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Speaker 1: Hello, Colorado. The States so nice. We're playing there twice,

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Speaker 1: two days in a row. Chuck, we added a second

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Speaker 1: show to our Gothic Theater tour. That's right, we're gonna

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Speaker 1: be there June seventh and June now sold out, but

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Speaker 1: one of those weird cases where you go see the

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Speaker 1: first show you were actually late buying tickets. Right. We're

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Speaker 1: also going to be in Boston April four, d C

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Speaker 1: April five. We're gonna be in St. Louis on May,

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Speaker 1: in Cleveland one, and then of course we're gonna wrap

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Speaker 1: this summer up on June at the Gothic Theater in Colorado.

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Speaker 1: So go to s Y s K live dot com

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Speaker 1: for all of your information and ticket needs. Welcome to

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Speaker 1: Stuff you Should Know from how Stuff Works dot com. Hey,

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Speaker 1: and welcome to the podcast. I'm Josh Clark. There's Charles W.

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Speaker 1: Chuck Bryant, There's guest producer Noel all of Nature, Wild

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Speaker 1: and Free. This is where you long to be. Stuff

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Speaker 1: you should know. So let's go ahead and admit that

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Speaker 1: we just did a rare retake of like the first

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Speaker 1: four minutes of the show. Yeah, and I still reused

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Speaker 1: the Madonna lyric joke. That's fine, but we have to

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Speaker 1: recreate the rest of the previous four minutes. No, I

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Speaker 1: don't think so. I think we should just kind of

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Speaker 1: let it flow. I was just I was saying to myself,

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Speaker 1: By God, that Madonna jokes getting in there. All right, Well,

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Speaker 1: maybe just a quick recap. Noel's dressed up and looks great.

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Speaker 1: He's it's because he's a snappy dresser. Uh. We mispronounced

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Speaker 1: words in the UK and got laughed at. And now

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Speaker 1: we're talking about the Framing Him heart Study. That's right,

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Speaker 1: which we h. I don't know what podcast it was on,

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Speaker 1: but years ago we called it the Farmington hard Study. Um,

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Speaker 1: every time we said it, we said Farmington's did we really? Yeah,

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Speaker 1: you don't remember that. No, I mean that definitely sounds

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Speaker 1: like us, but I don't remember it. Yeah. Yeah, that's

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Speaker 1: why I made that joke when you first came in

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Speaker 1: about the Farmington Heart Study. Okay, yeah, we said it

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Speaker 1: was years ago. It was one of our earlier couple

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Speaker 1: of years and we said the Farmingtons Hearts Study probably

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Speaker 1: twelve times. Yeah. Back in the day, the standards used

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Speaker 1: to be its head lower. Yeah, because we were low

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Speaker 1: hanging Fruit podcast. It was us Zyberglass was Ricky Gervais

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Speaker 1: and Jesse Thorn, and then Adam Curry was out there

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Speaker 1: somewhere and probably Adam Corolla. Sure, yeah no, but no

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Speaker 1: one else we had. There were eight podcasts. That was it.

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Speaker 1: That was all you had to choose from, So you

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Speaker 1: better like at least one of them. Do you know

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Speaker 1: how many there are? Now? I just saw today? Uh no,

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Speaker 1: do you like you have an actual number? Well, I

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Speaker 1: mean it's a it's an even number, so it's probably

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Speaker 1: not exact. But the latest hot pod newsletter said that

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Speaker 1: there are roughly three podcasts. Oh my god, that's nuts.

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Speaker 1: I know, man alive. That's pretty impressive, and probably only

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Speaker 1: like five of those are good. Well, we we went

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Speaker 1: from that was mean, we went from eight to three

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Speaker 1: fifty thousand and how many years? Ten? We're still hanging strong,

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Speaker 1: we are. That's great. That's what happens when you say

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Speaker 1: things like Farmington ten twelve times. He's long gone. Yeah,

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Speaker 1: he pronounced everything perfectly like guys washed up now yea,

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Speaker 1: So the reason we're talking about framing him, which, by

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Speaker 1: the way, yeah, yeah, it's gonna be tough to say

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Speaker 1: it the same way every time, but it's framing Ham

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Speaker 1: is the city of Massachusetts. I don't get the Framingham

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Speaker 1: as opposed to framing him Yeah, ok, yeah, the h

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Speaker 1: is a hard age or soft aged like, Whereas if

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Speaker 1: this were in Scotland they would just say you're right,

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Speaker 1: which is again why we were laughed at Manchester that

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Speaker 1: it's Germany sorry, right, which is landlocked. So again we're

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Speaker 1: talking about Framingham, Massachusetts, a very small town these days.

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Speaker 1: In two thousand and seventeen, I think the census, well

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Speaker 1: that the population estimate was something like seventy residents, not

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Speaker 1: a not a huge town. I think that qualifies as

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Speaker 1: a small, dinky town. Still. Yeah, but it's a suburb

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Speaker 1: of Boston, which is a huge metropolis. Sure it is, um,

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Speaker 1: but it is aside from being a suburb of Boston,

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Speaker 1: it is in its own right, uh, an internationally renowned

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Speaker 1: tiny town. Not because it's like a place where the

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Speaker 1: circus used to hang out during the winter, or because um,

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Speaker 1: they have some amazing kind of fudge. Right, Farmingham, Massachusetts

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Speaker 1: is on the map because that town back in the day,

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Speaker 1: actually two times over that town. Just I did that

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Speaker 1: they were going to present themselves as as test subjects,

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Speaker 1: study participants, for some of the most important studies ever

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Speaker 1: carried out in the history of medicine. Yeah. What one

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Speaker 1: of the largest and certainly most influential longitudinal studies ever

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Speaker 1: performed in medicine. Yeah, it's called the Farming hum Or

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Speaker 1: farming Ham Heart Study, the Framingham Oh my god, was

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Speaker 1: that an accident? Yes, Oh boy, The Framing hum Heart Study. Yeah,

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Speaker 1: which you know, we've we've had challenges, as has the

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Speaker 1: medical community in research community throughout study history, of being

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Speaker 1: frustrated with like bad studies and poor sample sizes. This

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Speaker 1: one is really set the standard. Yeah, it's it's the

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Speaker 1: gold standard for anything that has anything to do is

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Speaker 1: studying cardiovascular disease. And as we'll see it basically is

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Speaker 1: everything we you and I, just Joe Schmo walking around

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Speaker 1: on the street know about cardiovascular disease basically came out

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Speaker 1: of this study. Um. And even before that, there was

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Speaker 1: another study that the town participated in that helped lick tuberculosis,

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Speaker 1: which was which was appropriate because you know, framing framing him. Yeah,

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Speaker 1: I got it right. Is in Massachusetts, which is part

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Speaker 1: of New England, which was part of the vampire panic area, which,

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Speaker 1: as you remember, was the result of tuberculosis. So it's

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Speaker 1: it was appropriate that that little town contributed to humanity

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Speaker 1: in that way as well. Yes, so should we hop

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Speaker 1: in the way back machine? Oh yes, all right, let's

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Speaker 1: set the dial. Let's load up the flux capacitor with

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Speaker 1: Miller heavy beer and banana peals. Miller heavy. Yeah that's

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Speaker 1: what he used, nice, I think so, yeah, okay, that's

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Speaker 1: that's at the end with the more modern version right

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Speaker 1: right of the Dolorean. Yeah. I think he used some

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Speaker 1: sort of plasma waist incenterator. Yeah. Uh so, let's let's

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Speaker 1: set the dials for um, the World War two era.

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Speaker 1: We're not gonna be super specific here, No, sometimes we

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Speaker 1: rolled the dice in the way back machine. Let's see

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Speaker 1: what happened. Just say, spit us out anytime in the

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Speaker 1: nineteen forties, not in Europe or the South Pacific, that's right.

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Speaker 1: So in the nineteen UM here was a scene in

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Speaker 1: the USA, and I guess all over the world is

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Speaker 1: we did not know a lot about and all this

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Speaker 1: stuff seems so second nature now and like duh about

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Speaker 1: heart disease, But we didn't know a lot about heart

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Speaker 1: disease back then, and it was sort of just accepted

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Speaker 1: that once you reach a certain age, like, yeah, your

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Speaker 1: heart just may take you out. Nothing we can do

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Speaker 1: about it. Might as well not research it. And there's

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Speaker 1: certainly no preventative medicines for your to ensure that health. No,

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Speaker 1: certainly not like they could try to treat it or whatever.

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Speaker 1: But most of the time, once you came down with UM,

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Speaker 1: one of the cardiovascular diseases, you UM, you were a goner.

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Speaker 1: YEA of us deaths we're due to CBD, right, And

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Speaker 1: so there was a confounding factor that led to this

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Speaker 1: huge increase. There are actually two of them. One is

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Speaker 1: as far as percentages go. The cardiovascular disease deaths lurched

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Speaker 1: forward in the mid early mid twentieth century because what

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Speaker 1: used to be the big killers, which were infectious diseases

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Speaker 1: which we now consider highly treatable. They used to kill everybody, right,

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Speaker 1: And as we started to treat them thanks to the

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Speaker 1: discovery and use of penicillin and antibiotics, those things fell

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Speaker 1: into the background and and by by extend mention or

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Speaker 1: by proxy, cardiovascular disease was basically bear naked out there

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Speaker 1: statistics wise. Suddenly something that was just kind of like

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Speaker 1: a secondary problem was now that the leading cause of

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Speaker 1: death in the United States and in the West. I believe, yeah,

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Speaker 1: because I guess people were living routinely, living into their

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Speaker 1: fifties and sixties, maybe for the first time, I don't know, Yeah,

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Speaker 1: and they were saying, my god, I'm so glad I

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Speaker 1: get these extra couple of decades of eating raw steak

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Speaker 1: and smoking cigarettes at the dinner table. Grass. That is

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Speaker 1: so nasty. It's a it's a true story, though. I

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Speaker 1: saw my grandpa do it with my own eyes, smoke

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Speaker 1: at the table. Now. Actually, my grandpa was one of

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Speaker 1: the He went the other way. He was like like

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Speaker 1: subscriber number three to Prevention magazine and yeah, into like

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Speaker 1: coffee animas and all sorts of weird st He was

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Speaker 1: big time healthy guy. Is that what led your dad

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Speaker 1: to become the herbal Elviots? I think that that had

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Speaker 1: some had to have had something to do with it,

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Speaker 1: for sure. Luckily my dad didn't carry on the family

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Speaker 1: tradition of coffee animos down to me. So um alright,

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Speaker 1: So by of death or cardiovascular everyone's dying now from

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Speaker 1: their heart because they're living longer because they're not dying

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Speaker 1: of TV and their thirties and forties and then the

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Speaker 1: second big thing that happened that you teased was President Roosevelt.

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Speaker 1: Uh started to get really he got cardiovascular disease. He

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Speaker 1: started to get really high blood pressure. Uh. This was

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Speaker 1: compounded by UM. Now we understand that stress and anxiety

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Speaker 1: can compound these things, and he certainly had no shortage

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Speaker 1: of that UM as president. And you know Winston Churchill

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Speaker 1: of all people, when he says he seems to be

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Speaker 1: a very tired man. If Winston Churchill was saying that,

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Speaker 1: then you're in trouble. Yeah, because he wasn't the picture

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Speaker 1: of health. No, he certainly wasn't. But apparently f D

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Speaker 1: made him look like he was fresh as a daisy.

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Speaker 1: So FDR had high blood pressure when he went into

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Speaker 1: the White House to begin with. But by the time

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Speaker 1: rolls around right after the Yalta UM conference where they

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Speaker 1: divided Europe up between what Great Britain, the United States

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Speaker 1: in UM, Russia the Soviet Union, right. Um. He died

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Speaker 1: a couple of weeks after that, at age sixty three.

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Speaker 1: He had a stroke from hypertension, which is another word

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Speaker 1: for high blood pressure. And boy, oh boy, did he

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Speaker 1: have high blood pressure like off the charts. Chuck, Yeah,

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Speaker 1: three hundred, when when he died he had three hundred

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Speaker 1: over one. One more time, three hundred over one. So

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Speaker 1: I went and look that up. I'm like, even without

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Speaker 1: looking it up, I know that's high, but how high

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Speaker 1: is it? So? Ideal is between ninety over sixty and

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Speaker 1: one over eighty. That's how deal blood pressure. Anything over

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Speaker 1: one eighty over one twenty is what's called a hypertensive crisis.

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Speaker 1: And the chart tells you to go to your doctor

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Speaker 1: immediately for that if you have anything over one eight over.

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Speaker 1: FDR had three over one. Yeah, and I mean his

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Speaker 1: doctor said, I predict he's a very sick man. I

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Speaker 1: predicted will be dead within a few months. And he

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Speaker 1: was running the money, right Churchill's doctor. Yeah, FDR Zone

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Speaker 1: doctor was like, here, take this digitalis You'll love that.

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Speaker 1: Churchill's guy, Yeah, okay, yeah. At the y'all take conference.

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Speaker 1: I guess he just travels with I would think, so,

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Speaker 1: I thought, I mean, I would imagine all those guys

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Speaker 1: would travel with their doctors, you know, just just for fun,

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Speaker 1: like what kind of pills you got today? Yeah, and

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Speaker 1: again I'm watching The Crown now. I talked about that

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Speaker 1: in the TV h well, in the episode but when

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Speaker 1: we talked about it and John listcal As Winston, Churchill

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Speaker 1: is grow great. What he's awesome? When he and FDR

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Speaker 1: like half two part ways after the y'all to conference,

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Speaker 1: does he punch FDR in the face and say O,

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Speaker 1: FDR hasn't actually he hasn't been in it. Okay, well

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Speaker 1: look for that scene coming up. Yeah, but it's crazy.

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Speaker 1: Churchill's all over the place. He had the Gary Oldman

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Speaker 1: movie and then there were dual Churchill movies. Brian Cox

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Speaker 1: was on another one. Oh, he's in it's quality. He's great,

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Speaker 1: although his Hannibal lecture was it was fine until Anthony

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Speaker 1: Hopkins got his hands on that role. Yeah. The rare

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Speaker 1: case where the second actor totally owns the role usually

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Speaker 1: like the first actor. Will you know, just probably by

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Speaker 1: the fact that the first Although I liked Um, What's

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Speaker 1: the to Live In Diane l A's guy's name who

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Speaker 1: was the lead guy in Manhunter? William Peterson. Yeah, I

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Speaker 1: liked William Peterson's character. That's a great movie more than

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Speaker 1: Um Edward Norton's version. Oh, in Red Dragon, because Red

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Speaker 1: Dragon and Manhunter they're based on the same book. Yeah, yeah,

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Speaker 1: it's the same thing. Yeah, yeah, you're really right. William

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Speaker 1: Peterson a way better than Edward Norton in that role,

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Speaker 1: but Jodie Foster better than all of them, is closed, Yes, yeah,

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Speaker 1: all of them put together. Man. I just watched the

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Speaker 1: end of that again the other day, and oh, you're

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Speaker 1: gonna appreciate this. Uh. Emily was in the other room, um,

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Speaker 1: in the bathroom or something, I can't remember, and she

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Speaker 1: didn't know what. I turned it on and I passed

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Speaker 1: it right at the moment of the Penis Tuck Buffalo

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Speaker 1: Bill when he had his arms out in the Jesus

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Speaker 1: Christ post and Emily came in and just got in

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Speaker 1: bed and looked up and was like, oh my god,

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Speaker 1: what a great movie that was. Had everything, the perfect

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Speaker 1: race Rain did everything, had Jodie Foster, Anthony Hopkins, and

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Speaker 1: a Penis Tuck scene. We should probably take a break,

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Speaker 1: all right, We're off the rails here, are you ready? Yes?

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Speaker 1: Break starting now? Okay, Chuck. So we were talking about

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Speaker 1: Penis tux right. FDR famously did that at the Yalta conference.

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Speaker 1: Oh my god, so he you know the reason the

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Speaker 1: reason FDR's death from hypertension really factors into the stories

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Speaker 1: because it was extremely public, okay, And what FDR basically

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Speaker 1: did without using these last words, he basically said he

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Speaker 1: pointed at at modern medicine and said, I beseech you,

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Speaker 1: and then keeled over right, So modern medicine was like,

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Speaker 1: who us, we don't know what we're doing when it

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Speaker 1: comes to cardiovascular disease ease. And shortly thereafter, the framing

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Speaker 1: him heart study was born. No, you can almost coming.

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Speaker 1: The framing of heart study was born because Harry Truman

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Speaker 1: signed the National Heart Act, which is probably the thing

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Speaker 1: that he's most famous for. Its president. Yeah, and that

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Speaker 1: included and that included five thousand dollars in the form

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Speaker 1: of a grant for this study for twenty years to

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Speaker 1: cover twenty years for the study. And um, I think

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Speaker 1: initially Public Health service physician Uh Gilson or Gilkin Metters

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Speaker 1: uh said, it sounds like you messed that up, but

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Speaker 1: you didn't. I think you hit it right on the head.

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Speaker 1: Gilson Metters. It matters sounds like a weird you think

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Speaker 1: it'd be meadows or something. It sounds like you're drunk

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Speaker 1: and saying meadows. Uh. And this was the original quote,

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Speaker 1: which is actually a pretty good mission statement for the study.

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Speaker 1: Their mission was to study the express and of coronary

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Speaker 1: artery disease and a normal or unselected population, and to

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Speaker 1: determine the factors predisposing to the development of the disease

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Speaker 1: through clinical and laboratory examined long term follow up. So

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Speaker 1: there you have it. Not bad, it's got a clinical ring,

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Speaker 1: it's got a it's concise. You can dance to it. Yeah, exactly.

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Speaker 1: So this this framing Him heart study was a heart

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Speaker 1: study before it was set in framing him. And they

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Speaker 1: went to framing him for a number of reasons. One

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Speaker 1: they said, well, this is a pretty pretty standard UM

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Speaker 1: middle America, middle class UM community, at least of the

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Speaker 1: kind that we pay attention to in this day and age, right,

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Speaker 1: meaning it was almost entirely white people, which will see

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Speaker 1: as a huge criticism of this study that UM the

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Speaker 1: study directors over time have tried to work on. But um,

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Speaker 1: they said, aside from the the the complete and almost

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Speaker 1: complete and utter of UM diversity. Yes, in this study,

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Speaker 1: it's a pretty good slice of America. It's a small town,

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Speaker 1: most of the people their middle income. It's it's got

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Speaker 1: a big enough population. At the time, this is the

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Speaker 1: nineteen forties or something like twenty eight thousand people that

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Speaker 1: we could get a pretty decent, like random sample of

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Speaker 1: the population going. But the town itself is small enough.

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Speaker 1: There's only like two hospitals and in time there would

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Speaker 1: only be one hospital that we can actually easily keep

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Speaker 1: track of the people in this town. And it's not

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Speaker 1: too far from Boston University, which would win the contrast

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Speaker 1: to UM carrying out the study on behalf of the

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Speaker 1: National Heart Institute. Well, yeah, and they had also, like

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Speaker 1: you said, earlier, proven that their game for this kind

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Speaker 1: of thing by participating in that uh to what was

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Speaker 1: called tuberculosis how down or something. Ye had a name.

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Speaker 1: It did have a name. It was called the Framing

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Speaker 1: Him Tuberculosis Demonstration. There would be like watch this, no,

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Speaker 1: but it could be on a Saturday night. It was

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Speaker 1: the hold Down. So that, yeah, the whole town had

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Speaker 1: was not the whole town, but the town had gotten

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Speaker 1: behind being UM test subjects or study participants for a

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Speaker 1: whole other study about thirty years before the Heart study began.

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Speaker 1: So they were already kind of like there. Their healthcare

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Speaker 1: providers were already like aware that this stuff was going on.

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Speaker 1: And at the time, apparently healthcare providers like your general practitioner.

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Speaker 1: That was like the end all be all of your health.

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Speaker 1: That person was meant to know everything about you and

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Speaker 1: everything about disease and how to treat you. And that

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Speaker 1: was that. There weren't any longitudinal studies, There wasn't any

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Speaker 1: preventative medicine, There wasn't any national hard institute, there was

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Speaker 1: nothing like that. It all came down to your general practitioner.

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Speaker 1: So it was really important that the general practitioners and

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Speaker 1: the healthcare providers in the town of Framing Them were

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Speaker 1: on board this kind of thing, because they could very

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Speaker 1: easily have seen this as encroaching on their turf, but

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Speaker 1: they didn't. And I think the Framing Him study directors

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Speaker 1: and the people who carried this actual study out deferred

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Speaker 1: to the general practitioners in the town as far as

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Speaker 1: like giving advice from the findings and and keeping up

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Speaker 1: with the the like outside medical findings or even the

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Speaker 1: stuff they were finding from the study. They didn't directly

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Speaker 1: give it to the study participants. They gave it to

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Speaker 1: their doctors, and then the doctors would tell the study

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Speaker 1: parts participants, so they were kept in the loop. So

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Speaker 1: there was a there was a a symbiotic relationship that

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Speaker 1: was forged. Yeah. I thought that was interesting that they

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Speaker 1: just kept the research like they weren't there to offer

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Speaker 1: medical advice. They were literally just collecting research. But I

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Speaker 1: do wonder if some of the times they would say, hey, uh,

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Speaker 1: gp of Mr Donaldson, you really need to get him

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Speaker 1: in like next week. Yeah, like really yeah, like he

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Speaker 1: It's kind of like I guess how Churchill's doctor saw Roosevelt, right, Like,

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Speaker 1: I know we're not supposed to give advice, but my

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Speaker 1: advice to you is to call this guy up and say,

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Speaker 1: maybe you should come in a little earlier than next spring, right,

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Speaker 1: or go up your malpractice insurance. So we did say

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Speaker 1: that it wasn't super ethnically diverse, which um didn't phase

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Speaker 1: them too much at the time, And it really hit

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Speaker 1: home to me just how like just how white probably

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Speaker 1: every major study had been up until this point without

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Speaker 1: even like thinking it was a problem, which is being like,

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Speaker 1: I don't know, there's a great study. They're like, well,

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Speaker 1: you know, he didn't include any black people, and they

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Speaker 1: just it probably just didn't even occur to them at

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Speaker 1: the time. I don't know if it didn't occur to him.

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Speaker 1: I I think that it was mostly that's who their

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Speaker 1: clientele was. I think that that's probably who was being

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Speaker 1: studied because that's what America catered to at the time,

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Speaker 1: or who America catered to, I should say at the time.

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Speaker 1: I don't know that that much has changed these days, unfortunately,

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Speaker 1: but I think it was vastly more pronounced back then.

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Speaker 1: Well I think they I think they're way more inclusive

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Speaker 1: now and and probably have to be to get research

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Speaker 1: grants these days. I would think, oh, yeah, yeah, yeah, yeah, yeah,

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Speaker 1: for sure. No, I'm saying America as a whole being

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Speaker 1: like catering to Yeah, hear you, But that did change

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Speaker 1: in and framing him after World War Two. Apparently there

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Speaker 1: was an influx of a more diverse population after the

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Speaker 1: war at least, right, and I think by the Good

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Speaker 1: Lord was that the nineties when they added the new cohort.

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Speaker 1: Well we'll get to the cohorts, Okay, well, anyway, sure

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Speaker 1: we'll spoiler alert. They added they made the study population

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Speaker 1: more diverse. One thing that is in the credit of

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Speaker 1: the study designers is that they included women at a

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Speaker 1: about which was totally unheard of it's in any kind

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Speaker 1: of medical study at the time. Because again, not only

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Speaker 1: did they cater to almost exclusively white people in America

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Speaker 1: at the time. They catered almost exclusively to white men

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Speaker 1: at the time. Yeah, and I think also women. I

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Speaker 1: think heart disease probably still has a stigma of like, yeah,

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Speaker 1: men have heart disease, uh more than women do, right, Like,

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Speaker 1: what are you a trucker lady? How do you have

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Speaker 1: heart disease? Go back, go back home, get out of

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Speaker 1: my doctor's office. Yeah, you dummy. Yeah, which is not

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Speaker 1: the case, right, No. But the weird thing is is

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Speaker 1: what they found from the study. Just overall, they found

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Speaker 1: that the stuff that they've come up with, which we'll

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Speaker 1: talk about in a second, is really good at predicting

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Speaker 1: things for like white guys, for cardio vascular disease for

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Speaker 1: white guys. But even though women were very um clearly

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Speaker 1: represented in the study, they've actually found that the same

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Speaker 1: predictors don't work for women. So it's kind of led

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Speaker 1: to a separate study of women and how they suffer

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Speaker 1: from cardiovascular disease, because they definitely do, it's just under

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Speaker 1: different circumstances it appears than men. Yeah, it's pretty interesting.

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Speaker 1: So let's talk about the beginning of the study, right, Yeah,

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Speaker 1: So they recruited people between the ages of thirty and

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Speaker 1: fifty nine initially because that is the window where you

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Speaker 1: might develop c D d UM and they they thought

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Speaker 1: by recruiting people in this range, they would also get

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Speaker 1: a certain amount of people that are already have this

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Speaker 1: uh appearing like these symptoms appearing right. They didn't though.

390
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Speaker 1: Actually it turned out that they had to actually go

391
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Speaker 1: recruit people who had cardiovascular disease already and put them

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Speaker 1: into this study themselves, I think, because people probably that

393
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Speaker 1: maybe we're on that track, don't volunteer for studies like this. Well.

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Speaker 1: They also it wasn't a very random sample, especial at

395
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Speaker 1: first because they initially got participants through um word of

396
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Speaker 1: mouth at like civic groups and clubs. So so the

397
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Speaker 1: presence of a social network or a certain type of

398
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Speaker 1: social network, we just kind of does away with randomness

399
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Speaker 1: right out of the gate. And they ended up recruiting

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Speaker 1: other people outside of like these groups and civic civic

401
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Speaker 1: clubs and all that, who initially formed a large part

402
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Speaker 1: of the study. UM cohort to make it a little

403
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Speaker 1: more random, and I guess they were successful because it

404
00:25:32,760 --> 00:25:37,000
Speaker 1: seems like the idea of it being not very random

405
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Speaker 1: or not very representative sample of the whole um isn't

406
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Speaker 1: really discussed any longer. So I guess they took care

407
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Speaker 1: of it by the inclusion of the additional I think

408
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Speaker 1: like seven people. Yeah, so they the idea was that

409
00:25:49,160 --> 00:25:53,400
Speaker 1: you would come in every two years to give um

410
00:25:53,440 --> 00:25:57,480
Speaker 1: your medical history updated, to get updated, to have your physical,

411
00:25:58,000 --> 00:26:01,200
Speaker 1: to get you all your labs done. And they thought

412
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Speaker 1: at the time like, there's probably they were smart enough

413
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Speaker 1: to know that there's probably not one thing this causing CBD.

414
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Speaker 1: So collecting all this history from all these people over time,

415
00:26:10,720 --> 00:26:12,680
Speaker 1: and initially it was going to be twenty years, but

416
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Speaker 1: as you will learn, it's still going on today, which

417
00:26:15,320 --> 00:26:19,159
Speaker 1: is amazing. Um, they can really get a robust sampling

418
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Speaker 1: of people and time from kind of all walks of

419
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Speaker 1: life once they started being more inclusive. Yeah, and they

420
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Speaker 1: can watch the disease develop or not develop. And since

421
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Speaker 1: they do like a really they did a phenomenal baseline

422
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Speaker 1: exam and Chuck, actually, I saw and the very original

423
00:26:38,480 --> 00:26:41,440
Speaker 1: inception or conception of the study was that they were

424
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Speaker 1: going to do a baseline exam and then a second

425
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Speaker 1: follow up three to five years later and that was it.

426
00:26:46,680 --> 00:26:48,520
Speaker 1: But luckily they had the foresight to be like, no, no no, no,

427
00:26:48,680 --> 00:26:50,760
Speaker 1: let's keep this thing going and keep a rolling. Baby,

428
00:26:50,800 --> 00:26:55,359
Speaker 1: I'm feeling hot, right. So they were by doing this

429
00:26:55,480 --> 00:26:58,320
Speaker 1: baseline exam and saying, you know, do you smoke, how

430
00:26:58,359 --> 00:27:00,719
Speaker 1: much read meet you? How much do you drink? How

431
00:27:00,800 --> 00:27:04,880
Speaker 1: much exercise do you get? How often do you go parasailing? Like? Um,

432
00:27:05,200 --> 00:27:07,760
Speaker 1: like how many kids do you have? What were your

433
00:27:07,800 --> 00:27:12,840
Speaker 1: parents medical histories? Like? By getting this really great baseline exam,

434
00:27:12,880 --> 00:27:15,679
Speaker 1: they had an idea of all the different factors that

435
00:27:15,720 --> 00:27:19,560
Speaker 1: could come into play when it comes to cardiovascular disease.

436
00:27:19,760 --> 00:27:22,159
Speaker 1: And then with these follow up exams every two years,

437
00:27:22,400 --> 00:27:24,600
Speaker 1: they would find people as the as they got the

438
00:27:24,680 --> 00:27:26,520
Speaker 1: disease or didn't get the disease, and then they could

439
00:27:26,520 --> 00:27:29,000
Speaker 1: go back and look and say, well, this person has

440
00:27:29,040 --> 00:27:33,919
Speaker 1: cardiovascular disease and they smoke and they have diabetes, and uh,

441
00:27:34,080 --> 00:27:36,959
Speaker 1: their parents had a stroke. They're dead at a stroke

442
00:27:37,720 --> 00:27:40,159
Speaker 1: and they just had a stroke. So they started to

443
00:27:40,240 --> 00:27:42,720
Speaker 1: see from all of this data, it was basically like

444
00:27:42,800 --> 00:27:45,440
Speaker 1: you know how data, big data is just enormous right now.

445
00:27:46,000 --> 00:27:49,960
Speaker 1: That's basically what the Heart Institute did in Boston University

446
00:27:50,000 --> 00:27:52,119
Speaker 1: just went and set up camp in this town and

447
00:27:52,160 --> 00:27:55,119
Speaker 1: they started collecting as much data as they possibly could,

448
00:27:55,440 --> 00:27:58,480
Speaker 1: and then they set about sorting through it and publishing

449
00:27:58,520 --> 00:28:01,920
Speaker 1: papers based on the finding. Yeah, and you mentioned the

450
00:28:01,960 --> 00:28:05,160
Speaker 1: cohort earlier there, and I'm just gonna go ahead and say,

451
00:28:05,359 --> 00:28:07,800
Speaker 1: each of these cohort names is a great band name.

452
00:28:08,760 --> 00:28:12,080
Speaker 1: All of them a blanket. That's a blanket, great band name. Statement.

453
00:28:12,600 --> 00:28:14,720
Speaker 1: So the initial you said when they went out and

454
00:28:14,720 --> 00:28:18,040
Speaker 1: got another seven forty people, who and those are the

455
00:28:18,040 --> 00:28:22,280
Speaker 1: people who had the early signs of CBD. Yeah, they

456
00:28:22,280 --> 00:28:25,200
Speaker 1: were included in there. Okay, that's the Framing Him Cohort.

457
00:28:25,480 --> 00:28:28,159
Speaker 1: That's everybody. That's the first group. Okay, all of the

458
00:28:28,200 --> 00:28:31,480
Speaker 1: first group combined was the Framing Him Cohort. That's a

459
00:28:32,000 --> 00:28:35,600
Speaker 1: that's kind of an emo folkey band. Then in seventy

460
00:28:35,680 --> 00:28:39,000
Speaker 1: one they said, you know what, these people are having kids.

461
00:28:39,040 --> 00:28:41,959
Speaker 1: So what would be awesome is if we started studying

462
00:28:41,960 --> 00:28:45,840
Speaker 1: these children and their lifetimes and they were known as

463
00:28:45,880 --> 00:28:50,160
Speaker 1: the Offspring Cohort. So that's like an offspring cover band. Okay,

464
00:28:50,240 --> 00:28:53,440
Speaker 1: that's terrible. I thought, it's not bad. What what was offspring?

465
00:28:53,480 --> 00:28:56,400
Speaker 1: I don't even know. Oh, remember you got to keep

466
00:28:56,440 --> 00:29:00,160
Speaker 1: them separated. I do remember that song that was had

467
00:29:00,200 --> 00:29:02,360
Speaker 1: a couple of good songs. Yeah, and I think the guy,

468
00:29:02,520 --> 00:29:05,200
Speaker 1: if I'm not mistaken, and I'm not thinking of Milo

469
00:29:05,320 --> 00:29:09,280
Speaker 1: from the Descendants, Um, this was the guy from Offspring

470
00:29:09,600 --> 00:29:14,080
Speaker 1: went on to get like a PhD in like biochemistry

471
00:29:14,160 --> 00:29:19,000
Speaker 1: or nuclear physics or something really impressive. Interesting, Yeah, I was.

472
00:29:19,040 --> 00:29:22,440
Speaker 1: I'm so I have no idea about any of that genre,

473
00:29:22,520 --> 00:29:25,080
Speaker 1: whatever that genre is. I'm not sure what that is either.

474
00:29:25,760 --> 00:29:28,160
Speaker 1: The Offspring were kind of their own thing. Yeah, but

475
00:29:28,280 --> 00:29:31,640
Speaker 1: isn't it a part of just the whole Like what

476
00:29:31,680 --> 00:29:34,400
Speaker 1: was that tour like the Vans Warped Tour and that

477
00:29:34,520 --> 00:29:38,000
Speaker 1: all that stuff. I know nothing about any of those bands.

478
00:29:38,000 --> 00:29:40,080
Speaker 1: I'll bet they were on Warped Tour now that you

479
00:29:40,120 --> 00:29:42,680
Speaker 1: mentioned it. They were not definitely not a part of

480
00:29:44,000 --> 00:29:49,640
Speaker 1: what was Lilith Fair No, no, but ironically they did

481
00:29:49,680 --> 00:29:51,920
Speaker 1: go to a couple of dates just as audience member

482
00:29:52,200 --> 00:29:55,760
Speaker 1: probably so. Alright, So the Offspring cohort were the kids.

483
00:29:56,480 --> 00:29:59,400
Speaker 1: That was about fifty of them, and then they included

484
00:29:59,400 --> 00:30:02,600
Speaker 1: their spouse is um which was a big deal because,

485
00:30:02,680 --> 00:30:05,680
Speaker 1: like I said, adding the kids allowed to look for

486
00:30:06,120 --> 00:30:10,400
Speaker 1: hereditary functions as far as CBD goes. And then the

487
00:30:10,440 --> 00:30:14,760
Speaker 1: spouses just gave that extra layer of examination when they

488
00:30:14,760 --> 00:30:18,120
Speaker 1: weren't related, right, Yeah, so it's almost like a built

489
00:30:18,160 --> 00:30:22,000
Speaker 1: in control group as far as um looking at hereditary

490
00:30:22,040 --> 00:30:25,240
Speaker 1: stuff goes. Right. And then that was also like I've

491
00:30:25,240 --> 00:30:30,120
Speaker 1: seen it remarked on, man, my brain is a little

492
00:30:30,160 --> 00:30:35,200
Speaker 1: broken to day. But um, the having adding the kids

493
00:30:35,240 --> 00:30:38,120
Speaker 1: as a second cohort was was just a stroke of

494
00:30:38,200 --> 00:30:41,560
Speaker 1: genius because even before they had any idea that we

495
00:30:41,560 --> 00:30:45,000
Speaker 1: were going to be able to easily examine genes and

496
00:30:45,160 --> 00:30:50,040
Speaker 1: d n A, they they started building this this study

497
00:30:50,320 --> 00:30:55,360
Speaker 1: data that can be mined now for genetic stuff thanks

498
00:30:55,400 --> 00:30:59,800
Speaker 1: to these guys foresight by adding this offspring cohort. That

499
00:31:00,320 --> 00:31:05,640
Speaker 1: pretty cool. Uh. The first omni cohort first of three,

500
00:31:06,120 --> 00:31:10,320
Speaker 1: those are all three good band names. And this was

501
00:31:10,440 --> 00:31:12,960
Speaker 1: when they started getting that diversity. They said, hey, maybe

502
00:31:13,000 --> 00:31:16,800
Speaker 1: we should sort of officially include this and break this out.

503
00:31:17,240 --> 00:31:19,600
Speaker 1: So that was made up of about five hundred people

504
00:31:20,240 --> 00:31:24,520
Speaker 1: of Native American descent, African American descent, Hispanic, Indian, Asian,

505
00:31:24,520 --> 00:31:29,040
Speaker 1: and Pacific islander right first. And I guess second and

506
00:31:29,120 --> 00:31:33,920
Speaker 1: third omni cohorts, And that was that's surprising to me

507
00:31:34,000 --> 00:31:36,160
Speaker 1: that it took that long when they knew out of

508
00:31:36,200 --> 00:31:39,640
Speaker 1: the gate that it wasn't representative of America as a whole. Yeah,

509
00:31:39,680 --> 00:31:41,560
Speaker 1: I mean it's that's not to say that they didn't

510
00:31:41,600 --> 00:31:43,360
Speaker 1: have any of those people in the study, but they

511
00:31:43,360 --> 00:31:48,440
Speaker 1: officially recruited more. Isn't that right? That's my impression. Yeah, okay, Yeah,

512
00:31:48,640 --> 00:31:52,200
Speaker 1: I don't know that the original cohort was entirely white,

513
00:31:52,280 --> 00:31:56,040
Speaker 1: but I from what I understand, it was so so

514
00:31:56,240 --> 00:32:00,520
Speaker 1: majority white that it was not representative of of America

515
00:32:00,560 --> 00:32:04,480
Speaker 1: population wise. And by the way, Omni Cohort that's obviously

516
00:32:04,600 --> 00:32:08,280
Speaker 1: a E d M band that would probably tour with

517
00:32:08,360 --> 00:32:11,880
Speaker 1: like the Crystal Method or something like that. Uh. And

518
00:32:11,920 --> 00:32:16,200
Speaker 1: then finally the third generation Cohort or Gin three, which

519
00:32:16,200 --> 00:32:19,840
Speaker 1: is their album title, that started in two thousand two,

520
00:32:20,720 --> 00:32:22,480
Speaker 1: and I think they're expected to shut that one down

521
00:32:23,160 --> 00:32:26,400
Speaker 1: next year. That I thought was really weird. Why shut

522
00:32:26,440 --> 00:32:28,680
Speaker 1: any of them down? Might not be like, we're gonna

523
00:32:28,760 --> 00:32:31,520
Speaker 1: follow you to the grave, man, Yeah, we might even

524
00:32:31,600 --> 00:32:33,880
Speaker 1: dig you up in ten years after you're dead in

525
00:32:34,000 --> 00:32:36,440
Speaker 1: case we figure out something new to do with you,

526
00:32:36,560 --> 00:32:40,320
Speaker 1: you know. Yeah, And these are kids who had at

527
00:32:40,400 --> 00:32:46,240
Speaker 1: least one parent in the offspring cohort? Is that right? Okay?

528
00:32:46,760 --> 00:32:52,800
Speaker 1: And then there's another one called the offspring spousal cohort,

529
00:32:52,960 --> 00:32:56,720
Speaker 1: the new offspring spouse cohort. Right, that's a that's just

530
00:32:56,760 --> 00:33:00,960
Speaker 1: a weird one. Yeah, they're getting a little meta. Yeah, So, um,

531
00:33:01,000 --> 00:33:05,040
Speaker 1: the new offspring spouse cohort is made up of spouses who,

532
00:33:05,280 --> 00:33:10,040
Speaker 1: for whatever reasons, weren't part of the original offspring cohort

533
00:33:10,360 --> 00:33:15,040
Speaker 1: and have at least two kids in the Gen three cohort?

534
00:33:15,200 --> 00:33:18,080
Speaker 1: Is that correct? It gets a little wonky, But but

535
00:33:18,200 --> 00:33:20,200
Speaker 1: the point is is they're like adding more and more

536
00:33:20,280 --> 00:33:22,920
Speaker 1: people in the town. As the town's getting bigger and

537
00:33:23,000 --> 00:33:25,800
Speaker 1: as the town's getting more diverse, they're they're making the

538
00:33:25,800 --> 00:33:29,640
Speaker 1: study reflect this population more and more with the hopes

539
00:33:29,680 --> 00:33:31,640
Speaker 1: that it's going to reflect America more and more. And

540
00:33:31,680 --> 00:33:36,360
Speaker 1: they again this the study designers and and directors have

541
00:33:36,480 --> 00:33:39,000
Speaker 1: always known that this isn't just like a perfect snapshot

542
00:33:39,440 --> 00:33:43,800
Speaker 1: of America. Um, there's always been criticisms of it, and UM,

543
00:33:43,840 --> 00:33:45,120
Speaker 1: I don't know, you want to take a break before

544
00:33:45,160 --> 00:33:47,680
Speaker 1: we get into those, Okay, we will do that right

545
00:33:47,720 --> 00:34:18,880
Speaker 1: after this. Okay, so I said, we're going to get

546
00:34:18,880 --> 00:34:21,799
Speaker 1: into criticisms, but first we should probably talk about some

547
00:34:21,880 --> 00:34:25,240
Speaker 1: of the successes, right yeah. And like I said earlier

548
00:34:25,280 --> 00:34:27,640
Speaker 1: that so much of what we learned from this UM

549
00:34:27,640 --> 00:34:31,760
Speaker 1: today seems just so brainless. But it's important to remember

550
00:34:31,840 --> 00:34:36,279
Speaker 1: that before this, I mean, you still even though you think, like, yeah,

551
00:34:36,320 --> 00:34:38,600
Speaker 1: you smoke cigarettes, you're going to increase your risk of

552
00:34:38,640 --> 00:34:41,680
Speaker 1: heart disease. It seems like such such a second nature

553
00:34:41,719 --> 00:34:45,000
Speaker 1: thing to know now, But until you have actual scientific proof,

554
00:34:45,920 --> 00:34:48,799
Speaker 1: you can't say something like that. And this study gave

555
00:34:48,880 --> 00:34:50,520
Speaker 1: us a lot of these things that we take for

556
00:34:50,560 --> 00:34:54,520
Speaker 1: granted now as obvious and proved them came out of

557
00:34:54,560 --> 00:34:57,759
Speaker 1: this study in particular, And and cigarettes was a big one.

558
00:34:58,520 --> 00:35:01,040
Speaker 1: I read in this article. I can't remember where it

559
00:35:01,080 --> 00:35:03,839
Speaker 1: came from, Chuck, I sent to you where um they

560
00:35:03,840 --> 00:35:07,640
Speaker 1: were talking about how one of the reasons why cardiovascular

561
00:35:07,680 --> 00:35:11,680
Speaker 1: disease spiked in the forties was because they were giving

562
00:35:11,719 --> 00:35:13,920
Speaker 1: free cigarettes out to all of the g I s

563
00:35:14,040 --> 00:35:16,440
Speaker 1: during World War Two. They had like an endless supply

564
00:35:16,520 --> 00:35:19,359
Speaker 1: of free cigarettes over there, and that they think that

565
00:35:19,719 --> 00:35:23,080
Speaker 1: directly led to a rise in the in depths from

566
00:35:23,120 --> 00:35:27,560
Speaker 1: cardiovascular disease. So, but no one knew for sure. Some

567
00:35:27,600 --> 00:35:30,800
Speaker 1: people probably suspected. Every once in a while a newspaper

568
00:35:30,800 --> 00:35:33,120
Speaker 1: would quote them. They would be called a crack potter

569
00:35:33,200 --> 00:35:36,200
Speaker 1: and by somebody else in the in the article, and

570
00:35:36,239 --> 00:35:39,279
Speaker 1: that would be that. Right. So these guys went to

571
00:35:39,320 --> 00:35:44,720
Speaker 1: town like establishing a link between smoking and cardiovascular disease.

572
00:35:44,920 --> 00:35:48,360
Speaker 1: They tried very very hard to um connect diet in

573
00:35:48,400 --> 00:35:52,200
Speaker 1: cardiovascular disease and had very mixed results, so much so

574
00:35:52,280 --> 00:35:55,200
Speaker 1: that some of their early work in that realm was

575
00:35:55,280 --> 00:35:58,600
Speaker 1: just went unpublished. For the most part, they just kind

576
00:35:58,600 --> 00:36:01,080
Speaker 1: of were like, uh, we'd don't understand this, so we're

577
00:36:01,080 --> 00:36:03,560
Speaker 1: not gonna include this. But some of the other ones

578
00:36:03,600 --> 00:36:07,719
Speaker 1: were stroke. Like, um, if you have cardiovascular disease, are

579
00:36:07,719 --> 00:36:10,560
Speaker 1: at a much higher risk for stroke. Nobody knew that

580
00:36:10,640 --> 00:36:14,120
Speaker 1: conclusively before. Yeah, they confirmed that things like cholesterol and

581
00:36:14,120 --> 00:36:20,200
Speaker 1: blood pressure abnormalities increase your risk. UM, irregular heartbeat, atrial

582
00:36:20,520 --> 00:36:27,000
Speaker 1: fibrillation increases your risk five times menopause. Yeah, that was

583
00:36:27,040 --> 00:36:29,680
Speaker 1: a that was a big one, super big one. Um,

584
00:36:29,840 --> 00:36:33,360
Speaker 1: here's here's one, Like, seriously, this was figured out in

585
00:36:33,400 --> 00:36:37,600
Speaker 1: this study that um, physical activity decreases your risk for

586
00:36:37,640 --> 00:36:43,040
Speaker 1: cardiovascular disease, while lower physical activity and obesity increases your risk.

587
00:36:43,800 --> 00:36:45,920
Speaker 1: Like again, this is stuff that we're like, of course,

588
00:36:46,200 --> 00:36:49,240
Speaker 1: who doesn't know that, well, American in the world didn't

589
00:36:49,239 --> 00:36:54,720
Speaker 1: know that until Framing a Heart Study actually published its results. Yeah,

590
00:36:54,760 --> 00:36:57,840
Speaker 1: here's one that. Um, if you're in your forties and

591
00:36:57,920 --> 00:37:00,080
Speaker 1: you go to get a physical, there's a pretty to

592
00:37:00,120 --> 00:37:03,000
Speaker 1: get a chance. At some point after your labs, your

593
00:37:03,040 --> 00:37:06,480
Speaker 1: doctor will talk to you about your f R S score.

594
00:37:06,520 --> 00:37:09,759
Speaker 1: You're Framing Him risk score. It is still widely used

595
00:37:09,800 --> 00:37:12,760
Speaker 1: today as the standard. And that is the very sad

596
00:37:12,920 --> 00:37:17,080
Speaker 1: moment where your doctor says you have this much of

597
00:37:17,120 --> 00:37:22,200
Speaker 1: a percentage risk of of developing heart disease within ten

598
00:37:22,280 --> 00:37:25,920
Speaker 1: years from this state. They tell you have a hundred

599
00:37:25,920 --> 00:37:28,520
Speaker 1: and three risk. You say, well, what can it go

600
00:37:28,600 --> 00:37:31,839
Speaker 1: up to and they say a hundred Yeah, that's not good. Um,

601
00:37:32,000 --> 00:37:35,360
Speaker 1: so there's the Framing HUM risk score is based on

602
00:37:35,440 --> 00:37:38,439
Speaker 1: a bunch of different risk factors. And by the way,

603
00:37:38,480 --> 00:37:41,279
Speaker 1: the term risk factor was coined from the Framing Him

604
00:37:41,560 --> 00:37:45,719
Speaker 1: Heart study, So that's another thing it gave to the world. Uh.

605
00:37:45,760 --> 00:37:48,920
Speaker 1: Your risk factors are based on your age, your gender,

606
00:37:49,520 --> 00:37:54,080
Speaker 1: total cholesterol, HDL cholesterol, whether you have diabetes or not,

607
00:37:54,120 --> 00:37:57,160
Speaker 1: whether you smoke or not, and your systolic blood pressure.

608
00:37:57,840 --> 00:38:00,000
Speaker 1: You put all this together, each of those gets a score.

609
00:38:00,480 --> 00:38:04,239
Speaker 1: You can come up with a really really good indicator

610
00:38:04,600 --> 00:38:06,760
Speaker 1: of whether you're going to come down with a cardio

611
00:38:06,800 --> 00:38:10,960
Speaker 1: of vascular disease in ten years. If you're a white guy, um,

612
00:38:11,000 --> 00:38:13,799
Speaker 1: to a lesser extent, if you're an African American guy,

613
00:38:14,280 --> 00:38:17,440
Speaker 1: to a much lesser extent, if you're a woman of

614
00:38:17,800 --> 00:38:20,640
Speaker 1: I think any um ethnicity. Do you get a piscol

615
00:38:20,680 --> 00:38:24,120
Speaker 1: every year? I try to. It's been Oh it hasn't

616
00:38:24,120 --> 00:38:26,160
Speaker 1: been a year yet. I'm just under a year right now,

617
00:38:26,160 --> 00:38:28,319
Speaker 1: but I need to find a new doctor. Are you.

618
00:38:28,480 --> 00:38:32,960
Speaker 1: Uh how's your cholesterol? It's great man? My family dude?

619
00:38:33,680 --> 00:38:36,480
Speaker 1: Oh yeah, is that it runs high? Well? I mean

620
00:38:36,560 --> 00:38:38,880
Speaker 1: I certainly do don't do myself any favors with my

621
00:38:38,920 --> 00:38:41,640
Speaker 1: weight in my diet, but me, my brother, and my

622
00:38:41,719 --> 00:38:46,279
Speaker 1: sister are all on cholesterol medication. Oh is that right? Statens?

623
00:38:46,360 --> 00:38:48,680
Speaker 1: Is that what it's called? And and my brother like

624
00:38:48,880 --> 00:38:51,680
Speaker 1: is in great shape, and so's my sister. So it's

625
00:38:51,760 --> 00:38:55,880
Speaker 1: ah yeah, I mean it's just a totally Bryant family tradition,

626
00:38:56,080 --> 00:39:00,360
Speaker 1: just naturally high cholesterol. Huh. Well, I mean my dementia

627
00:39:00,440 --> 00:39:03,000
Speaker 1: runs in my family, so I'm toast one way or another.

628
00:39:03,160 --> 00:39:05,200
Speaker 1: Oh yeah, I mean it's basically you look at your

629
00:39:05,239 --> 00:39:09,920
Speaker 1: family history and spin the big wheel. What's gonna kill me? Right,

630
00:39:10,040 --> 00:39:13,560
Speaker 1: It's like common medical science, finally care for mine. Let's

631
00:39:13,560 --> 00:39:16,399
Speaker 1: go with that one first. Well, thank god for statins there,

632
00:39:16,440 --> 00:39:20,520
Speaker 1: you know now my cholesterol is great. So I since

633
00:39:20,600 --> 00:39:23,200
Speaker 1: I went last went to the doctor, I've begun to

634
00:39:23,280 --> 00:39:26,719
Speaker 1: introduce butter into my diet way more than I ever

635
00:39:26,760 --> 00:39:30,239
Speaker 1: had before. But I love yes, of course, Um like

636
00:39:30,280 --> 00:39:32,080
Speaker 1: a really if it has like a picture of an

637
00:39:32,120 --> 00:39:35,200
Speaker 1: Amish person on the cover of the package, go with

638
00:39:35,320 --> 00:39:38,680
Speaker 1: that butter butter. Yeah, And I actually I read a

639
00:39:38,719 --> 00:39:42,880
Speaker 1: taste test on maybe rancor or something like that of

640
00:39:43,000 --> 00:39:48,000
Speaker 1: butters and apparently the ones that are like a pound

641
00:39:48,560 --> 00:39:51,600
Speaker 1: really don't taste much better than like Carrie gold that

642
00:39:51,680 --> 00:39:54,640
Speaker 1: you get at the grocery store just about any grocery store.

643
00:39:55,040 --> 00:39:57,760
Speaker 1: So I found like that's good. I'm not really missing

644
00:39:57,760 --> 00:40:00,440
Speaker 1: out on anything. Um, I'll just eat more cheese butter

645
00:40:01,239 --> 00:40:03,160
Speaker 1: and just like a little bit of butter on some

646
00:40:03,239 --> 00:40:07,000
Speaker 1: bread is a really like delightful little treat um ten

647
00:40:07,080 --> 00:40:10,640
Speaker 1: times a day. So I'm actually really interested to see

648
00:40:10,680 --> 00:40:13,040
Speaker 1: what my cholesterol is like this year. I'm I'm basically

649
00:40:13,080 --> 00:40:15,480
Speaker 1: just performing a test on myself right now. Well, and

650
00:40:15,480 --> 00:40:18,479
Speaker 1: they've learned so much in the past like ten years

651
00:40:18,560 --> 00:40:22,200
Speaker 1: or so about good fats and bad fats and low

652
00:40:22,239 --> 00:40:25,480
Speaker 1: fat foods really not being all they're cracked up to be,

653
00:40:25,480 --> 00:40:27,520
Speaker 1: because then they're packed with other things that are bad

654
00:40:27,560 --> 00:40:30,759
Speaker 1: for you, especially high freak toose coins from Yeah it's good,

655
00:40:30,840 --> 00:40:34,640
Speaker 1: we go with a good uh local butter called banner butter.

656
00:40:35,320 --> 00:40:38,799
Speaker 1: Mm hmm, it's it's good and you know, who knows

657
00:40:38,800 --> 00:40:41,000
Speaker 1: if it tastes a better, but it's it's locally made,

658
00:40:41,040 --> 00:40:43,120
Speaker 1: so that's always nice. Is it made from those doomed

659
00:40:43,160 --> 00:40:45,640
Speaker 1: goats across the street from you know, we just fed

660
00:40:45,640 --> 00:40:48,000
Speaker 1: them yesterday though, did you did you go? I'm so

661
00:40:48,000 --> 00:40:50,319
Speaker 1: sorry for what's going to happen to you know we.

662
00:40:50,400 --> 00:40:52,960
Speaker 1: I don't think they're doomed. I think they are are

663
00:40:53,040 --> 00:40:57,880
Speaker 1: being raised again and sent to Jamaica. Not for food

664
00:40:58,680 --> 00:41:05,239
Speaker 1: for what for for milk and cheese to raise people's spirits. Well,

665
00:41:05,239 --> 00:41:08,959
Speaker 1: they certainly do that, those goats playing. But yeah, it's

666
00:41:09,000 --> 00:41:12,880
Speaker 1: not like every goat has to be eaten to have worth. No,

667
00:41:12,960 --> 00:41:20,520
Speaker 1: I agree. I'm just saying they're also milked in there cheese.

668
00:41:21,280 --> 00:41:23,440
Speaker 1: We save all our Emily is a juicing theme now.

669
00:41:23,480 --> 00:41:27,120
Speaker 1: So we have a lot of um green scraps now,

670
00:41:27,760 --> 00:41:29,839
Speaker 1: so we just save them all and then about two

671
00:41:29,880 --> 00:41:32,319
Speaker 1: times a week we'll we'll take the kid over there

672
00:41:32,320 --> 00:41:34,600
Speaker 1: and feed the goats and it's pretty fun. They bray

673
00:41:34,640 --> 00:41:36,600
Speaker 1: at us now when we leave our house. Oh yeah,

674
00:41:36,640 --> 00:41:39,319
Speaker 1: they're like, can't you bring that over here? Pretty boomed? Yeah,

675
00:41:39,360 --> 00:41:42,000
Speaker 1: they love it. So you guys have green scraps. Let

676
00:41:42,000 --> 00:41:43,520
Speaker 1: me give you a little piece of advice to pass

677
00:41:43,520 --> 00:41:46,680
Speaker 1: along to Emily. One word, but I'm going to pronounce

678
00:41:46,680 --> 00:41:50,960
Speaker 1: it like to Vita mix. Oh dude, we've had a

679
00:41:51,200 --> 00:41:53,399
Speaker 1: a mix for like ten years. Is that what you use? Yeah,

680
00:41:53,640 --> 00:41:55,640
Speaker 1: you should have scraps. You gotta throw all that stuff

681
00:41:55,680 --> 00:41:59,480
Speaker 1: in there so you get the fiber too. Now we

682
00:41:59,480 --> 00:42:01,760
Speaker 1: we don't throw like the butt end of the celery

683
00:42:01,800 --> 00:42:04,200
Speaker 1: stalk in there. Okay, all right, stuff like that. I

684
00:42:04,239 --> 00:42:07,040
Speaker 1: got to because you know there's like there's like juicers

685
00:42:07,120 --> 00:42:10,920
Speaker 1: that just extract the juice and leave all of the fiber.

686
00:42:11,280 --> 00:42:12,920
Speaker 1: I thought that's what you were talking about. No, no no, no,

687
00:42:13,000 --> 00:42:14,839
Speaker 1: we well we do two things. We have the Vita

688
00:42:14,880 --> 00:42:18,120
Speaker 1: mix for a lot of the green smoothies and stuff.

689
00:42:18,600 --> 00:42:21,000
Speaker 1: But then we are also juicing some of the stuff

690
00:42:21,600 --> 00:42:25,360
Speaker 1: and uh, we'll give those the juice scraps to the goats.

691
00:42:25,360 --> 00:42:28,080
Speaker 1: But we we do both like every morning now with

692
00:42:28,200 --> 00:42:31,880
Speaker 1: some sort of green juice and smoothie. Okay, so you

693
00:42:31,920 --> 00:42:35,000
Speaker 1: do have like a juice or juicer than two? Right? Yeah? Yeah, okay,

694
00:42:35,160 --> 00:42:37,360
Speaker 1: I have another piece of advice for you. You're gonna

695
00:42:37,360 --> 00:42:41,040
Speaker 1: love this one. Get yourself some good mescal it's so

696
00:42:41,080 --> 00:42:45,479
Speaker 1: hard to find these days. Juice, some cucumber, yeah, you're

697
00:42:45,560 --> 00:42:48,880
Speaker 1: doing that. A little bit of lime juice which you

698
00:42:48,920 --> 00:42:51,279
Speaker 1: don't need to run through the juicer, and then some

699
00:42:51,320 --> 00:42:56,280
Speaker 1: sort of sweetener and thank me later. And and then mescal. Yeah,

700
00:42:56,440 --> 00:42:59,200
Speaker 1: oh yeah, much as you like, because then we've been

701
00:42:59,280 --> 00:43:03,279
Speaker 1: drinking the vodka. Uh with her fresh juices fail. Yeah,

702
00:43:03,280 --> 00:43:05,200
Speaker 1: that goes really well with the two. This is this

703
00:43:05,280 --> 00:43:07,640
Speaker 1: is a different, This is something different. You know. The

704
00:43:07,680 --> 00:43:11,520
Speaker 1: mess cow really stands out with the cucumber, makes it pop. Yeah,

705
00:43:11,800 --> 00:43:15,000
Speaker 1: give it a shot. All right, are we gonna let's

706
00:43:15,000 --> 00:43:17,239
Speaker 1: bring this homeless up torturing all these poor people who

707
00:43:17,280 --> 00:43:19,319
Speaker 1: are still listening. I think we got off track with

708
00:43:19,360 --> 00:43:25,080
Speaker 1: butter and goats, so f rs is what we were

709
00:43:25,080 --> 00:43:28,880
Speaker 1: talking about. Oh, here's another one. For you. Uh, they've

710
00:43:28,920 --> 00:43:32,040
Speaker 1: just some little ancillary things they've learned over time, because

711
00:43:32,080 --> 00:43:34,920
Speaker 1: it's not just about CBD. They've learned about things like

712
00:43:35,560 --> 00:43:39,719
Speaker 1: um depression and stress and anxiety, sleep apnea for one,

713
00:43:40,040 --> 00:43:43,279
Speaker 1: increasing a risk of stroke. And then they gave a

714
00:43:43,360 --> 00:43:47,960
Speaker 1: really uh ingenious thing when they just said, hey, we've

715
00:43:48,000 --> 00:43:50,920
Speaker 1: got all these people over this big chunk of time,

716
00:43:51,480 --> 00:43:54,239
Speaker 1: so why don't we start seeing if people will give

717
00:43:54,280 --> 00:43:57,160
Speaker 1: us a little bit of brain matter upon death and

718
00:43:57,200 --> 00:44:01,040
Speaker 1: we can start looking into things like Alzheimer's and dementia. Yeah,

719
00:44:01,440 --> 00:44:03,800
Speaker 1: and they've actually found recently, at least in the framing

720
00:44:03,800 --> 00:44:07,200
Speaker 1: and population, dementia's going down, which hopefully means that it's

721
00:44:07,239 --> 00:44:10,000
Speaker 1: going down in the larger population as well. But yeah,

722
00:44:10,040 --> 00:44:12,160
Speaker 1: they have all this study data and they say, well,

723
00:44:12,200 --> 00:44:15,239
Speaker 1: let's start mining it for other diseases as well. And

724
00:44:15,400 --> 00:44:19,000
Speaker 1: it's becoming not just a gold standard for cardiovascular disease,

725
00:44:19,040 --> 00:44:23,680
Speaker 1: but for like other neurological diseases as well, and eventually,

726
00:44:23,960 --> 00:44:27,719
Speaker 1: almost certainly it will become the gold standard for genetic

727
00:44:27,760 --> 00:44:32,120
Speaker 1: investigations into diseases as well. Yeah, And like we've been

728
00:44:32,120 --> 00:44:35,000
Speaker 1: talking about the lack of diversity over the like, basically

729
00:44:35,040 --> 00:44:38,279
Speaker 1: this is really good results for white dudes. They have

730
00:44:38,400 --> 00:44:42,560
Speaker 1: since over the years included other calculators for minority groups.

731
00:44:42,600 --> 00:44:46,400
Speaker 1: For women, Uh, the f risk calculator is for British

732
00:44:46,440 --> 00:44:51,600
Speaker 1: minority groups. The Reynolds Risk score has been developed for women. Uh.

733
00:44:51,680 --> 00:44:54,120
Speaker 1: And I think a couple of others too, where they've

734
00:44:54,160 --> 00:44:57,040
Speaker 1: tried to take all this data and then tailor it

735
00:44:57,200 --> 00:45:01,279
Speaker 1: to a specific group. They've also found that people who

736
00:45:01,320 --> 00:45:05,120
Speaker 1: go on vacation to have lower incidences of cardiovascular disease.

737
00:45:05,160 --> 00:45:11,319
Speaker 1: So remember to vacate at least twice a year. Uh.

738
00:45:11,400 --> 00:45:13,359
Speaker 1: What else? Oh that thing about dating people who look

739
00:45:13,400 --> 00:45:16,840
Speaker 1: like you? That was interesting. Yeah, I guess they saw

740
00:45:16,880 --> 00:45:20,200
Speaker 1: that in the initial cohort, a lot of people, a

741
00:45:20,200 --> 00:45:23,200
Speaker 1: lot of married couples looked alike. And they think that

742
00:45:23,239 --> 00:45:27,800
Speaker 1: people were preferentially seeking out people about their height, their weight, um,

743
00:45:27,840 --> 00:45:30,280
Speaker 1: maybe their hair color, who knows, but that that's largely

744
00:45:30,320 --> 00:45:34,879
Speaker 1: gone away in the second and third cohorts. I also

745
00:45:34,920 --> 00:45:37,600
Speaker 1: read an article that UM said that they found that

746
00:45:37,680 --> 00:45:41,160
Speaker 1: human evolution is still going on. They're noticing that each

747
00:45:41,200 --> 00:45:45,840
Speaker 1: generation of women is slightly shorter, slightly pump plumper, and

748
00:45:45,840 --> 00:45:48,120
Speaker 1: I'm talking like a tenth of an inch shorter and

749
00:45:48,239 --> 00:45:51,239
Speaker 1: something like a half of a pound heavier, but that

750
00:45:51,280 --> 00:45:56,680
Speaker 1: they this is traditionally tied to UM being able to

751
00:45:56,920 --> 00:46:02,239
Speaker 1: easy more easily UM have live births, another way to

752
00:46:02,239 --> 00:46:06,520
Speaker 1: put his having kids, because a lot easier to have kids, right,

753
00:46:07,280 --> 00:46:11,960
Speaker 1: is wrong with me? Um? So they think that this

754
00:46:12,040 --> 00:46:15,399
Speaker 1: is like as they're seeing in in framing evolution still

755
00:46:15,440 --> 00:46:17,800
Speaker 1: in place, which very much contradicts what a lot of

756
00:46:17,880 --> 00:46:20,719
Speaker 1: people have long said, which is humans took ourselves out

757
00:46:20,760 --> 00:46:23,480
Speaker 1: of evolution a while back when we started intervening in

758
00:46:23,560 --> 00:46:26,640
Speaker 1: medicine and things like that. So that just the this

759
00:46:27,239 --> 00:46:31,840
Speaker 1: cool pictures of humanity that this is provided. It's pretty sweet,

760
00:46:32,160 --> 00:46:35,440
Speaker 1: pretty pretty great study. Actually it is, and hopefully this

761
00:46:35,440 --> 00:46:38,360
Speaker 1: will be I know they had a little trouble getting

762
00:46:38,400 --> 00:46:40,960
Speaker 1: extended funding at one point, and they had some private

763
00:46:41,239 --> 00:46:44,839
Speaker 1: institutions that stepped up, some kind of unusual ones like

764
00:46:45,160 --> 00:46:47,880
Speaker 1: Oscar Meyer, and I believe that one of the cigarette companies, right,

765
00:46:48,600 --> 00:46:53,680
Speaker 1: and then Nixon eventually he got out the checkbook and

766
00:46:53,680 --> 00:46:56,520
Speaker 1: wrote him a big fat check, probably probably the thing

767
00:46:56,600 --> 00:46:59,239
Speaker 1: that he's most known for his president too, I think,

768
00:46:59,320 --> 00:47:02,239
Speaker 1: so continuing the framing Him heart study, I read that

769
00:47:02,320 --> 00:47:05,160
Speaker 1: he got out the checkbook or or twisted the arm

770
00:47:05,160 --> 00:47:08,799
Speaker 1: of the National Heart Institute. Um, because one of the

771
00:47:08,880 --> 00:47:13,440
Speaker 1: early champions of the Heart Study was Nixon's personal doctor,

772
00:47:13,480 --> 00:47:16,239
Speaker 1: and that's how it all went down. He's like, turn

773
00:47:16,280 --> 00:47:18,840
Speaker 1: your head and cough and give us fifty million dollars.

774
00:47:20,760 --> 00:47:23,799
Speaker 1: You got anything else? Nope, Well, we could probably just

775
00:47:23,840 --> 00:47:26,399
Speaker 1: talk about framing him for days, but we're gonna stop now.

776
00:47:26,480 --> 00:47:28,719
Speaker 1: I would urge you to go read I'm not even

777
00:47:28,760 --> 00:47:31,200
Speaker 1: sure when it was written, but a CBS Sunday Morning

778
00:47:31,320 --> 00:47:35,000
Speaker 1: article from maybe like the early two thousand's about framing

779
00:47:35,080 --> 00:47:36,839
Speaker 1: him and the Heart Study, and it really just kind

780
00:47:36,840 --> 00:47:38,719
Speaker 1: of gives you a picture of the people there. And

781
00:47:38,760 --> 00:47:40,640
Speaker 1: then I also saw when that was critical of it

782
00:47:40,680 --> 00:47:44,080
Speaker 1: that was pretty interesting, called framing him follies on something

783
00:47:44,080 --> 00:47:47,480
Speaker 1: called protein power dot com. Um, just go read them both.

784
00:47:47,520 --> 00:47:50,560
Speaker 1: You'll enjoy it. Uh. And since I said you'll enjoy it,

785
00:47:50,560 --> 00:47:55,640
Speaker 1: it's time for listener, ma'am. I'm gonna call this follow

786
00:47:55,719 --> 00:47:59,759
Speaker 1: up on the beach near the Hearst Castles a couple

787
00:47:59,800 --> 00:48:01,680
Speaker 1: of week to go. We talked about the when I

788
00:48:01,719 --> 00:48:04,240
Speaker 1: went and I thought I didn't think there are Walrus's.

789
00:48:04,280 --> 00:48:06,319
Speaker 1: I just couldn't remember what they were, and they are,

790
00:48:06,360 --> 00:48:09,359
Speaker 1: in fact elephant seals. I said they were sea lions.

791
00:48:09,400 --> 00:48:11,760
Speaker 1: That was wrong. Oh that's right, you did say sea lions.

792
00:48:12,160 --> 00:48:14,279
Speaker 1: Well that's right. Um. Hey, guys, listen to the show

793
00:48:14,320 --> 00:48:18,240
Speaker 1: on Walrus's and Chuck referred to the beach near Herst Castle.

794
00:48:18,560 --> 00:48:24,000
Speaker 1: They call it Piedras Blanca's Elephant Seal Rock Rookery. I

795
00:48:24,000 --> 00:48:25,600
Speaker 1: think it's funny that you had mentioned that because for

796
00:48:25,600 --> 00:48:28,120
Speaker 1: our honeymoon last June, my husband and I stayed in

797
00:48:28,680 --> 00:48:32,480
Speaker 1: Oceano for a week near Pismo Beach, and one of

798
00:48:32,480 --> 00:48:33,960
Speaker 1: our activities for a day was to go to Hearst

799
00:48:34,000 --> 00:48:37,120
Speaker 1: Castle and Elephant Seal Beach. Of course, hers Castle was amazing.

800
00:48:37,480 --> 00:48:39,040
Speaker 1: I still haven't been in there. I need to check

801
00:48:39,040 --> 00:48:42,319
Speaker 1: that out. Uh. You know that one party scene at

802
00:48:42,640 --> 00:48:45,880
Speaker 1: in Billy Madison was filmed at Hurst Castle. Yeah, I

803
00:48:45,880 --> 00:48:50,120
Speaker 1: never saw that. Still. Um. Getting to see the architectural

804
00:48:50,239 --> 00:48:53,160
Speaker 1: history and artifacts that reside there were great. But the beach, unfortunately,

805
00:48:53,200 --> 00:48:55,520
Speaker 1: on that particularly, was pretty quiet. I think it was

806
00:48:55,560 --> 00:48:57,160
Speaker 1: a nap time by the time we got there, because

807
00:48:57,200 --> 00:49:00,919
Speaker 1: most of them are sleeping or adjusting and going back

808
00:49:00,960 --> 00:49:03,879
Speaker 1: to sleep. Well, it's still fun to see him. It's

809
00:49:03,880 --> 00:49:06,759
Speaker 1: not like they're out there with with the beach ball.

810
00:49:06,880 --> 00:49:10,200
Speaker 1: Like in cartoons, it's fun. It's fun to be overpowered

811
00:49:10,239 --> 00:49:13,880
Speaker 1: by their stench when you're down wind of that massive elephant.

812
00:49:13,680 --> 00:49:16,360
Speaker 1: That uh. There were a few males that started an altercation,

813
00:49:16,360 --> 00:49:18,440
Speaker 1: but that ended pretty quickly and wasn't all that noisy.

814
00:49:18,840 --> 00:49:20,840
Speaker 1: I think the most interesting thing on that day, besides

815
00:49:20,840 --> 00:49:23,040
Speaker 1: seeing them up close, he was watching them sleep in

816
00:49:23,080 --> 00:49:25,120
Speaker 1: the water. First, I got a little nervous because I

817
00:49:25,120 --> 00:49:28,400
Speaker 1: wasn't sure if they were alive, but after several minutes

818
00:49:28,400 --> 00:49:31,040
Speaker 1: of watching one of them, it moved once the waves

819
00:49:31,040 --> 00:49:34,600
Speaker 1: pushed it close enough to the rocks. However, if you

820
00:49:34,640 --> 00:49:36,440
Speaker 1: do suggest people to go there, please tell them to

821
00:49:36,440 --> 00:49:39,000
Speaker 1: be aware there are no feeding of the squirrel signs.

822
00:49:39,680 --> 00:49:42,840
Speaker 1: There was a group of preteens that didn't regard the

823
00:49:42,880 --> 00:49:45,480
Speaker 1: sign and literally got chased by a big, fat squirrel.

824
00:49:45,920 --> 00:49:48,879
Speaker 1: It was hilarious to watch, but a little scary. Thanks

825
00:49:48,880 --> 00:49:50,920
Speaker 1: for the show. I hope you're doing well. Keep up

826
00:49:50,960 --> 00:49:54,920
Speaker 1: the work. And that is Morrigan body and Morgan actually

827
00:49:54,960 --> 00:49:57,319
Speaker 1: just emailed back when I told her she was going

828
00:49:57,360 --> 00:50:01,800
Speaker 1: to be on and said, o MG, no way for exclamations.

829
00:50:02,719 --> 00:50:07,640
Speaker 1: Thanks smiley face emoji, and then she inserted I guess

830
00:50:07,680 --> 00:50:14,520
Speaker 1: her or previous surname Morgan Meyer's body. Okay, way to go, Morgan.

831
00:50:14,719 --> 00:50:17,919
Speaker 1: Thanks for the emojis and the exclamation points to all

832
00:50:17,920 --> 00:50:21,080
Speaker 1: for it. If you have a story you want to

833
00:50:21,160 --> 00:50:23,839
Speaker 1: straighten us out with, you can tweet to us at

834
00:50:23,960 --> 00:50:26,440
Speaker 1: josh um Clark or at s Y s K podcast.

835
00:50:26,800 --> 00:50:29,040
Speaker 1: You can also go on to Facebook dot com slash

836
00:50:29,120 --> 00:50:32,680
Speaker 1: Charles W. Chuck Bryant. You can also visit Facebook dot

837
00:50:32,719 --> 00:50:34,920
Speaker 1: com slash stuff you Should Know. Send us an email

838
00:50:34,960 --> 00:50:37,279
Speaker 1: to Stuff Podcast at how stuff Works dot com, and

839
00:50:37,360 --> 00:50:39,160
Speaker 1: join us at our home on the web, stuff you

840
00:50:39,200 --> 00:50:46,440
Speaker 1: should Know dot com. For more on this and thousands

841
00:50:46,440 --> 00:50:59,239
Speaker 1: of other topics, is it how stuff Works dot com