- Part one includes a step by step manual for how to do great, scientific glucose experiments
- Part two explains how to respond to a "bad" glucose response
- Part three provides specific glucose experiment ideas and suggestions
- Part four shows you how to use the glucose experiments tab in the app
Part One: Learning how to do great glucose experiments
To make the most of your experience while wearing a CGM, I 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.
Step One – 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?"
Step Two – 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.
Step Three – 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.
Step Four – 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.
Part Two: What if I Experience an Abnormal Glucose Response?
A one time spike from a meal does not mean that you should avoid that food forever; instead, it is a signal to do some experimenting. The goal of experimenting is to learn which foods, in what combinations, will be optimal for long-term health. Some spikes in the short-term are not going to have detrimental long-term effects.
For example, let's say you observed a glucose response of 160 mg/dL after consuming a meal with quinoa. You realize this is an above-normal response, so you want to do some digging before getting rid of your favorite food forever. Below are some further tests to explore:
- Try the meal at different times of the day - we have varying responses to the same food depending on when it is consumed.
- Try the meal as your first versus second meal - consuming food on a completely empty stomach versus partially empty will lead to a different response.
- Try testing the quinoa with varying levels of processing and ingredients - try different varieties such as partially pre-cooked, instant, frozen, and whole dried quinoa.
- Add in a protein to your quinoa, such as seared shrimp or sautéed tofu.
- Add small amounts of fat to your quinoa, such as slivered almonds or extra virgin olive oil.
- Try the meal before vs after a workout - we are much more insulin sensitive after we workout.
- Alter the overall portion size - decrease the quinoa from 1 cup to 1/2 cup and try increasing the portion of non-starchy vegetables.
If you have done all the testing and still have an elevated glucose response, then you can more confidently conclude that quinoa may not be a great food for you. Or, maybe you learned quinoa can sometimes cause you trouble but when consumed in smaller portions, with more vegetables, and after physical activity, your glucose looks great. Now you know you can still work quinoa into your lifestyle, but under specific conditions.
Part Three: Experiment Ideas
Always keep in mind how the "big five" are affecting your glucose responses. This includes the meal content, fasting and meal timing, physical activity, stress, and sleep. With that in mind, below are some experiment ideas to help get you started and spark some curiosity for self-exploration.
- Try the same portion sizes of different types of carbohydrates from different foods (i.e. carbohydrates from fruit, dairy, starchy vegetables, legumes, grains).
- Compare carbohydrates that vary on the scale of glycemic index - Some low GI foods include steel cut oatmeal, unpearled barley, blueberries, sweet potatoes, and beans. Medium GI foods include brown rice and apples, and high GI foods include white potatoes, pineapple, and white bread.
- Compare the impact of food processing by trying a food in its most natural state, such as steel cut oats, versus in a more processed state, such as instant oats.
- Try a carbohydrate consumed alone and then paired with various different protein and fat sources.
- See if your glucose responds differently to resistant starch, such as cooked and cooled potatoes versus a freshly cooked hot potato.
- Test various "healthy" food products, such as kombucha or protein bars to test the marketing claims.
- See how your glucose may differ depending on the form the food is in. Compare the same amount of grams of carbohydrates from a liquid versus solid form of food, such as an orange versus orange juice.
- How do sugar substitutes and other "zero sugar" foods affect glucose?
- See how different types of exercise may affect your glucose (HIIT versus prolonged cardio versus weight lifting).
- Do your glucose levels change when you go for a walk after meals?
- Does your overall average glucose level change when your workout is in the morning versus the evening?
- How does your average glucose change on a day when you workout vs a rest day?
- Try a meal both after exercise and with no exercise to see how it differs.
Fasting & Meal Timing
- Try the same exact meal after 18 hours of fasting versus the second meal of the day.
- Try the same dinner at 5pm versus 10pm, how does your fasting glucose the next morning change?
- Does your overall average glucose levels differ when your time-restricted eating window is between 6am-2pm versus 1pm-9pm?
- Try the same exact meal but at different times of the day.
- Experiment with the effects of fasting and how to best break a fast. Try shortening your eating window to see how it affects your glucose values, shift your eating window to during the day versus evening, and try breaking a daily fast with different types of meals.
- If you are feeling up to it, try an extended fast!
- How does a bad night of sleep affect your glucose levels the next day?
- How does an elevated glucose level before bedtime affect your sleep?
- How do your glucose values differ depending on which stage of the menstrual cycle you are in?
- How do glucose values change when traveling?
- How do you respond to coffee? Does glucose lower, increase, or remain stable?
Part four: Logging Experiments in the App
Utilize the experiments tab in the drawer menu of the app to group your meals into specific categories to visualize and track your glucose responses.
- Add a title, such as "Legumes"
- Add a description for yourself, such as "Testing different types beans, peas, and lentils"
- By selecting "manual", this means you have now created a new experiments category that you can manually add meals to. Now, you will have one centralized location to compare all of your legume-based meals.
- As time goes on and you log future meals with legumes, you can add that meal card to your experiment by tapping the 3 dots on the meal cards and selecting "add to experiment".
Manual experiments could include any variety of categories you are trying to track, such as your dinner meals, post-workout shake, or whole grains.
- Add a title, such as "Wine"
- Add a description for yourself, such as "Testing different types of wine brands"
- By selecting "automatic", this means you have now created a new experiments category that will automatically populate with past and future meal cards that match any keywords. If you type "wine" into the search box and do not set time parameters, you will be able to see all past and future meal cards with the word "wine" in the description.
Automatic experiments are great for monitoring or viewing meals that contain a specific food. Let's say that you have been testing different variations of your morning oatmeal, by adding the word "oat" to your experiments query you can now view all of your oatmeal experiments with their correlated mini-graphs to see which toppings worked best for you!
You can use the following operators for experiment queries:
- The comma is an
oroperator. For example
strawberries, blueberriesmeans that either or both of the keywords appear in the meal description. This is great if you are trying to create a broad category of experiments, such as "carbs".
- The plus is an
chocolate+coffeewould mean that both words have to appear in the description. This is great if you are searching for responses to a very specific food, such as "steel-cut oats". You can also use "&" in replacement of "+", they will work the same way.
- The exclamation mark is a "not" operator. Searching for
chocolate+!coffeemeans that chocolate has to be in the meal description and coffee has to not be there.