The Dr. Hyman Show
The Health Conspiracy No One Talks About: Life Insurance, Big Data & Aging | Gary Brecka
Wed, 12 Mar 2025
What if I told you life insurance companies can predict, almost to the month, when you’re going to die? That’s exactly what Gary Brecka, a human biologist and former mortality expert, used to do—until he uncovered something shocking. After years of analyzing blood work and medical records, he realized that the biggest predictors of disease and early death aren’t genetic—they’re modifiable. Now, he’s using that knowledge to help people optimize their health and extend their lifespan. In this episode of The Dr. Hyman Show, we discuss: How insurance companies use hidden health data to predict life expectancy with stunning accuracy. The biggest factors that shorten lifespan—and why most of them are within our control. Why vitamin deficiencies, especially vitamin D, are quietly fueling chronic disease. How the right biohacking tools, like red light therapy and oxygen optimization, can reverse aging. What you can do today to take control of your health and longevity. This conversation will change the way you think about your own health. View Show Notes From This Episode Get Free Weekly Health Tips from Dr. Hyman Sign Up for Dr. Hyman’s Weekly Longevity Journal This episode is brought to you by BON CHARGE, Timeline Nutrition, Paleo Valley, and Big Bold Health. Order BON CHARGE’s Max Red Light Therapy device today and get 15% off. Visit boncharge.com and use code DRMARK for 15% off. Support essential mitochondrial health and save 10% on Mitopure. Visit timeline.com/drhyman to get 10% off today. Get nutrient-dense, whole foods. Head to paleovalley.com/hyman for 15% off your first purchase. Try Big Bold Health’s HTB Rejuvenate and get 25% off by going to bigboldhealth.com and use code DRMARK25 at checkout.
Chapter 1: What can life insurance companies predict about our lifespan?
The more pharmaceuticals you were on, the easier it was for us to predict your life expectancy.
The more you were on, the more likely you were to die sooner.
The more you're on, the more likely you were to die sooner and the more predictable.
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Chapter 2: How do pharmaceuticals influence life expectancy?
That's right. We saw your hydrogen machines, your ozone sauna, your whole biohacking suite, the red light therapy. It was quite interesting. But maybe people know or don't know about you.
But the thing that I find interesting is you came at this through the lens of sort of understanding why people die, not through the lens of longevity, which is sort of like you were trying to like help companies save money by understanding what was causing death and mortality and trying to help them navigate that. So can you tell us about your background, how you got like...
the insights about the nature of our chronic Z epidemic, what's going on, why these insurance companies have all this data, what they've learned, and why it matters to us.
So for the better part of my career, I was a mortality expert, which essentially means that, you know, we studied mortality, the variable basic tables, not just putting people on an actuarial curve, right? I mean, we're all on one, right? If you're a 54-year-old
Male, you have a life expectancy of X. If you're a 34-year-old female, you have a life expectancy of Y. You're lumped into a massive pool of mortality.
But when a life insurance company is getting ready to put $25 million or $50 million worth of risk on your life, or an annuity company is getting ready to issue you a SPIA, what's called a single premium immediate annuity, where you give them a lump sum of cash and they guarantee you an income stream for life,
Or you're getting ready to do what's called a reverse mortgage, which means you get to live in your house, but you sell it while you're still alive. All of these are based on mortality. The only thing that matters in those financial services instruments is how many more months does this person have left?
Yeah.
So they don't really care where you are on an actuarial curve, right?
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Chapter 4: How does red light therapy contribute to recovery?
They want to know- They don't adjust the prices to match when you're going to die so they don't lose money.
And insurance is priced like that. You have super preferred, preferred, standard. Then you have what's called table ratings.
So what did you learn as you sort of started looking at the data and the lab data for people who were in the pool? Yeah. Because these companies actually get your blood. Oh, yeah. Oh, they get your blood.
They can take genes. They get all of your medical records. They have all your demographic data. I mean, it's a proctology exam. I mean, if you've ever applied for- Maybe a full colonoscope.
Yeah.
I don't think you get as much information from a colonoscope as you do a full-blown life insurance application. Now, I'm not talking about term life insurance. I'm talking about whole life, permanent universal life insurance where people are putting $10 million, $25 million, $50 million of risk on a single life.
What happens in those cases is they take not only a deep dive into your demographic data, but I mean, they get everything, your divorce decrees, your trust accounts, your bank statements, your brokerage statements, your... your work history and all of your medical records.
And then before they actually issue the policy, they will essentially send a nurse to your house and they will pull whatever biomarker they want. So you got to like have an inside view of what that is. Real inside view. First of all, I'm not a physician. I'm a human biologist. My undergraduate degrees are in biology. My postgraduate degrees are in human biology.
And so I spent eight years in formal education just studying human physiology. And they wanted someone like that on the team with the rest of the MDs and actuarial scientists because we were trying to really build a model that was very accurate, probabilistic model that was accurate. What really emerged from this big data
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