Experiments are a great way to learn more about your body and your unique glucose response. Getting started on experiments can seem daunting. We are here to help!
We have put together this comprehensive guide that walks you through an overview of how to create great experiments through the utilization of the Scientific Method, experiment ideas, a step-by-step guide on how to create experiments in the app, and what to do with your experiment's findings.
Outline of Experiments
Part 1 includes a step by step manual for how to conduct great, scientific glucose experiments
Part 2 helps you create specific glucose experiments and provides ideas and suggestions
Part 3 shows you how to use the glucose experiments using the tab in the app
Part 4 explains what to do when you have a "bad" glucose response
Part 1: Learning How to do Great Glucose Experiments
To make the most of your experience while wearing a CGM, we recommend becoming an effective N of 1 researcher. In scientific literature, when an experiment only has one subject (N=1), the evidence is considered anecdotal. At NutriSense, however, N=1 testing is essential. You are here to learn about yourself after all. To become a proficient N=1 experimenter, we are going to take a step back in time to fifth-grade science class and rediscover the tenets of The Scientific Method.
1. Formulate a Question
There is no shortage of curiosities to explore in the world of health and longevity. These questions may arise from the latest news headline, your great aunt's advice, a favorite podcast, or trends you have noticed about yourself.
For example, maybe you particularly love oatmeal and want to see if this is a good component of your diet, so now your question becomes, "Will plain oatmeal negatively affect my glucose levels?"
2. Create a Hypothesis
Next, you suggest a possible answer in the form of a hypothesis. A good hypothesis has two important qualities. One is that it must be testable; an experiment can be set up to test how accurate your prediction is. Second, it must be falsifiable; an experiment can also be devised that might reveal your original prediction is incorrect.
Our hypothesis today is, “If I consume 1 cup of plain oatmeal then I will have a slight increase in glucose, but will stay within normal limits”. This is testable, because we can easily design an experiment to test exactly what is being asked. And it is also falsifiable, we could find that oatmeal actually does push us out of optimal glucose levels.
3. Test Your Hypothesis
When testing a hypothesis, we must control the number of variables, and try to remove any confounding factors. This is to make sure that we are truly testing the effect of our oatmeal, and not something else.
Tips for Testing:
Isolate the ingredient you are testing to tease out confounding factors. For example, blueberries and peanut butter in the oatmeal will make it hard to tell what is causing the change in your glucose. We can test the oatmeal with these foods later.
Eat the ingredient in isolation with 3 hours separating it from other foods. This will ensure that the response is due solely to the test food.
Control (as much as possible) for other factors. Aim to keep physical activity (type, intensity, and timing), sleep (quantity and quality), and stress levels as constant as possible.
Consider the time frame needed to draw conclusions. Your response to foods may be apparent quickly, but your response to an Intermittent Fasting regimen or a change in your workout routine may take a week or longer to fully understand.
4. Draw Conclusions & Iterate
Let’s suppose that you design a good experiment and discover that yes indeed, your hypothesis was correct! Glucose levels rose 20 points but remained within normal limits after consuming oatmeal. Is the science over? Can you firmly proclaim that oatmeal is always good and will never have a negative response? Unfortunately, it is never that simple. It is essential to be able to replicate your findings.
Let’s say that you repeat your experiment and see that you are not able to reproduce the same findings – you now have a blood sugar response of 160 (high!) after consuming 1 cup of plain oatmeal.
Now it is time to consider some confounding factors you may have forgotten during your experimental design. Running through the mental checklist of influencers is key – physical activity, sleep, stress, hydration, illness, hormones. Suddenly you realize that you skipped your morning workout. Now you repeat the experiment under more controlled conditions (after your morning workout), and see that your findings were indeed repeatable and your glucose remained within normal limits.
Whether your hypothesis was proven correct or incorrect, it can generate a new observation and more hypotheses to go with them. From this example, you might come out with the following things to test:
Hypothesis #1 – If I do 1 hour of HIIT exercise instead of weight lifting, I will have a lower glucose response.
Hypothesis #2 – If I add 1 scoop of plain protein powder to my 1 cup of plain oatmeal, I will have a lower glucose response than without the protein.
Hypothesis #3 – If I consume 1 cup of plain oatmeal as my second meal of the day, I will have a lower glucose response than if it is my first meal of the day.
Now that you have an understanding of the overall process of experimentation, we will work on developing a hypothesis for you to test!