Summary
Josh Clemente, founder and CEO of Levels, discusses surprising insights from continuous glucose monitoring. A former SpaceX systems engineer who led development of life support systems for Crew Dragon, Josh became obsessed with extending healthspan through better measurement of human health.
The conversation covers unexpected glucose responses to foods, how individual metabolic responses vary dramatically, and what CGM data reveals about sleep, stress, and exercise effects on blood sugar regulation.
Key Points
- Continuous glucose monitors reveal surprising individual food responses
- Metabolic responses to the same foods vary dramatically between people
- CGM data shows how sleep quality directly impacts glucose regulation
- Stress creates measurable effects on blood sugar
- Exercise timing and type affect glucose response patterns
- Frequent measurement enables personalized metabolic optimization
Key Moments
Levels' 75,000-person CGM study: the largest non-diabetic glucose dataset ever
Levels ran an IRB study with 75,000 participants over 3+ years - the largest CGM dataset linking glucose to nutrition in non-diabetics.
"We've got 75,000 participants, many of whom have been using CGM for years inside this data set. And it's the largest by far of its kind ever."
The dawn effect and how menstrual cycles dramatically shift glucose response
Everyone gets a 20-30 point morning glucose spike (dawn effect). Women's glucose shifts dramatically with estrogen/progesterone cycles.
"The degree of impact of the progesterone and estrogen cycle is wild for a lot of women and it can be really frustrating."
AI-powered glucose prediction: Levels aims to replace CGM with predictive models
Levels trains AI on billions of CGM data points to predict glucose response to meals without a sensor. Still too imprecise for individuals.
"We have by far the largest data set that corresponds in a non-diabetic population CGM data with nutrition specifically and exercise."
