#165 - AMA #24: Deep dive into blood glucose: why it matters, important metrics to track, and superior insights from a CGM

Jun 14, 2021 Episode Page ↗
Overview

Peter Attia, joined by Bob Kaplan, discusses why continuous glucose monitoring (CGM) is crucial for metabolic health and longevity, even for non-diabetics. They highlight the importance of tracking average blood glucose, variability, and peak glucose levels, which traditional tests often miss.

At a Glance
5 Insights
17m 22s Duration
6 Topics
4 Concepts

Deep Dive Analysis

Introduction to Glucose Homeostasis and CGM

Critique of Traditional Metabolic Health Metrics (HbA1c)

Advantages and Technology of Continuous Glucose Monitors (CGM)

Personal Experience: CGM vs. HbA1c Discrepancies

Peter's Hypothesis: Optimal Glucose Metrics for Non-Diabetics

The Three Key Glucose Metrics Tracked

Hemoglobin A1C (HbA1c)

HbA1c measures the concentration of glycosylated hemoglobin, inferring average glucose levels over a red blood cell's life, typically around 90 days. Its accuracy can be affected by factors like red blood cell turnover rate, potentially leading to artificially low or high readings.

Continuous Glucose Monitor (CGM)

A CGM is a device that continuously measures glucose levels in the interstitial fluid, providing a real-time, ongoing 'movie' of glucose excursions. This technology offers superior insight into glucose homeostasis compared to single-point measurements like fasting glucose or HbA1c.

Glucose Variability

Glucose variability refers to the fluctuations in blood glucose levels over time. It is best measured using a CGM, with the standard deviation serving as the mathematical tool, and minimizing this variability is considered a key indicator of better metabolic health.

Glucose Peaks

Glucose peaks are the highest points blood glucose reaches, often after meals. Minimizing these peaks is considered problematic and important for overall health, independent of average glucose levels or variability.

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Why does Peter find advanced glucose tests useful in 'healthy' people?

Peter believes that traditional definitions of 'normal' glucose are oversimplified and that metabolic health exists on a continuum, making advanced tests like OGTT with insulin measurements and CGM essential for understanding true glucose homeostasis even in non-diabetics.

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What is Peter looking for when assessing someone's glucose levels?

Peter focuses on three key metrics: lower average blood glucose, minimal glucose variability (standard deviation), and minimized glucose peaks, believing these are crucial for health and longevity beyond the formal diagnosis of type 2 diabetes.

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How does Peter define normal versus abnormal control of glucose?

Peter views glucose control as a continuum rather than a binary normal/abnormal state, arguing that even within the 'normal' range, lower average glucose, less variability, and fewer peaks are always better.

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If I'm not diabetic, do I have anything to worry about regarding glucose?

Yes, Peter argues that even non-diabetics should be concerned with optimizing their glucose metrics (average, variability, peaks) because better control is associated with improved health and longevity, irrespective of a formal diabetes diagnosis.

1. Optimize Glucose Levels

Aim for lower average blood glucose, minimize glucose variability (standard deviation), and minimize glucose peaks, as these are critical metrics for health and longevity even in non-diabetic individuals.

2. Utilize Continuous Glucose Monitor

Wear a Continuous Glucose Monitor (CGM) to get a continuous, real-time understanding of your glucose levels, variability, and peaks, as it provides more accurate and comprehensive data than traditional tests like HbA1c or fasting glucose.

3. Interpret HbA1c Cautiously

Be aware that HbA1c measurements can be misleading due to factors like red blood cell lifespan (e.g., short life due to blood loss, long life due to microcytic patterns), leading to artificially low or high readings, and view glucose levels as a continuum rather than binary categories.

4. Proactive Doctor’s Visit Prep

Consider wearing a CGM for 30 days prior to a doctor’s visit to provide comprehensive real-world glucose excursion data, which is more informative for your doctor than single HbA1c or fasting glucose measurements.

5. Monitor Blood Pressure at Home

Monitor your blood pressure at home using a preferred monitor and a structured logging method to gain a more comprehensive understanding of your blood pressure trends than what in-office readings alone can provide.

I think oversimplification is erroneous. And I think we should view these as a continuum.

Peter Attia

It's the difference between like a snapshot and a movie.

Bob Kaplan

I don't know why everyone in the world isn't wearing it, notwithstanding the cost and the logistics of it.

Peter Attia

Optimal Glucose Metric Tracking for Health and Longevity

Peter Attia
  1. Achieve the lowest possible average blood glucose.
  2. Minimize glucose variability (standard deviation).
  3. Minimize glucose peaks.
Greater than 6.5%
HbA1c threshold for Type 2 Diabetes Corresponds to an average blood glucose of approximately 130 milligrams per deciliter.
About 90 days
Typical red blood cell lifespan Relevant for HbA1c measurement period.
5.7% to 6.4%
HbA1c range for pre-diabetes Defined as a risk category for metabolic issues.
About 90 milligrams per deciliter
Peter Attia's average CGM glucose (last 24 hours) Personal data from his continuous glucose monitor.
About 9 or 10 milligrams per deciliter
Peter Attia's CGM glucose variability (last 24 hours) Standard deviation from his continuous glucose monitor.
102 milligrams per deciliter
Peter Attia's peak CGM glucose (last 24 hours) Highest level recorded on his continuous glucose monitor.
77 milligrams per deciliter
Peter Attia's nadir CGM glucose (last 24 hours) Lowest level recorded on his continuous glucose monitor.
5.1% to 5.8%
Peter Attia's measured HbA1c range His HbA1c always runs high due to beta thalassemia minor.
0.5 to 0.8 percentage points higher
Peter Attia's HbA1c overstatement compared to CGM His HbA1c readings are higher than what his CGM data predicts.
100 milligrams per deciliter
Excellent average glucose (example) Corresponds to an HbA1c of about 5% to 5.1%.