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Speaker 1: Before we get started, a brief correction from last week's

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Speaker 1: methylene blue episode. My wife, the brilliant breast surgeon, informed

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Speaker 1: me that I neglected to mention a very important use

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Speaker 1: of methylene blue, which is that it is used for

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Speaker 1: sentinel lymph node biopsy in all types of surgeries where

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Speaker 1: surgeons need to figure out where cancer may be spreading

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Speaker 1: and along what path. So one more good use of

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Speaker 1: methylene blue amidst the many bad uses that we talked

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Speaker 1: about last week. Let's get on with today's episode.

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Speaker 2: Okay, So, Perry, I'm going to tell you a story

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Speaker 2: about a colleague of mine at my old job who

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Speaker 2: ate only.

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Speaker 1: Meat, only meat pretty much.

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Speaker 2: Okay, So here's what happened. He was on a carnivore

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Speaker 2: paleo meat granted diet and his main snack food was

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Speaker 2: I want you to imagine, you know, those like ice

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Speaker 2: pop things that your kids have that are like long

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Speaker 2: plastic things at blue ice in the middle and it's.

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Speaker 3: Like a pushpop.

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Speaker 1: Yeah.

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Speaker 2: Yeah, it was like that, but instead of the blue ice,

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Speaker 2: it was a meat slurry. So it's sort of like

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Speaker 2: a like a like a beef tartar, but more of

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Speaker 2: a of a slurry he would just sort of like

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Speaker 2: push it up and eat it, okay, So that already

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Speaker 2: was like m he had the office next to mine.

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Speaker 2: Then it's the summer and he goes out of town

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Speaker 2: and he gets right before it's like quite hot, and

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Speaker 2: he gets a box of this stuff delivered right before

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Speaker 2: he leaves, and they put it in his office. The

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Speaker 2: course of the next few weeks, the smell just gets

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Speaker 2: worse and worse and worse, and finally it's like our

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Speaker 2: offices are around this open space where like the graduate

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Speaker 2: students work, and she's getting worse and worse and worse,

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Speaker 2: and finally we call in security and they go in

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Speaker 2: and there's just this box of like rotting meat slurry.

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Speaker 2: Did you think that someone had died, Well, we thought

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Speaker 2: it was animal like we didn't think it was in

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Speaker 2: dead person, but we thought there was an animal that

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Speaker 2: had died.

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Speaker 3: And then we opened it and the security guys are like,

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Speaker 3: there's a box of meat.

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Speaker 4: And.

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Speaker 3: I was mad. I was really mad.

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Speaker 1: I mean I would be livid. We're going to talk

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Speaker 1: about the benefits and risks of a red meat diet today,

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Speaker 1: but boy, this is what I didn't think of.

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Speaker 5: Keep your meat refrigerated people, geez, give your meat slurries.

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Speaker 2: Guys, your meat push up slurry pops. They need to

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Speaker 2: be refrigerated. If you learn nothing else from this episode,

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Speaker 2: it should be that I'm Emily Oster, I'm an economist

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Speaker 2: and a data expert.

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Speaker 1: And I'm Harry Wilson, I'm a medical doctor.

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Speaker 2: It's Thursday May twenty eight, twenty twenty six, and this

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Speaker 2: is wellness.

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Speaker 1: Actually, because you're getting a staggering amount of health and

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Speaker 1: wellness information nowadays from every source imaginable, and some of

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Speaker 1: it is awesome and some.

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Speaker 3: Of it is well actually both.

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Speaker 2: Fortunately we are both people who know how to read studies,

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Speaker 2: how to parse the data, and can tell you what's

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Speaker 2: worth thinking about and what you can safely ignore.

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Speaker 1: But before we dig in, a note that this podcast

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Speaker 1: is for educational purposes and should not be construed as

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Speaker 1: medical advice. We don't know your unique situation, so talk

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Speaker 1: to your doctor for personal health decisions.

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Speaker 2: This week, we're asking what's the deal with red meat?

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Speaker 2: Harry and I will give the official smasher pass, and

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Speaker 2: then we'll get to your question of the week. But

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Speaker 2: first let's do the health news roundup.

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Speaker 3: After the break.

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Speaker 1: And we're back with your Health News of the Week, Emily.

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Speaker 1: Running influencers are having a moment with peptides. What's going

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Speaker 1: on here? This is your world?

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Speaker 2: Okay, So there's a fight going on between two running

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Speaker 2: influencers about use of peptides. So there is one running

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Speaker 2: influencer who ran the Eugene Marathon and he's not even

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Speaker 2: really a running influencer. He's like a wellness guy influencer,

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Speaker 2: and he ran the Eugene Marathon actually quite fast, in

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Speaker 2: like two thirty nine. He's fifty, so it's actually a

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Speaker 2: very fast time, and he won his like old person

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Speaker 2: age group or whatever.

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Speaker 3: But he's not a professional athlete.

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Speaker 2: But then ex post he really he revealed that he's

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Speaker 2: been using BPC one fifty seven, which you may recall

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Speaker 2: as being part of the Wolverine.

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Speaker 3: Stack that is recommended by Joe Rogan.

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Speaker 1: And then the peptide episode please.

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Speaker 3: Listen to our theptid episode.

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Speaker 2: And then another running influencer is an ultra runner influencer,

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Speaker 2: is very upset about this because BPC one fifty seven

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Speaker 2: is not sanctioned by WATA, which is the antidoping agency.

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Speaker 3: But this guy's view is.

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Speaker 2: Like he's not a professional athlete, he's not in a

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Speaker 2: doping pool, and the other other guys view is you're cheating,

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Speaker 2: and my view is there's no evidence that this peptide

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Speaker 2: improves your performance. But I love the overlap of like

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Speaker 2: endurance sports and peptides and influencers.

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Speaker 3: It's just it's a dream.

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Speaker 1: Yeah. I mean, as more of this stuff gets out there,

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Speaker 1: with less and less data, these issues just you can

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Speaker 1: you can impose whatever you want on the effects of

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Speaker 1: these things because there's no one who can prove you

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Speaker 1: wrong since there's no strong data. So you can say like, oh,

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Speaker 1: this is the same as taking steroids, or you can

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Speaker 1: be like it's a fancy placebo and it made me

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Speaker 1: believe in myself. And you've got equal evidentiary support for

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Speaker 1: both of those statements totally.

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Speaker 2: So anyway, that was my that was my thing. I

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Speaker 2: am going to refrain from making us do an entire

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Speaker 2: episode on a thing called the enhanced Games, but we

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Speaker 2: can discuss that at another time.

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Speaker 1: Oh I saw that fascinating.

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Speaker 3: Yes, absolutely, all right.

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Speaker 2: In less fun news, please tell us what's going on

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Speaker 2: with Ebola.

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Speaker 1: Yeah. I'd like to not have this be a news

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Speaker 1: item every week, but it is important. The Abola outbreak

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Speaker 1: continues in the Democratic Republic of Congo right now as

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Speaker 1: of the recording, today's Tuesday, the twenty six, when we're recording,

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Speaker 1: you'll hear this a couple days later. They're about a

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Speaker 1: thousand suspected and confirmed cases and two hundred and twenty

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Speaker 1: three suspected deaths. The outbreak has spread into Uganda now

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Speaker 1: with seven confirmed cases and one confirmed death. One American

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Speaker 1: has been infected. They were administering care to people in

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Speaker 1: the Democratic Republic of Congo, tested positive and has been

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Speaker 1: evacuated to Germany to a hospital there. Obviously, we wish

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Speaker 1: them the best. I think. One of the concerning things

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Speaker 1: that has emergency weeks, there have been several attacks against

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Speaker 1: health centers in the Democratic Republic of Congo that are

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Speaker 1: you know, ministering to this population. You know. One of

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Speaker 1: the issues is apparently that the cultural funereal practices are

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Speaker 1: very important in this part of the world, and healthcare

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Speaker 1: workers have been limiting access to dead bodies to their

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Speaker 1: families and loved ones, in part because inebola deceased bodies

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Speaker 1: are highly highly infectious. This is transmitted by bodily fluids

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Speaker 1: and in fact, in prior outbreaks, sixty to eighty percent

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Speaker 1: of the infections were attributed to funereal practices because there,

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Speaker 1: you know, families will like bathe the bodies, even sleep

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Speaker 1: near the bodies for several days at a time. There's

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Speaker 1: really interesting public health work being done there to like

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Speaker 1: work within the communities, work with religious leaders to try

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Speaker 1: to you know, educate the populace on safe funereal practices here.

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Speaker 1: But obviously there's a lot of anger and mistrust in

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Speaker 1: the populace as well, which is why you see these attacks,

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Speaker 1: which you know, it goes without saying, are a terrible

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Speaker 1: thing to you know, you're not going to reduce the

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Speaker 1: spread of this if you attack the clinics that are

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Speaker 1: isolating and treating people as best they can.

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Speaker 2: This is very I hope we will not keep talking

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Speaker 2: about this, but it is scary but also very very

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Speaker 2: sad it is.

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Speaker 1: Let's move on to let's add more crazy. I think

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Speaker 1: I read the wildest quote I've seen in a long

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Speaker 1: time from a legitimate researcher. So this comes from doctor

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Speaker 1: Glenn Jeffrey. He's at University of College London. He's a

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Speaker 1: mitochondrial researcher. So there we go, all of you playing

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Speaker 1: the drinking game at home. We've now mentioned mitochondria. You

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Speaker 1: have to take a shot. He's a mitochondrial researcher and,

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Speaker 1: appearing on Huberman's podcast, referred to LED lighting as an

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Speaker 1: asbestos level crisis. Bonker's statement to make Emily, why does

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Speaker 1: he think that LED lights are as bad as asbestos?

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Speaker 2: Asbestos a substance which, just to be clear, is well

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Speaker 2: known to have caused many, many cases of cancer in

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Speaker 2: people over time.

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Speaker 1: Yes, very difficult to treat cancer, MUSICIELI almost.

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Speaker 2: Difficult to treat cancer, all right. So this researcher was

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Speaker 2: working on LED lights and he ran an experiment in

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Speaker 2: which he exposed some people to LED lights with sunlight

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Speaker 2: and some people with INCANDESCI lights like different kinds of lighting,

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Speaker 2: some of which was more LED focused than others. And

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Speaker 2: he showed some changes in the retina after two weeks

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Speaker 2: of this exposure and concluded that this might be related

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Speaker 2: to the mitochondria, and as a result, it's as bad

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Speaker 2: as asbestos. I will be Frank. I can read the paper.

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Speaker 2: The paper says we did this thing with the light

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Speaker 2: and there was some small changes in retinal function, and

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Speaker 2: that's an interesting thing to explore. But I'm failing to

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Speaker 2: see the link the jump between small changes to the

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Speaker 2: retina and then cancer.

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Speaker 3: Did you did you see it?

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Speaker 6: No?

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Speaker 1: I the link as far as I can see. And

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Speaker 1: this is like a theme that I keep seeing now

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Speaker 1: that I'm exposed to, like the wellness and influencer space

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Speaker 1: is like apparently you can just say like that that

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Speaker 1: that's where we are right now, And it's much more

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Speaker 1: interesting to say this is an asbestos level health crisis

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Speaker 1: than as expected when exposing people to different kinds of

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Speaker 1: bright lights, there are subtle changes in the eye right

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Speaker 1: like this.

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Speaker 3: I did not click on that.

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Speaker 1: I didn't So, you know, anyway, for listeners, just like

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Speaker 1: claims like this, you know, trustworthy science communication unfortunately is

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Speaker 1: not that exciting because most evidence is somewhere in the

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Speaker 1: middle and and requires nuance.

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Speaker 3: And and most effects are small. I mean I think

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Speaker 3: that's the thing.

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Speaker 2: Like most things, if they have a positive effect or

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Speaker 2: a negative fact, most of these effects are very small.

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Speaker 3: Yeah.

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Speaker 1: And also, I you know, one of the things that

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Speaker 1: he said was like, oh, you know, you should consider

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Speaker 1: moving back to incandescent lights, And it's like we've made

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Speaker 1: so much like this is one area where technology I

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Speaker 1: think just completely fixed a problem like led lights are

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Speaker 1: so much better than incandescent totally.

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Speaker 2: They are better for the environment, cheaper, last, longer, last way.

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Speaker 1: Is there that a superior product in every possible way?

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Speaker 1: Don't move us back to the dark ages, no pun intended.

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Speaker 2: That is the health news of the week. After the break,

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Speaker 2: what is the deal with red meat? Okay, Perry, let's

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Speaker 2: talk about red meat.

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Speaker 1: I'm here for it. I am like a hack of

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Speaker 1: a politician. I want to throw out some red meat

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Speaker 1: to my listeners.

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Speaker 2: So I want to start with a short disclaimer, which

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Speaker 2: is that we are going to talk here about red

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Speaker 2: meat and its impacts on health and varying sources of

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Speaker 2: protein and how nutrition relates to human health.

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Speaker 3: We are not going to talk about climate. I know

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Speaker 3: that a.

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Speaker 2: Lot of people avoid red meat because of the impact

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Speaker 2: of cows on climate, and we are not going to

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Speaker 2: be talking about that today, not because it's not important,

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Speaker 2: but because that's not the topic of today's podcast.

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Speaker 1: Excellent disclaimer. There you go.

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Speaker 3: Yep.

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Speaker 2: Okay, let's start with some basic science. What makes red

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Speaker 2: meat red? Trivia question for the doctor?

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Speaker 1: My aglobin In a word, my globin is a protein

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Speaker 1: that lives in muscle, cells and has a heme group

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Speaker 1: in the middle, which is an iron containing group in

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Speaker 1: the middle, and it provides oxygen to muscle cells which

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Speaker 1: need that oxygen so that they can run their mitochondria

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Speaker 1: and contract and things like that. Differing amounts of myoglobin

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Speaker 1: colors muscles differing shades of red, and so you know,

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Speaker 1: when we think about red meat like cows and pork

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Speaker 1: and stuff like that, that's basically what you're seeing. It's

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Speaker 1: the same heme group that comes in hemoglobin, which delivers

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Speaker 1: oxygen to the rest of the body, but myoglobin is

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Speaker 1: quite concentrated in muscle cells. It does lead to the question,

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Speaker 1: of course, like why don't birds and chickens have myoglobin

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Speaker 1: in their muscle fibers. And it turns out that birds

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Speaker 1: don't use aerobic respiration to fuel their muscle movements. They

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Speaker 1: use anaerobic respirations, so they aren't using their mitochondria, they

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Speaker 1: don't need an oxygen carrier in their muscle fibers, and

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Speaker 1: hence they have white muscle, and fundamentally that's what explains

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Speaker 1: the color. But of course what's interesting to us is

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Speaker 1: less like a why is it red? And more what

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Speaker 1: are the nutritional differences? Writen large between you know, a

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Speaker 1: given amount of red meat and a given amount of

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Speaker 1: non red or white meat. So we should probably dig

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Speaker 1: in there.

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Speaker 2: Yeah, I think we should start there because in general,

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Speaker 2: when people are eating meat, this is an important source

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Speaker 2: of protein.

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Speaker 3: And that is what people are mostly getting.

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Speaker 2: That is the most important macronutrient people are getting out

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Speaker 2: of meat.

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Speaker 3: And there are.

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Speaker 2: Sources of protein that come from animals and sources of

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Speaker 2: protein that come from plants, and I think gets useful

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Speaker 2: to do a little bit of a comparison for people about,

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Speaker 2: you know, what are some common sources of protein and

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Speaker 2: what do they deliver, So we can maybe think about beef, chicken, fish,

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Speaker 2: and tofu as being kind of representative of the kinds

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Speaker 2: of meat.

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Speaker 1: I would say the four proteins of the Apocalypse.

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Speaker 2: Lean, ground, beef, skinless chicken, breast, salmon, and tofu.

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Speaker 3: Distinguishing features among these are.

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Speaker 2: Beef has more calories than the other items because it

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Speaker 2: has more fat. Like that's like the for me, that's

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Speaker 2: like the most crucial element of this is that that

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Speaker 2: for a guin amount of protein, beef is going to

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Speaker 2: have more calories because it has more fat, and particularly

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Speaker 2: more saturated fat.

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Speaker 3: Tofu is going to have sort of slightly.

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Speaker 2: Less much less fat, much less saturated fat. The lowest

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Speaker 2: thing in saturated fat or Jeff fat in general is

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Speaker 2: like skinless chicken breast. That's why that's everyone's favorite nineteen

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Speaker 2: eighties diet food. But when I think about how we

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Speaker 2: organize the questions about health here, it is really about

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Speaker 2: around the fact that this is a higher calorie food

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Speaker 2: because it has more fat.

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Speaker 3: Is there more that you would say about the nutrients?

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Speaker 1: I'd say a couple little other things, But yes, I

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Speaker 1: think when it comes to health, we're talking not just

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Speaker 1: about fat, but about saturated fat. And I think everyone's

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Speaker 1: heard the term saturated fat, so we should, but we

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Speaker 1: should actually define it like what it is and why

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Speaker 1: we care. And that is kind of the distinguishing feature

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Speaker 1: of beef. As you say, there are a couple little

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Speaker 1: other things that, like micronutrients, that are worth describing. People

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Speaker 1: won't be surprised to hear that beef has more iron

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Speaker 1: in it than chicken and salmon, although actually tofu has

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Speaker 1: quite a bit of iron as well. The other major

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Speaker 1: thing that comes up all the time we talk about

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Speaker 1: carnivore based diets are heavily meat protein based diets. Is

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Speaker 1: that meat has no fiber, not red meat, not chicken,

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Speaker 1: not salmon. There's no dietary fiber in these and in

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Speaker 1: so far as dietary fiber is important for promoting colon

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Speaker 1: health and reducing the risk of colon cancer, that is

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Speaker 1: the absence of fiber. It's something that we need to

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Speaker 1: think about. So, but maybe let's just start with saturated fat. Emily,

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Speaker 1: do you like? What do you think me?

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Speaker 3: Pushback on?

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Speaker 2: Like, I think fiber is very important, but none of

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Speaker 2: these things have fiber in them. So like if you

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Speaker 2: said chicken doesn't have fiber.

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Speaker 1: Either, chicken doesn't have fiber either, right, I mean like,

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Speaker 1: but but plant based proteins do, right.

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Speaker 3: So plantbease proteins have fiber.

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Speaker 2: But is this is that people's most important source of

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Speaker 2: fiber mostly?

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Speaker 1: Well, it could be like if you're if you're sitting

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Speaker 1: here and asking the question of my concern is getting

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Speaker 1: adequate amounts of protein and how should I do it?

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Speaker 1: By the way, call back to the what's the deal

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Speaker 1: with protein? Episode? Like plant based proteins would offer you

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Speaker 1: fiber in addition to similar amounts of protein and less

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Speaker 1: saturated fat than red meat. Okay, if you think that matters,

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Speaker 1: I think, okay.

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Speaker 2: Fine, I'm gonna I think we're already getting a sense

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Speaker 2: that Perry and I are not going to agree about

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Speaker 2: everything here. I don't think this is that your protein

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Speaker 2: sources are an important source of your fiber.

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Speaker 3: But let's move on.

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Speaker 1: Okay, let's talk about saturated fat.

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Speaker 3: Let's talk about saturated fat.

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Speaker 1: Yeah, what makes saturated fat saturated? So should we do

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Speaker 1: a very quick chemistry?

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Speaker 3: Your fat carbon chains big.

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Speaker 1: Long carbon chains. So fat is just a big long

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Speaker 1: chain of carbons, you know, whereas sugars, like the kind

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Speaker 1: of sucrose that we eat, are two carbons stuck together,

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Speaker 1: so it's simple. And then like glucose is just one

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Speaker 1: carbon with some stuff attached to it, but you know,

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Speaker 1: you're getting their energy from there. And fats like carbon

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Speaker 1: carbon carbon carbon carbon, You can have different lengths of

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Speaker 1: these carbon chains, and then you break those things down

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Speaker 1: and you digest them, and that's how you get energy.

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Speaker 1: The end of that long chain of carbon has a

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Speaker 1: little acid on it, which is why people used to

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Speaker 1: talk about fatty acids. We now just say fats. That's

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Speaker 1: basically what we're talking about. It's all fatty acid now

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Speaker 1: saturated fats. The reason they're saturated is that their carbons

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Speaker 1: are connected are fully bound to hydrogen, so they only

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Speaker 1: have single bonds to each other. And the practical upshot

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Speaker 1: of that is that those long, squiggly chains can pack

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Speaker 1: very tightly together. And the way you notice that is

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Speaker 1: that when something has more saturated fat, it will be

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Speaker 1: solid at room temperature because the fat can all kind

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Speaker 1: of pack together. So if you're wondering like butter or beef,

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Speaker 1: tallol or like coconut oil, right, like, so there are more,

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Speaker 1: there are relatively more and less saturated fats. And a

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Speaker 1: hint as to what that is is you know whether

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Speaker 1: it's a liquid or not at room temperature. But like,

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Speaker 1: that's a fun trivia fact, I guess. But the reason

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Speaker 1: people care is because I'm curious if you'll agree with

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Speaker 1: me on this, Emily. There is a clear and causal

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Speaker 1: relationship between saturated fat intake and serum cholesterol levels.

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Speaker 3: Yeah, I think that's true.

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Speaker 5: Okay, all right, just want to make sure you weren't

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Speaker 5: like gonna come out with like, well, actually, okay, great,

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Speaker 5: So saturated fat raises cholesterol and higher.

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Speaker 1: Cholesterol levels are causally linked to cardiovascular disease and stroke.

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Speaker 2: Right, what I think is interesting and is a great

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Speaker 2: opportunity to get into some complaints.

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Speaker 3: I have, Okay, are how we draw links between those things.

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Speaker 2: So consumption are more saturated fat leading to higher cholesterol

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Speaker 2: on our ridge, people with higher cholesterol more likely to

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Speaker 2: have cardiovascular disease. I think the question is, then if

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Speaker 2: you change someone's diet from a low saturated fat to

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Speaker 2: a higher saturated fat or vice versa, would that alter

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Speaker 2: their cardiovascular risk? And that is the question that I

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Speaker 2: think we want to talk about because in the course

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Speaker 2: of this discussion on red meat, I think the core

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Speaker 2: question is whether a diet that has its meat source

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Speaker 2: be higher and saturated fat is going to put you

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Speaker 2: at higher risks for cardiovascular disease than a calorically equivalent

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Speaker 2: diet with less saturated fat. Right, Okay, I want to

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Speaker 2: take an opportunity to give some complaints about nutrition science.

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Speaker 1: At this idea. This is a perfect time.

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Speaker 3: Great.

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Speaker 2: A lot of what we know about nutrition is based

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Speaker 2: on studies which are very large, but in my personal view, terrible.

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Speaker 2: Many of these studies, many of the studies you hear

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Speaker 2: about the difference in health outcomes for people who drink

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Speaker 2: more coffee, or drink more milk, or dark chocolate, chocolate

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Speaker 2: or GC's or blueberries or whatever. Is the most of

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Speaker 2: that is based on getting data on people's diets and

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Speaker 2: comparing the health outcomes for people who have one kind

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Speaker 2: of diet versus another kind of diet. The problem is

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Speaker 2: that those two groups are typically very very different in

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Speaker 2: many other ways that are not about their diet, and

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Speaker 2: it is extremely challenging for researchers to fully adjust for

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Speaker 2: those factors. And I think people would be surprised at

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Speaker 2: how much you can mess around with things to make

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Speaker 2: stuff show up in whatever way you want. So, for example,

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Speaker 2: I once took the Marquee study data source on diet,

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Speaker 2: the en Hanes, which is where we survey many Americans thousands.

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Speaker 1: Of nationally representative survey sample.

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Speaker 2: National representative survey, and I showed that you can do

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Speaker 2: something that looks very close. It actually is kind of

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Speaker 2: the standard approach to analyzing diet, and you can show

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Speaker 2: that consuming iceberg lettuce raises your BMI, but consuming dandelion

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Speaker 2: greens lowers your BMI.

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Speaker 1: Yeah.

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Speaker 2: Now, both iceberg lettuce and dandelion greens contain no calories.

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Speaker 3: They are calorically free.

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Speaker 2: But the difference is that people who are poor tend

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Speaker 2: to eat iceberg lettuce, and people who are rich tend

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Speaker 2: dandelion greens.

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Speaker 3: And in fact, even though you see in these.

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Speaker 2: Data sets things like education and income, you don't see

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Speaker 2: enough about them.

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Speaker 1: You can never adjust enough, you.

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Speaker 2: Can never adjust enough, and so in like, my view

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Speaker 2: is that basically all studies that rely on this kind

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Speaker 2: of observational data to analyze nutrition are just trash.

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Speaker 3: Honestly, that's my view that they're all trash. Okay, I'm

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Speaker 3: going it's a hot take.

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Speaker 1: It's a hot take, and I'm not I'm not even

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Speaker 1: that offended by your hot take. And I'm going to

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Speaker 1: add one other problem to this body of literature, which

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Speaker 1: is the food frequency questionnaire, where the enhanes data and

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Speaker 1: a lot of other data comes from. A food frequency

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Speaker 1: questionnaire is something that says, over the past week, how

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Speaker 1: many times did you eat bananas over the past month,

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Speaker 1: how many times over the past year, how many times, okay,

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Speaker 1: over the past week, how many times did you eat

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Speaker 1: walnuts over the past month, over the past and so

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Speaker 1: on and so forth. And there's about one hundred and

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Speaker 1: ten different food items on the standard Food Frequency keshnaire,

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Speaker 1: there of course variants. Okay, what I can do with

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Speaker 1: that data if I have that on all the enhanes people,

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Speaker 1: and I have outcomes on these endhanes people I know

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Speaker 1: who had you know, heart attacks or whatever, at least

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Speaker 1: maybe cross sectionally, I know what their BMI is, for example,

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Speaker 1: But in other data sets, I might have longitudinal outcomes.

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Speaker 1: I can take all of those one hundred and ten

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Speaker 1: things on the food frequency questionnaire and test whether they

444
00:23:56,119 --> 00:24:00,120
Speaker 1: you know, statistically associate with hard tech stroke divorce rates,

445
00:24:00,200 --> 00:24:02,040
Speaker 1: whatever it is. And because there's one hundred and ten

446
00:24:02,040 --> 00:24:04,880
Speaker 1: of them, several of them just by chance alone will

447
00:24:04,920 --> 00:24:06,200
Speaker 1: be statistically significant.

448
00:24:06,400 --> 00:24:06,600
Speaker 3: Five.

449
00:24:06,920 --> 00:24:10,159
Speaker 1: Wait, there's more at the level. That's what Okay, go ahead,

450
00:24:10,359 --> 00:24:12,919
Speaker 1: weight there's more. People have taken those one hundred ten

451
00:24:12,920 --> 00:24:15,600
Speaker 1: items on the food frequency questionnaire and grouped them in

452
00:24:15,680 --> 00:24:19,480
Speaker 1: weird ways. Sure, by macronutrients, right, like, okay, based on

453
00:24:19,520 --> 00:24:21,640
Speaker 1: your answers, how much carbs do we think you get?

454
00:24:21,680 --> 00:24:25,640
Speaker 1: But they've done it for like pesticide exposure. Right, they'll say, okay,

455
00:24:25,960 --> 00:24:28,760
Speaker 1: based on your food frequency questionnaires, how much pesticide are

456
00:24:28,760 --> 00:24:30,840
Speaker 1: you probably taking in? Because we know that like whatever,

457
00:24:30,920 --> 00:24:35,040
Speaker 1: cucumbers have more pesticides than cherries or something like that.

458
00:24:35,200 --> 00:24:37,560
Speaker 1: And now you have a new exposure called like pesticide exposure,

459
00:24:37,600 --> 00:24:39,720
Speaker 1: which is based on no measurement whatsoever except how you

460
00:24:39,760 --> 00:24:41,960
Speaker 1: answer to survey, and you can link that to a

461
00:24:41,960 --> 00:24:45,520
Speaker 1: bunch of different outcomes. And so there's a huge opportunity

462
00:24:45,640 --> 00:24:48,959
Speaker 1: for kind of trolling through data and finding interesting things.

463
00:24:49,119 --> 00:24:52,160
Speaker 1: They often get published because people love to talk about

464
00:24:52,160 --> 00:24:55,359
Speaker 1: this stuff, right, like it's it's relevant to everyone. We

465
00:24:55,480 --> 00:24:57,960
Speaker 1: all have to eat. The one thing I do want

466
00:24:57,960 --> 00:25:01,840
Speaker 1: to say is that while I agree that randomized trials

467
00:25:02,119 --> 00:25:07,159
Speaker 1: are the gold standard of evidence, here, it is completely

468
00:25:07,200 --> 00:25:11,919
Speaker 1: infeasible to randomize someone's diet for a long enough period

469
00:25:11,920 --> 00:25:15,400
Speaker 1: of time to witness the effects of that diet on

470
00:25:15,800 --> 00:25:20,840
Speaker 1: hard clinical outcomes. And so we'll talk about.

471
00:25:20,600 --> 00:25:22,280
Speaker 3: Something rather trash than nothing.

472
00:25:23,160 --> 00:25:26,399
Speaker 1: I'd rather have trash than nothing. Yes, I think that

473
00:25:27,520 --> 00:25:33,919
Speaker 1: I can, you know, take sort of triangulate from the

474
00:25:33,920 --> 00:25:36,720
Speaker 1: these I'm not going to call them trash. I'm going

475
00:25:36,760 --> 00:25:40,280
Speaker 1: to call them, you know, less than ideal study designs

476
00:25:41,000 --> 00:25:44,399
Speaker 1: to make inference. And because if we don't, then we're

477
00:25:44,440 --> 00:25:46,320
Speaker 1: like we're totally what are we going to say? Like

478
00:25:46,320 --> 00:25:48,679
Speaker 1: we don't know? And we'll never know, so go crazy.

479
00:25:48,840 --> 00:25:52,159
Speaker 2: Yeah, that's I think that's fair. I guess for me,

480
00:25:52,640 --> 00:25:55,600
Speaker 2: that makes it very important to look at the size

481
00:25:55,600 --> 00:25:58,560
Speaker 2: of these impacts. So an example that people always give

482
00:25:58,720 --> 00:26:00,439
Speaker 2: in this space when they want to argue that we

483
00:26:00,440 --> 00:26:04,320
Speaker 2: should use observational data that it's good is smoking. They say,

484
00:26:04,359 --> 00:26:07,080
Speaker 2: you know, well, in you know, when the first evidence

485
00:26:07,119 --> 00:26:09,960
Speaker 2: that's smoking gave you lung cancer was from just comparing

486
00:26:10,000 --> 00:26:12,200
Speaker 2: smokers to non smokers, And you know.

487
00:26:12,200 --> 00:26:14,440
Speaker 3: That if we had really trusted.

488
00:26:14,080 --> 00:26:16,680
Speaker 2: That evidence, then you know, which later was confirmed my

489
00:26:16,760 --> 00:26:19,080
Speaker 2: randomized trials. But if we'd really trusted that evidence, we

490
00:26:19,119 --> 00:26:22,000
Speaker 2: would have you know, told people to stop smoking earlier.

491
00:26:22,240 --> 00:26:23,240
Speaker 3: And that's true.

492
00:26:23,600 --> 00:26:26,440
Speaker 2: But in the smoking data, the excess risk of lung

493
00:26:26,480 --> 00:26:29,200
Speaker 2: cancer was like sixty times. It was like a sixty

494
00:26:29,440 --> 00:26:33,919
Speaker 2: six thousand percent increase in lunchture and it was not subtle.

495
00:26:33,960 --> 00:26:36,000
Speaker 2: And so you could say, well, is it likely that

496
00:26:36,080 --> 00:26:40,399
Speaker 2: the other differences across these people could drive this effect

497
00:26:40,440 --> 00:26:43,840
Speaker 2: to be sixty times as big, especially given that it's

498
00:26:43,840 --> 00:26:47,399
Speaker 2: a cancer associated with something that you're inhaling through a smoke,

499
00:26:47,440 --> 00:26:50,919
Speaker 2: like there's some biological plausibility, and the effect size was

500
00:26:51,040 --> 00:26:53,879
Speaker 2: so big. I think where I get stuck in a

501
00:26:53,920 --> 00:26:56,720
Speaker 2: lot of these things. Is we're saying, Okay, we're comparing

502
00:26:56,720 --> 00:26:58,439
Speaker 2: this kind of diet to this kind of diet or

503
00:26:58,440 --> 00:27:01,520
Speaker 2: this food to this food, and the increase in cardiovascular

504
00:27:01,640 --> 00:27:04,679
Speaker 2: risk is like seven percent, And it feels to me

505
00:27:04,840 --> 00:27:07,840
Speaker 2: like I can I can imagine we get a seven

506
00:27:07,840 --> 00:27:11,040
Speaker 2: percent increase from the many other differences across these people,

507
00:27:11,119 --> 00:27:14,000
Speaker 2: and so like maybe we look at the observational data,

508
00:27:14,000 --> 00:27:16,800
Speaker 2: but the kind of observational data with tiny effect sizes

509
00:27:17,560 --> 00:27:20,840
Speaker 2: tells me like you should this is it feels like zero.

510
00:27:21,160 --> 00:27:26,639
Speaker 1: Yeah, I mean, we may conclude that the evidence and

511
00:27:26,720 --> 00:27:28,919
Speaker 1: is strong enough for you to seriously worry about, and

512
00:27:29,000 --> 00:27:30,800
Speaker 1: like in terms of the mental energy you want to

513
00:27:30,840 --> 00:27:34,120
Speaker 1: spend trying to get healthier, Like there are other areas

514
00:27:34,160 --> 00:27:36,840
Speaker 1: where there's stronger evidence, like not smoking. Right, if you

515
00:27:37,000 --> 00:27:39,119
Speaker 1: are a smoker and are debating whether you should be

516
00:27:39,119 --> 00:27:42,480
Speaker 1: eating red meat or chicken, don't worry about it. Quit

517
00:27:42,520 --> 00:27:44,280
Speaker 1: stop smoking.

518
00:27:44,480 --> 00:27:47,280
Speaker 2: Yeah all right, I feel like I literally, I mean,

519
00:27:47,280 --> 00:27:48,639
Speaker 2: this is a topic of my research.

520
00:27:48,640 --> 00:27:50,160
Speaker 3: So I could literally talk about.

521
00:27:49,920 --> 00:27:53,720
Speaker 2: This for like an entire semester course, but maybe we

522
00:27:53,720 --> 00:27:54,560
Speaker 2: should move on to.

523
00:27:55,200 --> 00:27:58,240
Speaker 1: As long as I can get a credit because.

524
00:27:58,760 --> 00:28:01,760
Speaker 2: Continuing medici metaical education credit for I need some of

525
00:28:01,800 --> 00:28:06,040
Speaker 2: those we meant about my feelings. Okay, all right, So

526
00:28:06,160 --> 00:28:08,600
Speaker 2: with that as the background, I think that tells us

527
00:28:08,800 --> 00:28:12,000
Speaker 2: the to step out of the weeds a bit. I

528
00:28:12,000 --> 00:28:13,920
Speaker 2: think what this says is that it is actually quite

529
00:28:13,960 --> 00:28:16,240
Speaker 2: difficult to answer this question. And part of the reason

530
00:28:16,280 --> 00:28:20,919
Speaker 2: we see so much debate and discussion and disagreement about

531
00:28:21,000 --> 00:28:25,960
Speaker 2: questions around nutrition, including red meat, is that the data

532
00:28:26,080 --> 00:28:31,160
Speaker 2: is not perfect or really very good for the most part.

533
00:28:33,040 --> 00:28:37,399
Speaker 1: Yeah, so let's let me draw mechanism for you and

534
00:28:37,600 --> 00:28:40,520
Speaker 1: saying what we do have with high quality data. Let's

535
00:28:40,560 --> 00:28:43,600
Speaker 1: start with cardiovascular disease because I think that's what people

536
00:28:43,680 --> 00:28:46,520
Speaker 1: often think about, but we will get to cancer because

537
00:28:46,520 --> 00:28:50,360
Speaker 1: that's sort of an emerging concern from certain dietary habits.

538
00:28:50,880 --> 00:28:55,080
Speaker 1: So in terms of cardiovascular disease, we do know from

539
00:28:55,120 --> 00:28:59,240
Speaker 1: fairly high quality evidence that in randomized trials over a

540
00:28:59,240 --> 00:29:01,640
Speaker 1: limited period of time, yes not over years and years

541
00:29:01,680 --> 00:29:05,600
Speaker 1: and years, but over you know, weeks to months, replacing

542
00:29:05,600 --> 00:29:09,400
Speaker 1: a diet high and saturated fat with a diet lower

543
00:29:09,440 --> 00:29:14,960
Speaker 1: and saturated fat reduces LDL cholesterol. So this comes from

544
00:29:15,360 --> 00:29:19,760
Speaker 1: the Cochrane collaboration, which is many people would say the

545
00:29:19,800 --> 00:29:24,560
Speaker 1: gold standard of evidence synthesis groups. They performed a meta

546
00:29:24,560 --> 00:29:30,320
Speaker 1: analysis of fifty something trials in this space and found

547
00:29:30,320 --> 00:29:34,840
Speaker 1: this relationship to LDL cholesterol. It was stronger in people

548
00:29:34,880 --> 00:29:37,680
Speaker 1: who had higher LDL cholesterols to begin with. So there's,

549
00:29:37,800 --> 00:29:40,120
Speaker 1: you know, potentially some floor effect here. You can only

550
00:29:40,200 --> 00:29:41,800
Speaker 1: you know, there's only so much bang for your buck

551
00:29:41,800 --> 00:29:45,520
Speaker 1: you can get by switching out saturated fats for unsaturated fats.

552
00:29:45,600 --> 00:29:47,680
Speaker 1: And of course you can get saturated fats from places

553
00:29:47,680 --> 00:29:49,480
Speaker 1: that aren't red meat. But I think if we're really

554
00:29:49,480 --> 00:29:52,200
Speaker 1: thinking about like a high red meat diet, that is

555
00:29:52,240 --> 00:29:54,920
Speaker 1: an area of major concern is the saturated fats. So

556
00:29:55,760 --> 00:29:59,320
Speaker 1: looks to me like it increases LDL. I think, rightly,

557
00:29:59,360 --> 00:30:00,800
Speaker 1: switching it out decrease LDL.

558
00:30:01,040 --> 00:30:03,720
Speaker 2: Yeah, that switching it out will decrease l D. I

559
00:30:03,760 --> 00:30:06,280
Speaker 2: think that seems that seems fair. I think the biological

560
00:30:06,320 --> 00:30:10,040
Speaker 2: mechanism works. I think the evidence is reasonable. But these

561
00:30:10,040 --> 00:30:14,640
Speaker 2: effects are not like spectacularly large, but they are.

562
00:30:14,440 --> 00:30:17,400
Speaker 3: Significant yep, in a statistical sense.

563
00:30:18,000 --> 00:30:21,360
Speaker 2: Okay, And then what we I think would most want

564
00:30:21,400 --> 00:30:24,680
Speaker 2: to know then is does that have any actual like

565
00:30:25,000 --> 00:30:26,080
Speaker 2: health implications?

566
00:30:26,280 --> 00:30:31,960
Speaker 1: Yeah? Like so okay, so we know, go with me. Here,

567
00:30:32,320 --> 00:30:37,600
Speaker 1: we know from randomized trial data that reducing LDL reduces

568
00:30:37,640 --> 00:30:41,640
Speaker 1: the risk of cardiovascular events. This is from Staton trials

569
00:30:41,680 --> 00:30:46,600
Speaker 1: for example. Okay, so I know what you're gonna say,

570
00:30:46,640 --> 00:30:53,040
Speaker 1: but you know, if reducing saturated fat intake reduces LDL

571
00:30:53,920 --> 00:31:00,000
Speaker 1: and reducing LDL, albeit by some other mechanism, reduces cardiovascular events,

572
00:31:00,720 --> 00:31:04,720
Speaker 1: I'm comfortable saying probably reducing saturated fat intake will reduce

573
00:31:04,760 --> 00:31:06,600
Speaker 1: the risk of cardiovascular events.

574
00:31:07,120 --> 00:31:09,640
Speaker 3: And I will say that.

575
00:31:10,880 --> 00:31:15,160
Speaker 2: If you look in the Cochrane review trials that do

576
00:31:15,400 --> 00:31:19,880
Speaker 2: try to look long term at saturated fat and cardiovascular events,

577
00:31:20,240 --> 00:31:26,800
Speaker 2: you do see a small, marginally significant reduction in cardiovascular

578
00:31:26,800 --> 00:31:31,080
Speaker 2: events with a diet. What you don't see is impacts

579
00:31:31,120 --> 00:31:31,800
Speaker 2: on mortality.

580
00:31:32,520 --> 00:31:33,760
Speaker 3: So although we see.

581
00:31:33,600 --> 00:31:37,320
Speaker 2: Reductions in cardiovascular events, we do not see reductions in

582
00:31:37,560 --> 00:31:41,640
Speaker 2: all cause mortality or cardiovascular mortality.

583
00:31:41,840 --> 00:31:46,280
Speaker 3: So this relationship seems is more complicated to me.

584
00:31:46,360 --> 00:31:49,200
Speaker 2: Then we might think, Yeah, I guess I think it

585
00:31:49,200 --> 00:31:52,040
Speaker 2: would be a stretch to say that reducing your red

586
00:31:52,080 --> 00:31:54,760
Speaker 2: meat intake, of reducing your saturated fat intake would cause

587
00:31:54,760 --> 00:31:55,600
Speaker 2: you to live longer.

588
00:31:56,240 --> 00:31:57,760
Speaker 3: Maybe it's not a stretch to say.

589
00:31:57,600 --> 00:32:00,720
Speaker 2: It would reduce your LDL and that it might reduce

590
00:32:00,760 --> 00:32:04,000
Speaker 2: your risk of cardiovascular events by a small amount.

591
00:32:04,720 --> 00:32:07,480
Speaker 1: Yeah. I mean death is messy. That you can unfortunately,

592
00:32:07,520 --> 00:32:11,000
Speaker 1: you can die. You can die from many things and uh,

593
00:32:11,120 --> 00:32:15,640
Speaker 1: and so it's always harder to prove an overall mortality benefit. Certainly,

594
00:32:15,680 --> 00:32:18,920
Speaker 1: I'm not seeing anything that suggests that like enhancing red

595
00:32:18,920 --> 00:32:22,640
Speaker 1: meat in your diet is doing anything particularly wonderful for

596
00:32:22,720 --> 00:32:25,680
Speaker 1: you systematically, and we should say or in terms of

597
00:32:25,680 --> 00:32:29,440
Speaker 1: cardiovascular disease at least. And we should say though that

598
00:32:29,800 --> 00:32:33,160
Speaker 1: the vast majority of real studies that look at red

599
00:32:33,160 --> 00:32:38,040
Speaker 1: meat and take are using unprocessed like lean red meat,

600
00:32:38,080 --> 00:32:40,840
Speaker 1: like not lean, you know, but like red meat that

601
00:32:40,840 --> 00:32:45,400
Speaker 1: you would buy in the refrigerator section of the grocery store,

602
00:32:45,680 --> 00:32:48,080
Speaker 1: not processed red meat. And I think we need to

603
00:32:48,080 --> 00:32:50,640
Speaker 1: touch on this when we get to cancer, because there's

604
00:32:50,680 --> 00:32:55,120
Speaker 1: a big difference between eating like a steak, you know,

605
00:32:55,160 --> 00:32:57,920
Speaker 1: with its high saturated fat and but high amount of

606
00:32:57,960 --> 00:33:02,800
Speaker 1: protein and relatively little other things and like a equivalent

607
00:33:02,800 --> 00:33:06,800
Speaker 1: amount of processed salami or something like that, And we

608
00:33:07,160 --> 00:33:07,960
Speaker 1: can talk about that.

609
00:33:08,360 --> 00:33:09,440
Speaker 3: Yeah, let's get into that.

610
00:33:09,480 --> 00:33:12,200
Speaker 2: But I think here here we are really talking about

611
00:33:12,360 --> 00:33:19,120
Speaker 2: the like again kind of switching out your red meat

612
00:33:19,320 --> 00:33:23,959
Speaker 2: for a calorically equivalent amount of chicken.

613
00:33:24,480 --> 00:33:27,480
Speaker 1: Yeah, it's a way to slightly party vascular resists. They're

614
00:33:27,520 --> 00:33:30,280
Speaker 1: probably they're probably better ways to reduce your cardiovascular risk.

615
00:33:30,360 --> 00:33:32,200
Speaker 3: Yeah, like exercising or not smoking.

616
00:33:32,440 --> 00:33:37,160
Speaker 1: Yes, yeah, those are better. But let's talk about cancer.

617
00:33:38,280 --> 00:33:40,280
Speaker 1: This is the concern I've heard most from people I've

618
00:33:40,280 --> 00:33:42,200
Speaker 1: talked to about this. But it's interesting. I feel like

619
00:33:42,200 --> 00:33:45,240
Speaker 1: for my parents' generation, like heart attacks and strokes were

620
00:33:45,400 --> 00:33:47,320
Speaker 1: the thing that killed everyone, and they were very concerned

621
00:33:47,360 --> 00:33:49,960
Speaker 1: about this. And I think to some extent, because we've

622
00:33:50,000 --> 00:33:53,080
Speaker 1: gotten a better handle on cholesterol management, like that's at

623
00:33:53,240 --> 00:33:56,000
Speaker 1: less scary to our generation who thinks more about cancer

624
00:33:56,000 --> 00:34:01,800
Speaker 1: and dementia. There has been a row eyes in colon

625
00:34:01,840 --> 00:34:06,920
Speaker 1: cancer diagnoses among younger and younger people in the United States.

626
00:34:07,520 --> 00:34:11,640
Speaker 1: There's an interesting discussion about what the causes of that are,

627
00:34:12,000 --> 00:34:14,600
Speaker 1: but it's certainly in the zeitgeist. People are thinking about this.

628
00:34:14,640 --> 00:34:17,920
Speaker 1: Even the guidelines for colon cancer screening have recently changed

629
00:34:17,960 --> 00:34:20,520
Speaker 1: to start at a younger age, to start at forty

630
00:34:20,520 --> 00:34:22,960
Speaker 1: five instead of fifty. Based on some of this data

631
00:34:23,480 --> 00:34:28,160
Speaker 1: and most of the again observational data would suggest that

632
00:34:28,320 --> 00:34:33,160
Speaker 1: higher red meat intake does increase the risk of correctal cancer.

633
00:34:33,719 --> 00:34:36,040
Speaker 3: Yes, most of the observational data would say.

634
00:34:35,840 --> 00:34:40,120
Speaker 1: That, yeah, does that worry you?

635
00:34:40,200 --> 00:34:45,160
Speaker 2: No? I mean, like, does it worry I am worried

636
00:34:45,200 --> 00:34:47,279
Speaker 2: about the rise in colon cancer among younger people?

637
00:34:47,320 --> 00:34:49,759
Speaker 3: Of course, do I.

638
00:34:52,320 --> 00:34:54,000
Speaker 2: Me think about how to say this?

639
00:34:54,320 --> 00:34:54,400
Speaker 4: So?

640
00:34:54,560 --> 00:34:58,319
Speaker 2: Do I think it is plausible that changes in dietary

641
00:34:58,360 --> 00:35:00,840
Speaker 2: patterns have driven some of this and colon cancer.

642
00:35:00,960 --> 00:35:01,560
Speaker 3: Absolutely?

643
00:35:01,920 --> 00:35:04,520
Speaker 2: I think people obesity rates have gone up. My guess

644
00:35:04,560 --> 00:35:08,320
Speaker 2: is that explains a fair amount of this surprise. Consumption

645
00:35:08,440 --> 00:35:11,680
Speaker 2: of whole foods fiber in particular, has gone down. My

646
00:35:11,719 --> 00:35:14,080
Speaker 2: guess is that also explained something with the rides, clearly

647
00:35:14,160 --> 00:35:17,399
Speaker 2: something we need to understand much better. Some of the

648
00:35:17,560 --> 00:35:19,920
Speaker 2: data that's come out of at GLP ones suggests that

649
00:35:19,960 --> 00:35:22,279
Speaker 2: they reduce the risk of colon cancer, which I think

650
00:35:22,320 --> 00:35:25,520
Speaker 2: points to at least the first of those mechanisms as

651
00:35:25,600 --> 00:35:30,920
Speaker 2: being important. If you asked me, do I think that

652
00:35:31,040 --> 00:35:37,839
Speaker 2: replacing tofu and chicken with a calorically equivalent amount of

653
00:35:38,520 --> 00:35:42,560
Speaker 2: beef in your diet would raise your risk of colon cancer?

654
00:35:43,160 --> 00:35:46,960
Speaker 2: I do not think that that is supported by the data.

655
00:35:47,320 --> 00:35:51,680
Speaker 2: The observational data on this is just it's really weak.

656
00:35:51,719 --> 00:35:55,200
Speaker 2: It's confounded by other aspects of people's diet. It's confounded

657
00:35:55,239 --> 00:35:56,600
Speaker 2: by the fact that a lot of the ways people

658
00:35:56,640 --> 00:35:59,680
Speaker 2: are eating red meat are altar processed.

659
00:35:59,800 --> 00:36:03,120
Speaker 3: A Yeah, with Dorito's.

660
00:36:03,560 --> 00:36:06,279
Speaker 2: I mean this feels to me like the data is

661
00:36:06,400 --> 00:36:10,760
Speaker 2: so poor that if that's the question people are asking,

662
00:36:10,800 --> 00:36:13,719
Speaker 2: I think absolutely absolutely not. And I will say, let

663
00:36:13,719 --> 00:36:15,160
Speaker 2: me just say one other thing, which is that we

664
00:36:15,239 --> 00:36:19,520
Speaker 2: have one pretty large scale, long term health study that

665
00:36:19,600 --> 00:36:22,399
Speaker 2: evaluated the risk of cancer with a with a low

666
00:36:22,440 --> 00:36:24,960
Speaker 2: fat diet. It wasn't red meat and specific specifically, but

667
00:36:25,200 --> 00:36:29,440
Speaker 2: by evaluated low fat diet called the Women's Health.

668
00:36:30,760 --> 00:36:33,520
Speaker 1: Is Sorry, Women's Health Initiative Dietary Modification Trial.

669
00:36:34,120 --> 00:36:36,799
Speaker 2: Yes, the Women's Health Initiative Dietary Modification Trial. And that

670
00:36:36,960 --> 00:36:39,680
Speaker 2: showed no impact of switching people to a low fat

671
00:36:39,680 --> 00:36:43,560
Speaker 2: diet on cancer risk or basically anything anything else. And

672
00:36:43,800 --> 00:36:46,640
Speaker 2: you know that's that feels informative to me.

673
00:36:47,960 --> 00:36:54,279
Speaker 1: Yeah. I suspect this is true for unprocessed red meat,

674
00:36:54,960 --> 00:37:00,360
Speaker 1: and I'm worried. From a biological perspective on process meats,

675
00:37:01,360 --> 00:37:04,080
Speaker 1: there has long been, for example, a dramatically higher rate

676
00:37:04,120 --> 00:37:07,480
Speaker 1: of gastric cancer in China than there is in the

677
00:37:07,600 --> 00:37:13,839
Speaker 1: United States and thought to be driven by heavily uh

678
00:37:14,480 --> 00:37:18,920
Speaker 1: preserved you know, meat intake and protein intake. There have

679
00:37:18,960 --> 00:37:23,160
Speaker 1: been a number of studies that show that these nitroso compounds,

680
00:37:23,200 --> 00:37:26,880
Speaker 1: like use nitrates to preserve to preserve meats in things

681
00:37:26,880 --> 00:37:29,960
Speaker 1: like slim gems and stuff like that. There are studies

682
00:37:30,000 --> 00:37:32,920
Speaker 1: in you know, in patry dishes and stuff that that

683
00:37:33,000 --> 00:37:36,200
Speaker 1: do show that these these compounds can damage cells and

684
00:37:36,239 --> 00:37:38,880
Speaker 1: can affect the lining of the GI tract. And you

685
00:37:38,880 --> 00:37:43,239
Speaker 1: can actually recover these compounds in stool in like the

686
00:37:43,280 --> 00:37:46,480
Speaker 1: poop of people based on how much they take in. So,

687
00:37:47,520 --> 00:37:51,080
Speaker 1: you know, I think, you know, having that nice steak

688
00:37:51,200 --> 00:37:54,560
Speaker 1: is one thing. Having a bunch of slim gems is

689
00:37:54,560 --> 00:37:57,719
Speaker 1: another thing. But you know, to your point, Emily, there's

690
00:37:57,719 --> 00:37:59,839
Speaker 1: a certain type of person who can afford to have

691
00:38:00,480 --> 00:38:02,680
Speaker 1: the nice steak, and they probably can afford a lot

692
00:38:02,680 --> 00:38:05,160
Speaker 1: of other healthful things. And then there's a type of

693
00:38:05,200 --> 00:38:08,719
Speaker 1: person whose major source of calories is going to come

694
00:38:08,719 --> 00:38:11,480
Speaker 1: from that type of foods because they can't afford to

695
00:38:11,480 --> 00:38:13,400
Speaker 1: eat the nice steak at the end, and that's going

696
00:38:13,440 --> 00:38:14,760
Speaker 1: to be a major source of confounding.

697
00:38:15,360 --> 00:38:17,520
Speaker 2: Yeah, it's a major source of confounding. And I will say,

698
00:38:17,520 --> 00:38:19,600
Speaker 2: you know, back to my point about sizing. If you

699
00:38:19,640 --> 00:38:22,000
Speaker 2: look at like these meta analyzes and you know, what's

700
00:38:22,040 --> 00:38:24,040
Speaker 2: the size of the increase in risk. We're talking about

701
00:38:24,080 --> 00:38:27,440
Speaker 2: like a twenty percent increase in risk, not a four

702
00:38:27,520 --> 00:38:30,279
Speaker 2: hundred percent increase or a four thousand percent increase, and.

703
00:38:30,480 --> 00:38:32,680
Speaker 3: That that's not that big an effect.

704
00:38:32,680 --> 00:38:34,960
Speaker 2: I mean, it feels big, it's like, wow, twenty percent increase,

705
00:38:35,000 --> 00:38:39,880
Speaker 2: but it's actually magnitude quite small, and it could easily

706
00:38:39,920 --> 00:38:43,640
Speaker 2: be explained by either other aspects of people's diet, other

707
00:38:43,680 --> 00:38:46,040
Speaker 2: aspects of their exercise smoking. I mean, we see like

708
00:38:46,480 --> 00:38:51,160
Speaker 2: everything is different between groups that eat more and less

709
00:38:51,200 --> 00:38:52,840
Speaker 2: red meat in these observational studies.

710
00:38:52,920 --> 00:38:56,840
Speaker 3: Everything, not just a few things, literally everything. Yeah, And

711
00:38:56,920 --> 00:38:58,839
Speaker 3: I think that's Destra's really hard to fix.

712
00:38:59,239 --> 00:39:02,760
Speaker 1: It's very hard to fix. And diet is so culturally relevant,

713
00:39:02,760 --> 00:39:05,560
Speaker 1: Like diet is just it's so much a part of you.

714
00:39:05,680 --> 00:39:09,480
Speaker 1: It is very hard to control anything here. I want

715
00:39:09,480 --> 00:39:14,240
Speaker 1: to move on to some other cancers, particularly breast cancer,

716
00:39:14,280 --> 00:39:18,960
Speaker 1: which is another obesity associated cancer as they are defined.

717
00:39:19,480 --> 00:39:23,439
Speaker 1: But there's an interesting trial here, the preadimed trial, which

718
00:39:23,440 --> 00:39:25,320
Speaker 1: I really like. This is about a seventy five hundred

719
00:39:25,400 --> 00:39:30,400
Speaker 1: participant trial who are randomized to sort of a Mediterranean diet,

720
00:39:31,000 --> 00:39:33,480
Speaker 1: which you know is again it's not really red meat.

721
00:39:33,480 --> 00:39:36,000
Speaker 1: It's actually a lot of like fish and legumes and

722
00:39:36,040 --> 00:39:38,800
Speaker 1: things like that. But it's a lower carb diet and

723
00:39:39,080 --> 00:39:43,000
Speaker 1: a higher amount of meat protein either with olive oil

724
00:39:43,160 --> 00:39:48,320
Speaker 1: or nuts versus a control diet. And the Mediterranean diet

725
00:39:48,400 --> 00:39:51,919
Speaker 1: arms which you know limit red and processed meat, significantly

726
00:39:51,960 --> 00:39:55,320
Speaker 1: had a sixty two percent reduction in breast cancer incidents.

727
00:39:56,239 --> 00:39:58,319
Speaker 1: Now this wasn't the primary endpoint of the trial, but

728
00:39:59,000 --> 00:40:02,919
Speaker 1: you know, this is a Hasard issue zero point three eight.

729
00:40:03,200 --> 00:40:06,160
Speaker 1: That's a relatively big effect size. You wanted some big

730
00:40:06,160 --> 00:40:09,920
Speaker 1: effects sizes. This is a randomized trial. It's not just

731
00:40:10,080 --> 00:40:12,600
Speaker 1: limiting red meat. It's also like olive oil and nuts

732
00:40:12,640 --> 00:40:16,759
Speaker 1: and beans and all the other wonderful things from the

733
00:40:16,800 --> 00:40:20,960
Speaker 1: Mediterranean diet that might be affecting things here. But it's

734
00:40:21,160 --> 00:40:24,600
Speaker 1: again some evidence that the dietary, a red meat dominant

735
00:40:24,640 --> 00:40:27,480
Speaker 1: dietary pattern may not be the best.

736
00:40:28,520 --> 00:40:30,839
Speaker 2: Yeah, I mean, I think we have the Mediterranean diet

737
00:40:30,920 --> 00:40:33,600
Speaker 2: is one of our best tested diets. Like you if

738
00:40:33,640 --> 00:40:36,320
Speaker 2: you said, you know, I'm totally neutral.

739
00:40:36,360 --> 00:40:37,000
Speaker 3: I don't care what.

740
00:40:37,000 --> 00:40:39,960
Speaker 2: I eat, just tell me what's the best kind of

741
00:40:40,120 --> 00:40:43,520
Speaker 2: diet for overall health that we have seen in the data.

742
00:40:43,560 --> 00:40:46,080
Speaker 3: I think it is it is the Mediterranean diet.

743
00:40:46,440 --> 00:40:48,839
Speaker 2: This has a lot of components, as you said, not

744
00:40:49,000 --> 00:40:50,560
Speaker 2: just an avoidance of red meat.

745
00:40:50,920 --> 00:40:52,840
Speaker 3: It's not that we have head to head tested that

746
00:40:53,040 --> 00:40:55,360
Speaker 3: versus a version of that that has.

747
00:40:55,160 --> 00:40:58,440
Speaker 2: A higher red meat, right component, And I think that's

748
00:40:58,800 --> 00:41:00,440
Speaker 2: there's a limit to what we can from that.

749
00:41:00,840 --> 00:41:05,360
Speaker 1: Yeah, yeah, fair. There's a couple of things that people

750
00:41:05,520 --> 00:41:08,080
Speaker 1: wanted us to dig in on here as they're thinking

751
00:41:08,120 --> 00:41:10,920
Speaker 1: about red meat. I think people get the idea that,

752
00:41:11,000 --> 00:41:13,640
Speaker 1: like there's a difference between beef, jerky and salami and

753
00:41:13,680 --> 00:41:17,520
Speaker 1: like processed meats and the steak and unprocessed stuff. You

754
00:41:17,560 --> 00:41:21,239
Speaker 1: get people like eating steak. It's quite pleasurable for a

755
00:41:21,239 --> 00:41:23,640
Speaker 1: lot of people. One question I got asked a lot

756
00:41:23,840 --> 00:41:27,880
Speaker 1: is the difference between like grass fed and non grass

757
00:41:27,880 --> 00:41:30,879
Speaker 1: fed beef, Like should we be paying a premium for this?

758
00:41:33,480 --> 00:41:35,160
Speaker 3: I think it just it tastes different.

759
00:41:35,239 --> 00:41:38,040
Speaker 2: And I think this to me feels like you absolutely

760
00:41:38,600 --> 00:41:42,000
Speaker 2: absolutely are not going to get any evidence that is

761
00:41:42,160 --> 00:41:43,920
Speaker 2: meaningful on this. What you're going to find is that

762
00:41:43,960 --> 00:41:46,520
Speaker 2: grass fed beef is eaten by rich people, average people

763
00:41:46,560 --> 00:41:49,880
Speaker 2: are doing better on their health for a lot of reasons.

764
00:41:49,920 --> 00:41:53,479
Speaker 2: It's probably not the grass fed beef. But if that's

765
00:41:53,920 --> 00:41:55,279
Speaker 2: a thing you want to spend your money on and

766
00:41:55,320 --> 00:41:56,839
Speaker 2: you like the way it tastes better and you feel

767
00:41:56,880 --> 00:41:58,360
Speaker 2: better about it, like that's great.

768
00:41:58,840 --> 00:42:01,359
Speaker 1: It is it is a bit leaner. So again, yeah,

769
00:42:01,560 --> 00:42:03,239
Speaker 1: I agree, you're not gonna it's not gonna make a

770
00:42:03,239 --> 00:42:05,040
Speaker 1: difference in your in your long term health. It does

771
00:42:05,080 --> 00:42:08,000
Speaker 1: have slightly less fat. Actually in the research though, I

772
00:42:08,120 --> 00:42:12,560
Speaker 1: found that in twenty sixteen, the US uh what is it?

773
00:42:12,680 --> 00:42:19,080
Speaker 1: USDA eliminated their definitions, like their inspection process for grass

774
00:42:19,080 --> 00:42:23,959
Speaker 1: fed beef. So now it's it's via self certification, so

775
00:42:24,480 --> 00:42:28,279
Speaker 1: the meat producers themselves get to tell you whether they

776
00:42:28,320 --> 00:42:31,240
Speaker 1: are grass fed or not they have seen the cow.

777
00:42:32,200 --> 00:42:34,320
Speaker 3: Unless you have seen the COWI you cannot be sure.

778
00:42:35,000 --> 00:42:36,880
Speaker 1: You cannot be sure. This is like a trust us

779
00:42:36,960 --> 00:42:41,960
Speaker 1: brouh type of situation. So let's touch on the carnivore

780
00:42:41,960 --> 00:42:46,640
Speaker 1: diet because like we've kind of talked about dietary patterns.

781
00:42:47,040 --> 00:42:50,279
Speaker 1: Certain dietary patterns have more red meat. But like this

782
00:42:50,360 --> 00:42:53,319
Speaker 1: is the apotheosis of being a meat eater, right, I

783
00:42:53,360 --> 00:42:56,280
Speaker 1: am only going to eat meat. This isn't even paleo

784
00:42:56,360 --> 00:42:58,760
Speaker 1: where it's like we can have greens. This is meat

785
00:42:58,920 --> 00:43:01,200
Speaker 1: exclusively and or meets exclusively.

786
00:43:01,560 --> 00:43:02,799
Speaker 3: It's like the I mean, it's so.

787
00:43:03,239 --> 00:43:05,719
Speaker 2: I think what's interesting about the carnivore diet is its

788
00:43:05,719 --> 00:43:07,880
Speaker 2: connection to the keto diet, which is something that we

789
00:43:07,920 --> 00:43:11,040
Speaker 2: should spend an episode on, which is a diet with

790
00:43:11,080 --> 00:43:13,880
Speaker 2: effectively no carbohydrates.

791
00:43:13,080 --> 00:43:14,360
Speaker 1: Like extraordinarily low carbs.

792
00:43:14,480 --> 00:43:18,640
Speaker 2: Yeah, I had some interesting results on treating some diseases.

793
00:43:18,840 --> 00:43:22,399
Speaker 2: It's like, that's an interesting Diet's very very heartistic too,

794
00:43:22,880 --> 00:43:24,600
Speaker 2: because it's really really restrictive.

795
00:43:25,239 --> 00:43:27,000
Speaker 3: The carnivore diet is kind.

796
00:43:26,840 --> 00:43:29,920
Speaker 2: Of a like a Broye version of more relaxed Broi

797
00:43:30,120 --> 00:43:33,560
Speaker 2: version of that. It has almost no fiber. So I

798
00:43:33,680 --> 00:43:37,800
Speaker 2: would be shocked. I'm not saying I would be interested

799
00:43:37,840 --> 00:43:41,640
Speaker 2: in this. I am kind of interested in how people's digestion.

800
00:43:41,640 --> 00:43:43,080
Speaker 3: Is on the carnivore diet.

801
00:43:43,200 --> 00:43:47,680
Speaker 2: I would imagine if fiber is nature's broom, I'm concerned.

802
00:43:47,600 --> 00:43:51,920
Speaker 1: Oh my god, that what happens bro Bruh, I haven't

803
00:43:52,040 --> 00:43:54,320
Speaker 1: I haven't pooped in two weeks, bra, exactly.

804
00:43:54,400 --> 00:43:56,319
Speaker 2: I haven't put in two weeks, BRA, and so I

805
00:43:56,360 --> 00:43:58,279
Speaker 2: think this is going to be a this is a

806
00:43:58,400 --> 00:44:01,080
Speaker 2: very extreme form of the diet. To know often when

807
00:44:01,080 --> 00:44:04,120
Speaker 2: we are eating something that is so extreme, like what

808
00:44:04,200 --> 00:44:08,800
Speaker 2: that's going to do to our yeah systems.

809
00:44:08,520 --> 00:44:12,120
Speaker 1: And just like evolutionarily right, like we're not carnivores. Humans

810
00:44:12,160 --> 00:44:15,840
Speaker 1: are clearly omnivores. And in fact, you don't have to

811
00:44:15,840 --> 00:44:19,360
Speaker 1: take my word for it, we don't contain the apparatus

812
00:44:19,400 --> 00:44:22,000
Speaker 1: to synthesize certain things that only come from plants, like

813
00:44:22,080 --> 00:44:27,160
Speaker 1: vitamin C. For vitamin C, for example, some animals carnivores

814
00:44:27,239 --> 00:44:30,000
Speaker 1: actually synthesize their own vitamin C. So like tigers and

815
00:44:30,000 --> 00:44:32,160
Speaker 1: lions don't get scurvy because they can make their own

816
00:44:32,239 --> 00:44:34,040
Speaker 1: vitamin C and they don't have to eat fruits and

817
00:44:34,120 --> 00:44:36,920
Speaker 1: vegetables and stuff. We can't, so we need to get

818
00:44:37,000 --> 00:44:39,759
Speaker 1: vitamin C from other sources. Actually look to see if

819
00:44:39,760 --> 00:44:42,240
Speaker 1: there's been case reports of people on the carnivore diet

820
00:44:42,600 --> 00:44:46,600
Speaker 1: developing scurvy. I did find one case of a guy

821
00:44:46,800 --> 00:44:49,880
Speaker 1: who was kind of he was living alone in a

822
00:44:49,960 --> 00:44:52,360
Speaker 1: hut in Appalachia. I don't think he would have described

823
00:44:52,400 --> 00:44:55,400
Speaker 1: himself as being on the carnivore diet, but he clearly

824
00:44:55,520 --> 00:44:58,600
Speaker 1: was only eating meat and he did develop scurvy.

825
00:44:59,040 --> 00:45:01,600
Speaker 2: There are some meat that have vitamin C at like

826
00:45:01,680 --> 00:45:05,080
Speaker 2: seal meat. That's what I learned from one of the many, many,

827
00:45:05,160 --> 00:45:07,839
Speaker 2: many books I've read about people who die in Antarctica,

828
00:45:07,880 --> 00:45:10,799
Speaker 2: which is my favorite book genre. But it turns out

829
00:45:10,800 --> 00:45:14,440
Speaker 2: eating like penguins and seals have have vitamin C.

830
00:45:14,840 --> 00:45:17,080
Speaker 1: Right. It was always kind of a mystery that, like,

831
00:45:17,120 --> 00:45:20,440
Speaker 1: how do you know Inuits who really have almost no plant

832
00:45:20,480 --> 00:45:23,279
Speaker 1: intake like not get scurvy? And and yeah, that's part

833
00:45:23,280 --> 00:45:25,879
Speaker 1: of it. Blubber has vitamin C. Vitamin c's broken down

834
00:45:25,920 --> 00:45:28,399
Speaker 1: by heat though, so a lot of that comes from

835
00:45:28,440 --> 00:45:33,480
Speaker 1: like eating stuff raw, the organ meats that people who

836
00:45:33,560 --> 00:45:36,080
Speaker 1: adhere to the carnivor diet, like liver does have some

837
00:45:36,200 --> 00:45:38,120
Speaker 1: vitamin C and it's still very low, like you've got

838
00:45:38,160 --> 00:45:39,280
Speaker 1: to be eating a fair amount.

839
00:45:39,360 --> 00:45:44,560
Speaker 2: But you know, let's just say it probably don't do this.

840
00:45:44,680 --> 00:45:48,439
Speaker 1: Don't do this. I'm not sure what it like. It's

841
00:45:48,480 --> 00:45:50,000
Speaker 1: of a theme of do you remember when we were

842
00:45:50,040 --> 00:45:54,200
Speaker 1: talking about declining sperm counts and we were sort of

843
00:45:54,239 --> 00:45:59,200
Speaker 1: like like, if you're not trying to get someone pregnant, like,

844
00:45:59,640 --> 00:46:01,160
Speaker 1: why do you care about that? I don't know there's

845
00:46:01,200 --> 00:46:04,759
Speaker 1: some like relationship here that I see. I think this

846
00:46:04,920 --> 00:46:08,080
Speaker 1: is a manosphere thing. I think this is a diet

847
00:46:08,120 --> 00:46:10,040
Speaker 1: that's like I'm a big tough guy and all I

848
00:46:10,080 --> 00:46:11,680
Speaker 1: have to do is eat me. And it's like I

849
00:46:11,719 --> 00:46:15,200
Speaker 1: don't care if I get you know, calling cancer from

850
00:46:15,480 --> 00:46:18,719
Speaker 1: you know, or just severe constipation from not having any

851
00:46:18,760 --> 00:46:23,320
Speaker 1: fib or scra or whatever terrible. Like you know, guys

852
00:46:23,520 --> 00:46:24,400
Speaker 1: eat a very diet.

853
00:46:25,440 --> 00:46:30,000
Speaker 2: Let's talk about beef tallow before we end, because people

854
00:46:30,040 --> 00:46:33,080
Speaker 2: love beef tallow and really loves it.

855
00:46:33,360 --> 00:46:33,520
Speaker 1: Yeah.

856
00:46:33,600 --> 00:46:35,680
Speaker 2: Yeah, Sometimes people as just like what do I do

857
00:46:35,719 --> 00:46:38,839
Speaker 2: with beef tallow? And it's just an it's another fat

858
00:46:38,880 --> 00:46:40,279
Speaker 2: and you could cook with it, and he can has

859
00:46:40,480 --> 00:46:43,719
Speaker 2: quite a high it has quite a high smoke point,

860
00:46:44,719 --> 00:46:47,239
Speaker 2: maybe making it good for cooking. I have one friend

861
00:46:47,280 --> 00:46:49,680
Speaker 2: who's like a very serious chef, and he said he

862
00:46:49,719 --> 00:46:52,600
Speaker 2: has beef tallow in his fridge because it's useful for

863
00:46:52,680 --> 00:46:57,319
Speaker 2: particular cooking cooking sources. People do like to put it

864
00:46:57,360 --> 00:47:01,239
Speaker 2: on their face as a moisturizer, but it can clog

865
00:47:01,280 --> 00:47:01,840
Speaker 2: your pores.

866
00:47:01,880 --> 00:47:05,200
Speaker 1: I think so, I would imagine it can.

867
00:47:05,440 --> 00:47:08,759
Speaker 2: But as some other moisturizers that you might purchase from,

868
00:47:08,920 --> 00:47:12,440
Speaker 2: say CBS so you know, we have I would say

869
00:47:12,880 --> 00:47:15,320
Speaker 2: this is a fat, you could use it to cook.

870
00:47:17,320 --> 00:47:18,840
Speaker 3: It's not a magic fat.

871
00:47:18,880 --> 00:47:23,239
Speaker 1: It's just no, it's not particularly healthy. There's a meta

872
00:47:23,320 --> 00:47:28,280
Speaker 1: analysis of fifty four randomized trials looking at LDL reduction

873
00:47:28,440 --> 00:47:33,120
Speaker 1: through supplements of various types of fats, and all of

874
00:47:33,160 --> 00:47:37,680
Speaker 1: the plant based oils reduced LDL more than beef tallow,

875
00:47:38,080 --> 00:47:42,200
Speaker 1: but beef tallow was better than butter. Like beef tallow

876
00:47:42,239 --> 00:47:45,480
Speaker 1: raise your LDL less than butter. So but like you've

877
00:47:45,480 --> 00:47:48,719
Speaker 1: got a million choices for fats, I don't particularly know.

878
00:47:48,760 --> 00:47:50,239
Speaker 1: I mean, it tastes good, actually, I mean, I think

879
00:47:50,280 --> 00:47:52,960
Speaker 1: the reason to use beef tallo is it's actually quite tasty.

880
00:47:53,360 --> 00:47:55,960
Speaker 1: If you've ever had French fries deep fried in beef tallow,

881
00:47:56,200 --> 00:47:59,120
Speaker 1: this isn't a good healthy snack by any stretch. But

882
00:47:59,160 --> 00:48:01,279
Speaker 1: they do they do taste good. Maybe that's okay. We're

883
00:48:01,280 --> 00:48:03,280
Speaker 1: supposed to get enjoyment out of life, right.

884
00:48:03,160 --> 00:48:05,200
Speaker 2: Totally, And I think that is I mean, that is

885
00:48:05,239 --> 00:48:07,640
Speaker 2: an important point for me here because sometimes we will

886
00:48:07,680 --> 00:48:12,120
Speaker 2: talk about sort of these these products that you'll say, well,

887
00:48:12,160 --> 00:48:15,080
Speaker 2: you know, what's the reason to have steak? If you know,

888
00:48:15,160 --> 00:48:16,800
Speaker 2: even if we only have a little bit of evidence

889
00:48:16,800 --> 00:48:19,799
Speaker 2: that plant based sources reduce our LDL and we can't

890
00:48:19,800 --> 00:48:22,480
Speaker 2: really connect it to health outcomes, you know, why not

891
00:48:22,560 --> 00:48:25,279
Speaker 2: do it? And the answer is like, well, I I

892
00:48:25,520 --> 00:48:28,440
Speaker 2: that's not the diet I would most prefer, and food

893
00:48:28,520 --> 00:48:33,120
Speaker 2: is something that we enjoy, and so that's actually a reason.

894
00:48:32,840 --> 00:48:33,640
Speaker 3: To do it.

895
00:48:34,280 --> 00:48:36,120
Speaker 1: Yeah, yeah, yeah yeah. Life is for the living.

896
00:48:36,880 --> 00:48:37,800
Speaker 3: Life is for the living.

897
00:48:38,160 --> 00:48:40,839
Speaker 1: I've got to go to one more thing before we

898
00:48:41,000 --> 00:48:43,759
Speaker 1: smasher past this one, Emily, because I had a feeling

899
00:48:43,760 --> 00:48:45,520
Speaker 1: how this was going to shake out. I felt like

900
00:48:45,560 --> 00:48:47,520
Speaker 1: Emily was going to look at all the observational data

901
00:48:47,600 --> 00:48:51,000
Speaker 1: and be like, this is all crap. It's fine, you know,

902
00:48:51,239 --> 00:48:54,640
Speaker 1: just be healthy. And and then I was like, but

903
00:48:54,680 --> 00:48:57,240
Speaker 1: I've got a trump card because I'm going to scour

904
00:48:57,280 --> 00:49:02,080
Speaker 1: the literature to find a study of endurance athletes and

905
00:49:02,719 --> 00:49:06,279
Speaker 1: see if I could show her that actually, if you're

906
00:49:06,280 --> 00:49:09,160
Speaker 1: an indurance athlete, eating red meat is better. So I

907
00:49:09,280 --> 00:49:14,520
Speaker 1: found a study, a huge study of twenty eight cross

908
00:49:14,520 --> 00:49:20,800
Speaker 1: country runners who were randomized to their usual diet versus

909
00:49:20,960 --> 00:49:24,839
Speaker 1: supplementing nine ounces of lean red meat a week times

910
00:49:24,840 --> 00:49:26,399
Speaker 1: eight weeks. It's not that much, but it's the best

911
00:49:26,400 --> 00:49:30,320
Speaker 1: I could find they looked at about eight hundred different

912
00:49:31,120 --> 00:49:32,560
Speaker 1: outcomes like metabolicalcy.

913
00:49:32,600 --> 00:49:34,080
Speaker 3: How you get some things to be significant.

914
00:49:34,200 --> 00:49:37,920
Speaker 1: It's an insane amount. And actually I was quite surprised

915
00:49:37,960 --> 00:49:41,560
Speaker 1: at how few of these were statistically significant, because just

916
00:49:41,600 --> 00:49:43,960
Speaker 1: my chance, they measured so many things. But I do

917
00:49:44,040 --> 00:49:48,840
Speaker 1: have one women in the control armed hamatocrit, which is

918
00:49:48,880 --> 00:49:52,080
Speaker 1: their red blood cell concentration, decreased by three point eight

919
00:49:52,160 --> 00:49:56,200
Speaker 1: percent over the eight weeks, and women who got randomized

920
00:49:56,239 --> 00:49:58,879
Speaker 1: to have the lean red meat had a fourteen point

921
00:49:58,920 --> 00:50:03,080
Speaker 1: eight percent in the harmatocrit, that's their red blood cell count.

922
00:50:03,320 --> 00:50:09,480
Speaker 1: This is biologically plausible because red meat contains iron, and women,

923
00:50:09,719 --> 00:50:14,960
Speaker 1: as a postman, certainly college age women, premenopausal women have

924
00:50:15,080 --> 00:50:21,319
Speaker 1: ongoing iron losses due to menstruation, and maybe this is

925
00:50:21,360 --> 00:50:24,920
Speaker 1: a decent source of iron to help mitigate the anemia

926
00:50:24,960 --> 00:50:25,600
Speaker 1: that can come from that.

927
00:50:26,320 --> 00:50:31,840
Speaker 2: Yes, Actually most of the serious endurance athletes that I

928
00:50:31,880 --> 00:50:35,319
Speaker 2: know do eat like do eat a reasonable amount of

929
00:50:35,320 --> 00:50:39,320
Speaker 2: red meat or eat red meat because it is very common.

930
00:50:38,960 --> 00:50:41,720
Speaker 3: To be anemic and iron.

931
00:50:41,840 --> 00:50:45,480
Speaker 2: The iron levels that are optimal for endurance performance are

932
00:50:45,719 --> 00:50:49,480
Speaker 2: typically much higher, particularly ferretin levels are much higher than

933
00:50:49,960 --> 00:50:53,160
Speaker 2: would be sort of necessary for just being a person.

934
00:50:53,360 --> 00:50:56,080
Speaker 2: And so people like to sell thement with iron, but

935
00:50:56,080 --> 00:50:59,120
Speaker 2: they also like to eat meat. But I will say

936
00:50:59,200 --> 00:51:03,280
Speaker 2: that the carnivore diet is not well suited for endurance

937
00:51:03,320 --> 00:51:07,239
Speaker 2: efforts who primarily should be consuming carbohydrate. Yeah.

938
00:51:07,640 --> 00:51:09,799
Speaker 1: Now, when you have ten pounds of stool that you're

939
00:51:09,840 --> 00:51:13,200
Speaker 1: carrying around on the run, very.

940
00:51:13,360 --> 00:51:17,360
Speaker 3: Very challenging to run. If you have eaten exclusively liver.

941
00:51:19,840 --> 00:51:24,800
Speaker 1: Iron is absorbed from my globin better then it's absorbed

942
00:51:24,800 --> 00:51:28,319
Speaker 1: from plant based sources. So like soy. I mentioned early

943
00:51:28,400 --> 00:51:30,160
Speaker 1: on that soy has a fair amount of iron in it,

944
00:51:30,200 --> 00:51:32,439
Speaker 1: but it isn't absorbed quite as well as from red meat.

945
00:51:33,040 --> 00:51:35,680
Speaker 1: That is mitigated somewhat by vitamin C intake. So if

946
00:51:35,680 --> 00:51:37,319
Speaker 1: you really do want to avoid red meat but get

947
00:51:37,320 --> 00:51:40,680
Speaker 1: your iron through a natural source, you can soy plus

948
00:51:40,680 --> 00:51:44,319
Speaker 1: something that contains vitamin C, so soy plus orange, or.

949
00:51:44,280 --> 00:51:47,879
Speaker 2: You can take a hymn adecriate iron pill which comes

950
00:51:47,920 --> 00:51:50,600
Speaker 2: to vitamin C. You can also that is that is

951
00:51:50,640 --> 00:51:54,799
Speaker 2: mostly what people are doing. Okay, very are you smashing

952
00:51:54,960 --> 00:51:56,000
Speaker 2: or passing red meat?

953
00:51:56,000 --> 00:51:56,880
Speaker 3: I'm so interested.

954
00:51:57,440 --> 00:52:02,239
Speaker 1: I am as on processed or red meat. I think

955
00:52:02,280 --> 00:52:05,959
Speaker 1: it should be avoided. I think go ahead and eat

956
00:52:06,320 --> 00:52:09,680
Speaker 1: unprocessed red meat if you enjoy it. But I wouldn't

957
00:52:09,719 --> 00:52:11,400
Speaker 1: like target. I'm not gonna smash it. I'm not going

958
00:52:11,480 --> 00:52:13,120
Speaker 1: to say, like, go out and have more of it.

959
00:52:13,160 --> 00:52:14,880
Speaker 1: I think there are plenty of other good sources of

960
00:52:14,920 --> 00:52:17,759
Speaker 1: protein that are probably better for you. So I guess

961
00:52:17,760 --> 00:52:19,880
Speaker 1: I'm a pass. Emily, smash your pass.

962
00:52:21,080 --> 00:52:24,160
Speaker 3: Yeah, I'm I'm a smash. I think that again.

963
00:52:24,280 --> 00:52:25,920
Speaker 2: I will say I don't think eating a lot of

964
00:52:25,960 --> 00:52:28,399
Speaker 2: processed food in general is very good, so let's put

965
00:52:28,440 --> 00:52:28,920
Speaker 2: that aside.

966
00:52:28,960 --> 00:52:33,440
Speaker 3: But on the red meat, I think that this can.

967
00:52:33,320 --> 00:52:36,880
Speaker 2: Be a part of a balanced diet, and if it

968
00:52:36,960 --> 00:52:40,640
Speaker 2: is something that people enjoy, they should consume it.

969
00:52:40,719 --> 00:52:43,080
Speaker 3: I'm a smash.

970
00:52:43,160 --> 00:52:45,359
Speaker 1: All right, that's it for red meat. Your mail back

971
00:52:45,440 --> 00:52:46,879
Speaker 1: Question of the week after the.

972
00:52:46,800 --> 00:52:55,640
Speaker 4: Break, Hi, Emily and Perry. I'm Genevieve calling from Hudson, Ohio,

973
00:52:55,719 --> 00:52:59,480
Speaker 4: and my question is do dath piercings really help with migraines?

974
00:53:00,160 --> 00:53:02,319
Speaker 4: Something to do with the pressure points. I would love

975
00:53:02,360 --> 00:53:04,160
Speaker 4: to get one for the looks, but I just think

976
00:53:04,160 --> 00:53:07,440
Speaker 4: it's interesting that people say they helpathetics. So thank you.

977
00:53:08,480 --> 00:53:12,000
Speaker 1: So this is an interesting question. I'm going to disclose

978
00:53:12,040 --> 00:53:15,799
Speaker 1: something here like I lack the part of your ear

979
00:53:16,280 --> 00:53:20,919
Speaker 1: that gets a daith piercing like it is. I don't

980
00:53:20,920 --> 00:53:23,680
Speaker 1: know if you can see on video here. It is

981
00:53:23,760 --> 00:53:27,319
Speaker 1: problematic because like, earbuds don't stay in my ears, like

982
00:53:27,360 --> 00:53:29,960
Speaker 1: they have nothing to tuck into, so they just kind

983
00:53:29,960 --> 00:53:33,759
Speaker 1: of fall fall out. I did look into this. It

984
00:53:33,840 --> 00:53:37,000
Speaker 1: is apparently a normal and atomical variant. So if you're

985
00:53:37,080 --> 00:53:38,759
Speaker 1: like me and your earbuds always fall out and there's

986
00:53:38,760 --> 00:53:41,600
Speaker 1: nothing to pierce in your like inner helix of your ear,

987
00:53:42,960 --> 00:53:44,840
Speaker 1: I guess we should say that, right, A dath piercing

988
00:53:44,920 --> 00:53:48,480
Speaker 1: is like that, like inside of your ear helix piercing.

989
00:53:48,960 --> 00:53:50,640
Speaker 1: Look it up. I think it looks kind of cool.

990
00:53:50,680 --> 00:53:52,200
Speaker 1: Actually you don't like it.

991
00:53:52,200 --> 00:53:53,200
Speaker 3: It seems still painful.

992
00:53:53,200 --> 00:53:56,279
Speaker 1: Oh, definitely painful. But you know, yeah, it's better to

993
00:53:56,320 --> 00:53:57,319
Speaker 1: look good than to feel good.

994
00:53:57,640 --> 00:53:58,880
Speaker 3: Not No, I don't think that is.

995
00:54:01,239 --> 00:54:07,000
Speaker 1: Anyway does help with migraines. I don't know. Uh no,

996
00:54:07,280 --> 00:54:07,880
Speaker 1: I don't think so.

997
00:54:08,800 --> 00:54:08,840
Speaker 4: No.

998
00:54:09,120 --> 00:54:11,000
Speaker 1: I mean this is out there, like people people say

999
00:54:11,160 --> 00:54:15,280
Speaker 1: and and they argue that, you know, maybe it's stimulating

1000
00:54:15,280 --> 00:54:17,919
Speaker 1: the vagus nerve or something like that, but there haven't

1001
00:54:17,960 --> 00:54:20,800
Speaker 1: been any rigorous studies. But even the sort of observational

1002
00:54:20,920 --> 00:54:23,839
Speaker 1: ones don't support any long term benefit, but.

1003
00:54:23,800 --> 00:54:26,280
Speaker 2: It could be the placebo effect, which is our favorite effect.

1004
00:54:26,520 --> 00:54:29,960
Speaker 1: Short term. Absolutely, if you believe it. Yeah, if if

1005
00:54:29,960 --> 00:54:31,960
Speaker 1: you believe you're not going to get migraines, you will

1006
00:54:32,000 --> 00:54:36,120
Speaker 1: get less migraines. But those things do tend to wane

1007
00:54:36,160 --> 00:54:38,239
Speaker 1: over time. You sort of forget that that it's there.

1008
00:54:38,840 --> 00:54:41,120
Speaker 2: Yes, the all of the evidence for this is like

1009
00:54:41,280 --> 00:54:44,000
Speaker 2: some people said, it might help.

1010
00:54:44,120 --> 00:54:48,839
Speaker 1: Yeah, yep, that's fine. But I but it does look cool,

1011
00:54:48,880 --> 00:54:51,960
Speaker 1: So go ahead and and uh and and get it

1012
00:54:51,960 --> 00:54:53,120
Speaker 1: if you can tolerate the pain.

1013
00:54:53,280 --> 00:54:55,280
Speaker 3: Do you have any weird body parts pierced?

1014
00:54:56,160 --> 00:54:59,360
Speaker 1: I have entirely normal body parts pierced. No, I'm just

1015
00:54:59,360 --> 00:55:01,759
Speaker 1: going I don't have I don't have any what's a

1016
00:55:01,800 --> 00:55:04,200
Speaker 1: weird body part? No, I don't.

1017
00:55:04,719 --> 00:55:08,120
Speaker 3: I have no piercing the unusual like piercings that you do.

1018
00:55:08,160 --> 00:55:09,120
Speaker 3: You have any tattoos?

1019
00:55:09,400 --> 00:55:11,680
Speaker 1: I don't know. I don't have tattoos. I don't have

1020
00:55:11,760 --> 00:55:14,440
Speaker 1: no tattoos. No, what about you? You don't have tattoos,

1021
00:55:14,440 --> 00:55:18,840
Speaker 1: I'm sure absolutely, I don't even have botox.

1022
00:55:18,880 --> 00:55:20,880
Speaker 3: I'm afraid of needing to forget about tattoos.

1023
00:55:20,880 --> 00:55:26,600
Speaker 2: Okay, all right, that's it for us today. Stick with

1024
00:55:26,680 --> 00:55:28,880
Speaker 2: us next week when we'll ask what's the deal with

1025
00:55:29,000 --> 00:55:35,560
Speaker 2: cupping and dry needling? Speaking of needles, Wellness Actually is

1026
00:55:35,600 --> 00:55:37,800
Speaker 2: produced in association with iHeartMedia.

1027
00:55:38,360 --> 00:55:40,320
Speaker 3: Our senior producer is Tamar Avishaik.

1028
00:55:40,719 --> 00:55:44,359
Speaker 2: Our executive producer at iHeart is Jennifer Bassett. Our theme

1029
00:55:44,440 --> 00:55:47,080
Speaker 2: music is by Eric Deutsch, and our content is for

1030
00:55:47,160 --> 00:55:48,400
Speaker 2: educational purposes only.

1031
00:55:49,120 --> 00:55:51,359
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1032
00:55:51,719 --> 00:55:54,480
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1033
00:55:54,560 --> 00:55:57,319
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1034
00:55:57,320 --> 00:56:00,120
Speaker 1: the show. You can follow us on Instagram at all

1035
00:56:00,160 --> 00:56:02,839
Speaker 1: miss actually pod and don't forget We want to hear

1036
00:56:03,000 --> 00:56:06,160
Speaker 1: from you. Head over to Wellness Actually dot fm and

1037
00:56:06,200 --> 00:56:08,680
Speaker 1: leave us a question for our mailbag or suggest a

1038
00:56:08,719 --> 00:56:09,799
Speaker 1: topic for a future show.

1039
00:56:10,600 --> 00:56:12,439
Speaker 2: We'll let the influencers have the last word.

1040
00:56:12,760 --> 00:56:15,160
Speaker 6: I've eaten nothing but meat and butter for seven years.

1041
00:56:15,239 --> 00:56:17,879
Speaker 6: My husband thinks I'm absolutely insane for this, but I'm

1042
00:56:17,920 --> 00:56:20,440
Speaker 6: obsessed with eating cold meat. The flavor and texture it

1043
00:56:20,480 --> 00:56:23,240
Speaker 6: gets better, and the cold fat turns into this buttery frosting.

1044
00:56:23,320 --> 00:56:25,799
Speaker 6: I literally cook extra steak on purpose, just so I

1045
00:56:25,800 --> 00:56:27,440
Speaker 6: can eat it straight out of the fridge. Am I

1046
00:56:27,480 --> 00:56:44,200
Speaker 6: the only one