional athlete. I felt like studying nutritional science could give me an extra edge. I first found research about calorie restriction and aging.

I was also involved in self-experimentation in my nutritional biochemistry class. We centrifuged our blood and calculated LDL, HDL, and total cholesterol levels. In the same course, we supplemented with megadoses of vitamin C and then captured our urine to see what was absorbed. It turned out that nothing was absorbed in a healthy population of college students because the body intelligently responds to the absorption of nutrients by increasing absorption sensitivity when levels are low. Vitamin supplements are often a waste of money.

I took a year of anatomy and physiology and learned how to dissect the human body. I learned about the Krebs cycle and how glycogen storage works.1 The body produces insulin to increase blood sugar and stores it in the liver and muscle tissues. If those areas are “full,” it puts that glycogen into adipose tissue, or “fat.” Likewise, when the body is out of glycogen or aerobic activity is underway, fat tissue is the primary fuel. This storage is our “extra” gas tank.

I also spent a year at Cal Poly as a failed Division I Decathlete walk-on. One of the things I learned the hard way ...

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