If you're a long time reader, you know that I like to experiment. A cornerstone of any good experiment is a hypothesis... and it's absolutely crucial to control variables... but no matter how well designed your experiment is, if you don't have a way to measure outcomes, you're just guessing about the overall effectiveness of what you're testing.
of the last month was within a 'boundary area' for me between health related experiments. This meant that it was a time to confirm or deny my hypotheses. Was what I doing having the intended consequences or not? How can I use the collected information to inform future experiments?
While wearables have become great ways to do much of this validation, there are still many things that require good old blood (and other) tests in order to get accurate measurements. Like many self-employed, I have terrible insurance, so basic tests aren't covered let alone things that are deemed 'non-essential'. Because of this,
I've been using InsideTracker (blog post coming soon!) to conduct (and analyze) many of my tests. The testing is done through Quest, so I can get the raw data. This is useful so that I can enter it into other systems so that I always have a running history that I can compare. SelfDecode is another service that I use in order to analyze this data.