How to Use & Interpret a Continuous Glucose Monitor (CGM) | Dr. Casey Means & Dr. Andrew Huberman

00:00:00.000 | The way I think about a glucose monitor, first of all, I'll say the purpose of the glucose

00:00:06.560 | monitor is not to game the system and get flat glucose.

00:00:11.160 | The purpose of the glucose monitor is curiosity.

00:00:14.000 | It's to start to understand how essentially an MRI for how all of our different dietary

00:00:22.080 | and lifestyle strategies are creating this readout of glucose in our body, which I think

00:00:26.280 | can be really interesting.

00:00:27.280 | And in a world where so many cards are stacked against us with diet and lifestyle and where

00:00:31.920 | there's a lot of confusion about what's right for us, that can be very helpful in actually

00:00:36.240 | reducing the confusion and the cognitive load of our choices.

00:00:40.360 | We know that keeping your blood sugar through the course of a lifetime in a low and healthy

00:00:47.360 | range, so I don't mean up and down spikes during the day, but keeping your blood sugar

00:00:51.080 | healthy throughout the course of your lifetime is probably the best thing we can do for longevity,

00:00:56.360 | staying insulin sensitive, staying out of the diabetic range.

00:01:00.400 | And so one thing the glucose monitor does for us is just give us more awareness and

00:01:06.120 | agency into what the trends of our glucose are over time, as opposed to a literally one

00:01:13.320 | data point snapshot once a year in the doctor's office, which is what the majority of us are

00:01:18.200 | used to.

00:01:20.200 | I really love the idea that people who are able to wear glucose monitors every now and

00:01:25.720 | again, maybe once a year, maybe more than once a year, they know what their glucose

00:01:31.040 | is.

00:01:32.040 | And so they're never going to walk into a doctor's office and have a bomb dropped on

00:01:36.280 | them about prediabetes or type 2 diabetes, because you have the data, which is ultimately

00:01:41.600 | I hope the world that we can move towards for a lot of biomarkers.

00:01:44.200 | So you can see trends over time, which I think is very valuable.

00:01:47.920 | One thing that's fascinating in terms of early prediction of metabolic disease is that you

00:01:53.240 | can see how long it takes your glucose to come down after a meal.

00:01:57.360 | So in a normal, healthy, insulin sensitive body, even if the glucose goes way up, it

00:02:02.360 | should come way down very quickly, because the insulin is binding to insulin receptors

00:02:06.240 | and the glucose is getting taken up, and it'll lower.

00:02:09.680 | What is quickly over the course of--

00:02:11.000 | It should be down by two hours.

00:02:13.840 | But from what I've actually seen in our most insulin sensitive people and also in research

00:02:18.320 | that looks at young healthy populations, you should basically be spiking and coming down,

00:02:23.120 | spike about 45 minutes and come down hour and a half, 90 minutes to two hours.

00:02:27.320 | But if--

00:02:28.320 | This is after, sorry, after last bite?

00:02:31.080 | After last bite, although it's hard to kind of exactly know.

00:02:33.640 | But yeah, meal is over, I would say about 45 minutes to go up to the peak and then start

00:02:37.480 | coming down very quickly.

00:02:39.240 | Now if you start to see that glucose is going up and then trailing very slowly back down

00:02:47.160 | to normal, maybe taking more than two hours, three hours, that is going to be one of those

00:02:52.820 | early indicators of potential insulin resistance.

00:02:56.080 | Your body's not clearing the glucose, but that's not a metric that we use in standard

00:03:00.280 | practice at all.

00:03:02.600 | And I've actually seen myself very insulin sensitive.

00:03:06.040 | My insulin is like 2.5, and if I don't sleep and I am stressed and I have been sitting,

00:03:13.040 | my glucose will take way longer to come down.

00:03:15.280 | I have become transiently insulin resistant.

00:03:17.840 | So I think that's just fascinating to see that.

00:03:19.640 | So looking-- what that ultimately-- the metric that we call that is area under the curve.

00:03:24.920 | You want a low area under the curve, AUC, after a glucose spike.

00:03:29.080 | So you want to spike and come down quickly.

00:03:31.240 | That's going to-- if you shade the area under the curve, it's a small amount.

00:03:35.220 | If you go up and then trail off for two to three hours, that's going to be a lot of shading

00:03:42.200 | under that curve, and high AUC is associated with insulin resistance, basically.

00:03:47.440 | Another thing that you can see is essentially glycemic variability.

00:03:55.360 | And glycemic variability, GV, is a metric of how spiky your curves are.

00:04:00.600 | Fascinating paper out of Michael Schneider's lab at Stanford in 2018 called "Glucotypes

00:04:08.200 | Show New Patterns of Glucose Dysregulation," totally landmark study.

00:04:13.440 | But basically, they put continuous glucose monitors on non-diabetic individuals who,

00:04:18.040 | by standard criteria of diabetes, do not have diabetes.

00:04:21.780 | And he showed that on a CGM, a continuous glucose monitor, you have these low variability

00:04:28.480 | people that are pretty much flat throughout the day with little teeny, little teeny rolling

00:04:32.520 | hills after their meals.

00:04:33.880 | You have moderately spiky people.

00:04:35.360 | And then you have very spiky people who are going up, down, up, down, up, down, up, down.

00:04:39.120 | When you correlate those different patterns of glycemic variability in non-diabetic people,

00:04:44.280 | you find that the spikier they are, the worse their biomarkers are metabolically across

00:04:48.560 | the board, insulin, triglycerides, et cetera.

00:04:51.520 | So basically, they're showing signs through variability of underlying dysfunction that

00:04:57.440 | you would never know from a standard test.

00:05:00.080 | Those are the people who I imagine are probably going to go on to develop diseases.

00:05:03.360 | And yet, based on standard criteria, their doctor is telling them that they're fine,

00:05:07.480 | that they're all the same.

00:05:08.760 | So he also showed in that study that non-diabetic individuals, when you have a CGM on, are going

00:05:14.560 | into the diabetic range and the pre-diabetic range a fairly significant amount.

00:05:20.200 | And we would never know that if you weren't actually tracking a movie of the glucose.

00:05:25.640 | So glycemic variability, area under the curve, those are two things.

00:05:30.380 | Another really interesting thing you can know from a CGM is dawn effect.

00:05:33.640 | So dawn effect is basically a term in the literature for how high your glucose rises

00:05:40.680 | right when you wake up in the morning.

00:05:42.040 | I don't know if you noticed this when you were wearing a CGM, but some people notice

00:05:45.960 | that the second they wake up, their glucose jumps up 5, 10, 20, 30 points.

00:05:52.000 | What's happening here is that the cortisol awakening response to actually get you to

00:05:55.860 | wake up and get out of bed, that cortisol can cause you to dump a bunch of glucose from

00:06:01.720 | your liver.

00:06:02.720 | Because it's basically saying, stress hormone, cortisol, we got to get up.

00:06:06.120 | We need glucose to fuel the muscles.

00:06:07.720 | Let's dump a little glucose.

00:06:10.280 | So it's normal.

00:06:11.820 | But what the research shows is that magnitude of dawn effect is correlated with insulin

00:06:18.400 | resistance.

00:06:19.400 | So the more the dawn effect you're getting, I think it can signal maybe the more stress

00:06:23.400 | you're under, the more cortisol you have floating around, how big your cortisol awakening response

00:06:27.680 | is.

00:06:28.680 | But also, if you imagine if you're dumping all that glucose from your liver and your

00:06:31.240 | cells aren't taking it up well because you're insulin resistant, that response, that dawn

00:06:36.400 | effect is going to be higher.

00:06:37.640 | So I don't have the numbers right in front of me, but typically, I would want to see

00:06:43.520 | a dawn effect, I think, of less than 10 points.

00:06:46.200 | So you wake up and you may very well see a rise.

00:06:49.360 | This is absence of any food yet.

00:06:51.800 | And you do not want to see that going up 20, 30, 40 points.

00:06:55.900 | Some people see a little bump again with caffeine in the morning because it's more cortisol.

00:06:59.720 | And so that's another thing that standard stuff would never tell you.

00:07:05.200 | So those are kind of some of the looking at early predictors of metabolic dysfunction.

00:07:09.960 | More of the fun stuff is actually just figuring out how is food affecting your body.

00:07:14.520 | And this is where people really enjoy it and figure out, oh, my god, this food that I thought

00:07:18.560 | was healthy is actually not serving me.

00:07:22.760 | And actually, a lot of people, I think, who are trying to make healthy choices-- my boyfriend,

00:07:28.000 | when we started dating, he started using Levels.

00:07:30.360 | His healthy snack, he worked in Venice, would be to go to Moon Juice and get-- oh, gosh,

00:07:36.360 | I don't want to throw Moon Juice under the bus here, but he would get--

00:07:38.760 | They have some tasty stuff there.

00:07:39.760 | They do.

00:07:40.760 | But he would get this green juice that was sweetened with dates, and it was $9, and this

00:07:44.320 | was the healthy choice.

00:07:46.360 | And he saw, the second he put on Levels, that it was causing a huge spike, like 50, 60,

00:07:51.800 | 70 points, and then he was crashing.

00:07:55.680 | And he was actually trying to make a good decision.

00:07:58.720 | So now he's swapped his snacks out for more like grass-fed cheese and some flax crackers

00:08:04.840 | and maybe like a venison stick or something, like grab-and-go stuff that isn't spiking

00:08:08.840 | his glucose.

00:08:09.840 | But I think it can help people figure out which foods are doing what I want them to

00:08:14.040 | do and which maybe aren't.

00:08:17.240 | And same thing happened for so many of our members with oatmeal.

00:08:20.720 | Unfortunately, instant oatmeal is one of the biggest spikers in our data set for breakfast,

00:08:26.200 | and a lot of people are making that choice because they think it's heart healthy.

00:08:29.720 | And in many people, it's actually causing a big glucose excursion and crash.

00:08:35.120 | And then in some other people, it's not.

00:08:37.320 | And so it's really helping with, what are the sneaky spikers?

00:08:40.960 | And then where's the biochemical individuality?

00:08:44.000 | And there was a phenomenal paper out of Israel from Cell about seven years ago called Personalized

00:08:54.140 | Nutrition by Prediction of Glycemic Responses.

00:08:56.640 | It made big waves.

00:08:57.640 | But it basically showed that you and I could eat the same handful of blueberries and have

00:09:03.520 | totally different glycemic responses.

00:09:07.840 | So the idea of glycemic index as like a certain amount of food with a certain amount of glucose

00:09:12.880 | causes a certain glucose rise, it kind of debunked that.

00:09:17.320 | And that matters because repeated sustained glycemic variability over time is not good

00:09:22.760 | for our health.

00:09:23.760 | We want to choose the foods or balance the foods that are going to keep us relatively

00:09:27.400 | more stable.

00:09:29.640 | So that's very helpful, just understanding your personal response to food.

00:09:33.360 | And then what are the lifestyle strategies you can use-- sleeping better, walking after

00:09:38.080 | meals, more resistance training, cold plunging, breath work-- that can actually serve to modulate

00:09:45.920 | the food environment to actually reduce the glucose spikes?

00:09:49.720 | And people find that all of those things can positively impact glucose spikes, especially

00:09:53.360 | the walks after the meals.

00:09:54.560 | But it's been fascinating to see a lot of women, especially like menopausal women in

00:09:59.880 | our community, who find that their glucose patterns are getting worse because estrogen

00:10:04.440 | is dropping.

00:10:05.440 | So that's going to really take a hit on insulin sensitivity.

00:10:09.360 | They start resistance training.

00:10:11.600 | Glucose comes kind of right back down.

00:10:13.600 | So because of the monitor, they can feel more confident in the intervention they've chose

00:10:18.720 | to do to help with metabolism, and that kind of creates a virtuous cycle.

00:10:23.080 | Thank you for tuning in to the Huberman Lab Clips channel.

00:10:26.400 | If you enjoyed the clip that you just viewed, please check out the full-length episode by

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How to Use & Interpret a Continuous Glucose Monitor (CGM) | Dr. Casey Means & Dr. Andrew Huberman

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