1 00:00:00,680 --> 00:00:03,160 Speaker 1: I get a team Craig Anthony Harper reporting in It's 2 00:00:03,160 --> 00:00:07,240 Speaker 1: four oh two, it's bloody, it's New Year's Eve, it's news. 3 00:00:07,400 --> 00:00:10,280 Speaker 1: I don't even know why we're recording today. Well I 4 00:00:10,320 --> 00:00:12,480 Speaker 1: do because I asked David and he's got no life 5 00:00:12,480 --> 00:00:16,360 Speaker 1: and I've got no life between the two of us, 6 00:00:16,440 --> 00:00:19,680 Speaker 1: los as we went. Fuck it, let's record an episode 7 00:00:19,680 --> 00:00:21,360 Speaker 1: of the Year project. Happy New Year, mate? 8 00:00:21,360 --> 00:00:21,840 Speaker 2: How are you? 9 00:00:22,320 --> 00:00:23,239 Speaker 3: Yeah? Good? How are you? 10 00:00:24,480 --> 00:00:25,040 Speaker 2: I'm good? 11 00:00:25,560 --> 00:00:28,800 Speaker 1: You don't I could get in trouble saying this, but 12 00:00:28,880 --> 00:00:31,960 Speaker 1: fuck it, I'll say. You don't strike me as the 13 00:00:32,040 --> 00:00:35,280 Speaker 1: super festive type. Am I right or wrong with that? 14 00:00:36,240 --> 00:00:40,479 Speaker 1: I think you're probably right. I don't tend to go 15 00:00:40,600 --> 00:00:45,800 Speaker 1: in for celebrating things. I guess yeah. 16 00:00:45,840 --> 00:00:48,640 Speaker 3: I'm also just quite happy if people ignore my birthday 17 00:00:48,680 --> 00:00:49,640 Speaker 3: and things like that too. 18 00:00:50,520 --> 00:00:53,600 Speaker 1: What, yeah, is that a personality thing with you? Is 19 00:00:53,640 --> 00:00:56,080 Speaker 1: that just a personal preference? Where have you always been 20 00:00:57,080 --> 00:00:57,440 Speaker 1: like that? 21 00:00:57,600 --> 00:00:57,720 Speaker 3: Like? 22 00:00:57,800 --> 00:01:00,560 Speaker 1: I can't ever see you despite the fact that you 23 00:01:00,640 --> 00:01:03,520 Speaker 1: have a profile and you're very public in a way, 24 00:01:04,680 --> 00:01:07,800 Speaker 1: you seem you don't seem like an introvert, but you 25 00:01:07,880 --> 00:01:12,959 Speaker 1: definitely seem like somebody who doesn't want to be in 26 00:01:13,000 --> 00:01:14,960 Speaker 1: the middle of a crowd or be the center of 27 00:01:15,000 --> 00:01:18,679 Speaker 1: attention at all, unlike a lot of other public figures. 28 00:01:19,480 --> 00:01:24,319 Speaker 3: Yeah, I've well, I guess maybe it's just laziness. I 29 00:01:24,360 --> 00:01:26,440 Speaker 3: think being the center of attention takes a lot of 30 00:01:26,480 --> 00:01:32,320 Speaker 3: work and is unnecessary for a lot of what I 31 00:01:32,360 --> 00:01:36,400 Speaker 3: have to do, in the sense that all the things 32 00:01:36,440 --> 00:01:42,760 Speaker 3: I've written about are really about providing people with knowledge 33 00:01:43,680 --> 00:01:48,760 Speaker 3: and the tools to do something about something in their lives. 34 00:01:48,880 --> 00:01:51,920 Speaker 3: Like I don't bother writing books, you know, clutching our 35 00:01:51,960 --> 00:01:56,640 Speaker 3: pearls and wringing our hands about climate change even though 36 00:01:56,640 --> 00:01:59,760 Speaker 3: it's very real and very dangerous and so on, because 37 00:02:00,520 --> 00:02:02,760 Speaker 3: I can't think of a way to write a book 38 00:02:02,960 --> 00:02:06,000 Speaker 3: that results in someone being able to meaningfully affect it. 39 00:02:07,720 --> 00:02:12,520 Speaker 3: And it's sort of something that I follow with everything 40 00:02:12,560 --> 00:02:14,480 Speaker 3: I write. The person has to be able to put 41 00:02:14,480 --> 00:02:19,359 Speaker 3: the book down and immediately implement something at a personal 42 00:02:19,480 --> 00:02:28,160 Speaker 3: level that changes something about their lives. And I guess 43 00:02:28,680 --> 00:02:32,040 Speaker 3: that doesn't need me to be an Instagram star to 44 00:02:32,120 --> 00:02:38,840 Speaker 3: do that. It just needs me to be accurate and constant. 45 00:02:40,280 --> 00:02:45,480 Speaker 3: And like I said, probably all boils down to laziness 46 00:02:45,480 --> 00:02:48,120 Speaker 3: in the end, because to be an Instagram star, I'd 47 00:02:48,200 --> 00:02:50,720 Speaker 3: have to do all sorts of things I quite frankly 48 00:02:50,720 --> 00:02:54,880 Speaker 3: wouldn't be comfortable doing, you know, tiktoks and videos and 49 00:02:54,960 --> 00:02:57,200 Speaker 3: unboxings and all that sort of crap. 50 00:02:58,560 --> 00:03:02,400 Speaker 2: Maybe yeah, I just think for you though, like. 51 00:03:04,000 --> 00:03:06,520 Speaker 1: I know, you've got a profile and you you know, 52 00:03:06,600 --> 00:03:08,919 Speaker 1: I guess if I asked ten people, have you heard 53 00:03:08,960 --> 00:03:13,679 Speaker 1: of David Gillespie, the author you know, Sweet Poison, blah 54 00:03:13,720 --> 00:03:16,560 Speaker 1: blah blah all that, I don't know. I think maybe 55 00:03:16,720 --> 00:03:20,640 Speaker 1: three or four ossies might have heard of you, compared 56 00:03:20,680 --> 00:03:23,040 Speaker 1: to none out of ten for me, which I'm fine with. 57 00:03:23,160 --> 00:03:27,320 Speaker 1: But I just think for you, the bigger the bigger 58 00:03:27,360 --> 00:03:31,120 Speaker 1: your social media presence, the more awareness around your messages, 59 00:03:31,680 --> 00:03:34,280 Speaker 1: Like if you had a million followers on Instagram, not 60 00:03:34,360 --> 00:03:36,480 Speaker 1: because you're dancing like a fuck with at a train 61 00:03:36,560 --> 00:03:41,880 Speaker 1: station or unwrapping a fucking you know, a high def 62 00:03:41,920 --> 00:03:44,320 Speaker 1: TV or I don't know. 63 00:03:44,360 --> 00:03:48,040 Speaker 2: Look here's here's my breakfast. Hey everyone, you know. 64 00:03:48,280 --> 00:03:50,080 Speaker 1: I mean, there's a lot of that, But I just think, 65 00:03:50,280 --> 00:03:53,960 Speaker 1: like for you, I actually get frustrated because your writing 66 00:03:54,040 --> 00:03:58,120 Speaker 1: is so brilliant, and I just think enough people don't 67 00:03:58,120 --> 00:04:00,640 Speaker 1: see it, and there's so much shit out there. There's 68 00:04:00,680 --> 00:04:06,280 Speaker 1: so much poor writing and poor information and misinformation that 69 00:04:07,040 --> 00:04:11,640 Speaker 1: is overexposed, you know. Yeah, And I guess I guess 70 00:04:11,640 --> 00:04:15,240 Speaker 1: I live in hope that you know, there's an old 71 00:04:15,240 --> 00:04:17,479 Speaker 1: saying and I can't remember who said it, probably Mark Twain. 72 00:04:17,520 --> 00:04:19,599 Speaker 3: He comes up with all the best ones. You know, 73 00:04:19,600 --> 00:04:23,359 Speaker 3: if it's really news, it'll find you. And I guess 74 00:04:23,640 --> 00:04:27,080 Speaker 3: I live in hope that if someone really needs to 75 00:04:27,120 --> 00:04:30,320 Speaker 3: hear anything I've got to say, there's enough of my 76 00:04:30,480 --> 00:04:34,640 Speaker 3: stuff out there in various places that they will find it. 77 00:04:35,920 --> 00:04:41,479 Speaker 3: And m I just you know, I'd love to have 78 00:04:41,520 --> 00:04:44,960 Speaker 3: a million followers on something, because, as you say, a 79 00:04:44,960 --> 00:04:47,039 Speaker 3: lot more people would read what I had to say. 80 00:04:47,160 --> 00:04:54,359 Speaker 3: But I'm not prepared to get into the churn that 81 00:04:54,480 --> 00:05:01,960 Speaker 3: is required to make that happen. So yeah, like I said, 82 00:05:02,000 --> 00:05:03,600 Speaker 3: it comes back to laziness. 83 00:05:04,320 --> 00:05:06,560 Speaker 2: Well, I think, yah, maybe maybe wisdom. 84 00:05:06,600 --> 00:05:08,840 Speaker 1: I think sometimes I put a fair bit of effort 85 00:05:08,839 --> 00:05:13,320 Speaker 1: into my Instagram, only my Instagram, not really Facebook or whatever. 86 00:05:13,360 --> 00:05:16,799 Speaker 1: And I've got across Facebook and Instagram over one hundred 87 00:05:16,839 --> 00:05:20,200 Speaker 1: thousand followers, which is a few, but it's not bizarre, right, 88 00:05:20,320 --> 00:05:23,320 Speaker 1: But sometimes I think for the time, effort and energy, 89 00:05:23,920 --> 00:05:26,960 Speaker 1: and also what's funny is sometimes I will write something 90 00:05:27,040 --> 00:05:31,400 Speaker 1: that is, you know, as close to profound. 91 00:05:31,000 --> 00:05:31,800 Speaker 2: As I'm going to get. 92 00:05:31,839 --> 00:05:34,560 Speaker 1: Like, it's quite deep and thoughtful, insightful, and potentially if 93 00:05:34,600 --> 00:05:37,320 Speaker 1: somebody would turn that theory into behavior. 94 00:05:37,120 --> 00:05:40,280 Speaker 2: It might be really valuable. And it'll get out of ten. 95 00:05:40,400 --> 00:05:43,720 Speaker 1: Let's say it gets a one response, and then I'll 96 00:05:43,720 --> 00:05:46,400 Speaker 1: put up I'll write on my whiteboard, don't be a 97 00:05:46,440 --> 00:05:48,400 Speaker 1: fucking idiot, and that'll get a nine. 98 00:05:48,839 --> 00:05:50,640 Speaker 2: Right. It's like the. 99 00:05:50,640 --> 00:05:54,680 Speaker 1: Stuff that is so base and so and it's almost 100 00:05:54,880 --> 00:05:59,520 Speaker 1: like the more I swear, the greater the response. In fact, 101 00:05:59,600 --> 00:06:02,839 Speaker 1: it's not. It's not like it is. There's a direct correlation. 102 00:06:03,640 --> 00:06:05,880 Speaker 1: And in fact, I think you've discovered. 103 00:06:06,040 --> 00:06:08,880 Speaker 3: You discovered Ricky Gervais's secret success. 104 00:06:08,960 --> 00:06:12,719 Speaker 1: Then I think I discovered before him. I mean, my 105 00:06:12,920 --> 00:06:16,000 Speaker 1: second book had fuck on the front cover, and that 106 00:06:16,200 --> 00:06:20,040 Speaker 1: was twenty ten, so that was fifteen years ago. And 107 00:06:20,839 --> 00:06:24,719 Speaker 1: that my subsequent book to that, which Penguin saw that 108 00:06:24,839 --> 00:06:27,640 Speaker 1: was just called stop Fucking Around thirty Principles for Blah 109 00:06:27,640 --> 00:06:31,240 Speaker 1: blah blah. Right, And Penguin saw that book and reached 110 00:06:31,240 --> 00:06:33,400 Speaker 1: out to me, which I know is not the normal 111 00:06:33,480 --> 00:06:36,440 Speaker 1: kind of protocol, and said, we had a look at it, 112 00:06:36,480 --> 00:06:38,520 Speaker 1: we liked it, and I sold a lot, right, I 113 00:06:38,600 --> 00:06:42,120 Speaker 1: sold a lot of that book, as you know, like 114 00:06:42,200 --> 00:06:44,799 Speaker 1: I think in Australia ten thousand is the best seller, 115 00:06:44,880 --> 00:06:47,920 Speaker 1: and it was way way, way more than that, with 116 00:06:47,960 --> 00:06:52,160 Speaker 1: no distribution, no publisher, al self published, no interviews, right, 117 00:06:52,640 --> 00:06:53,960 Speaker 1: And so they went, we want. 118 00:06:53,839 --> 00:06:56,000 Speaker 2: You to do a big version of that and. 119 00:06:57,600 --> 00:07:01,279 Speaker 1: Anyway, so I spent I got paid to write a book, 120 00:07:01,320 --> 00:07:02,480 Speaker 1: as you do, and. 121 00:07:02,440 --> 00:07:04,279 Speaker 2: Then I had to deliver it within one hundred and 122 00:07:04,279 --> 00:07:06,880 Speaker 2: eighty days, which I did. But blah blah blah blah. 123 00:07:06,960 --> 00:07:10,360 Speaker 1: I did all this stuff and then they named it 124 00:07:10,600 --> 00:07:14,680 Speaker 1: pull Your Finger Out, which I fucking hated. Right the 125 00:07:14,680 --> 00:07:16,840 Speaker 1: first one stopped fucking around, and this was meant to 126 00:07:16,840 --> 00:07:18,000 Speaker 1: be the bigger, better version. 127 00:07:18,120 --> 00:07:20,960 Speaker 2: I'm like, and I said to them, that's a terrible name. 128 00:07:21,000 --> 00:07:23,120 Speaker 1: And they're like, oh, you know, we've done all the whatever, 129 00:07:23,160 --> 00:07:28,360 Speaker 1: the testing out, you know, and it really tested well, 130 00:07:28,440 --> 00:07:32,480 Speaker 1: and I just said, it absolutely won't work. And I 131 00:07:32,840 --> 00:07:35,000 Speaker 1: don't know if you've ever done this, but I went 132 00:07:35,040 --> 00:07:37,680 Speaker 1: into Penguin and I sat down in a boardroom with 133 00:07:37,760 --> 00:07:40,360 Speaker 1: like ten people who worked on it and marketing and 134 00:07:40,400 --> 00:07:44,440 Speaker 1: branding and market research and all the you know, look 135 00:07:44,480 --> 00:07:48,400 Speaker 1: and feel and color and vibe, and which was great, 136 00:07:48,520 --> 00:07:50,960 Speaker 1: and they were great. Everything was great except the title, 137 00:07:51,200 --> 00:07:53,559 Speaker 1: and then that book, which was a much better book 138 00:07:53,720 --> 00:07:58,240 Speaker 1: in my opinion. I wrote both it it was outsold 139 00:07:58,280 --> 00:07:59,880 Speaker 1: by the first one six to one. 140 00:08:01,040 --> 00:08:04,360 Speaker 2: Yeah, just because it's a shit title, you know. 141 00:08:04,440 --> 00:08:09,040 Speaker 3: Well, yeah, and you will have discovered that it doesn't 142 00:08:09,080 --> 00:08:11,800 Speaker 3: matter what you think of the title. If you signed 143 00:08:11,800 --> 00:08:19,119 Speaker 3: a standard Penguins publication contract, they have entire control over 144 00:08:19,160 --> 00:08:22,520 Speaker 3: the title to cover everything that's on the front and 145 00:08:22,600 --> 00:08:28,200 Speaker 3: back cover, and you they ask you, out of courtesy 146 00:08:28,280 --> 00:08:32,680 Speaker 3: what you think of it. But if you it's a 147 00:08:32,720 --> 00:08:35,800 Speaker 3: pr exercise. If you say it sucks, I want something else, 148 00:08:35,800 --> 00:08:38,000 Speaker 3: they'll say, well, thank you for your input, and go 149 00:08:38,040 --> 00:08:39,200 Speaker 3: ahead and do what they were going to do. 150 00:08:39,240 --> 00:08:43,800 Speaker 1: Anyway, I told them like I sat in the boardroom 151 00:08:44,160 --> 00:08:46,560 Speaker 1: and they literally had this reveal where they had an 152 00:08:46,600 --> 00:08:50,600 Speaker 1: a frame with the book on the cover right so 153 00:08:50,640 --> 00:08:54,439 Speaker 1: that all the artwork, and they pulled off a sheet essentially, 154 00:08:55,679 --> 00:09:00,760 Speaker 1: and my first words were I hate it, and everyone 155 00:09:00,840 --> 00:09:03,960 Speaker 1: looked at me like, apparently you're not meant to say that, 156 00:09:04,040 --> 00:09:04,959 Speaker 1: But anyway. 157 00:09:06,920 --> 00:09:09,120 Speaker 3: I'm having a similar experience at the moment with the 158 00:09:09,160 --> 00:09:12,599 Speaker 3: title of my next book, which but I look, I 159 00:09:12,920 --> 00:09:17,520 Speaker 3: come from the position of I think, never having successfully 160 00:09:17,520 --> 00:09:22,920 Speaker 3: given a good title to anything, and so I have 161 00:09:22,960 --> 00:09:25,959 Speaker 3: no confidence in my ability to be any better at 162 00:09:25,960 --> 00:09:29,360 Speaker 3: it than they are. So, you know, no matter what 163 00:09:29,440 --> 00:09:33,480 Speaker 3: my opinion of their title, I doubt anything I would 164 00:09:33,480 --> 00:09:36,520 Speaker 3: come up with is any better. You know, I find 165 00:09:36,520 --> 00:09:38,280 Speaker 3: that even when in writing an article. You know, at 166 00:09:38,280 --> 00:09:40,480 Speaker 3: the end of writing an article, I have to think 167 00:09:40,520 --> 00:09:43,520 Speaker 3: of a title for it, and I'm usually pretty stumped 168 00:09:44,320 --> 00:09:48,880 Speaker 3: about what to call it. And I doubt I've cracked 169 00:09:49,000 --> 00:09:52,719 Speaker 3: the magic. You know, this is highly clickable if you 170 00:09:52,920 --> 00:09:55,520 Speaker 3: just call it this title. You know, for starters. I 171 00:09:55,520 --> 00:09:57,439 Speaker 3: don't use the word fucking any of the titles of 172 00:09:57,720 --> 00:09:59,160 Speaker 3: any of my pieces or books. 173 00:10:00,760 --> 00:10:04,640 Speaker 1: Well, you've gone okay, So I don't think, well, who knows, 174 00:10:04,840 --> 00:10:06,440 Speaker 1: I mean, you got you are going okay. 175 00:10:06,440 --> 00:10:08,719 Speaker 3: But maybe I should, Yeah, maybe I should. Do you 176 00:10:08,800 --> 00:10:10,840 Speaker 3: know there's that new thing on substack where they do 177 00:10:10,960 --> 00:10:13,480 Speaker 3: the what are they called the ab testing, where you 178 00:10:13,480 --> 00:10:16,800 Speaker 3: can give it alternate titles, and it spends the first 179 00:10:16,840 --> 00:10:20,319 Speaker 3: hour dividing up your audience with various titles and then 180 00:10:20,360 --> 00:10:22,480 Speaker 3: picks the one that worked the best. Maybe I should 181 00:10:22,520 --> 00:10:25,360 Speaker 3: try a few profanities and see what happens. Huh. 182 00:10:25,400 --> 00:10:28,840 Speaker 1: I did a just tongue in cheek, completely ridiculous. You know, 183 00:10:28,840 --> 00:10:31,800 Speaker 1: how you develop scales and then you get scales validated 184 00:10:31,840 --> 00:10:34,480 Speaker 1: over the time. So for my PhD I developed a scale, 185 00:10:34,480 --> 00:10:37,679 Speaker 1: but just for fun, I did another bullshit scale called 186 00:10:38,280 --> 00:10:44,960 Speaker 1: called the fuck scale, which is friendship, understanding, caring, and kindness. 187 00:10:44,960 --> 00:10:49,760 Speaker 1: And it was an emotional kind of investment scale friendship, understanding, caring, 188 00:10:49,760 --> 00:10:52,320 Speaker 1: and kindness and fuck was an acronym for those four words, 189 00:10:52,320 --> 00:10:54,800 Speaker 1: and it was like how many one to seven fucks 190 00:10:54,800 --> 00:10:57,280 Speaker 1: on a like art scale, like how many fucks do 191 00:10:57,280 --> 00:10:57,600 Speaker 1: you give? 192 00:10:57,720 --> 00:10:59,160 Speaker 2: Right? Anyway? 193 00:11:00,880 --> 00:11:03,480 Speaker 1: And it was just complete, Well, that went nuts my 194 00:11:03,679 --> 00:11:09,439 Speaker 1: actual scale that I put up, which is a psychometric 195 00:11:09,520 --> 00:11:12,120 Speaker 1: evaluation like a real one. 196 00:11:11,480 --> 00:11:16,080 Speaker 4: Yeah, whatever sounds boring this other one, you know, the 197 00:11:16,120 --> 00:11:20,880 Speaker 4: fuck scale, Oh my god. Anyway, it's what happens before 198 00:11:20,880 --> 00:11:23,040 Speaker 4: we talk about our actual topic, which will take. 199 00:11:22,880 --> 00:11:27,280 Speaker 2: Six minutes knowing you and me or more. I wanted 200 00:11:27,280 --> 00:11:32,840 Speaker 2: to ask you how would you label How would you 201 00:11:32,960 --> 00:11:33,800 Speaker 2: label your. 202 00:11:33,600 --> 00:11:36,800 Speaker 1: Books or your writing? Would you call it would you 203 00:11:36,800 --> 00:11:40,200 Speaker 1: call it self help, would you call it education? Would 204 00:11:40,240 --> 00:11:43,120 Speaker 1: you call it something else? Or would you call it 205 00:11:43,679 --> 00:11:46,199 Speaker 1: a synthesis of a few things? 206 00:11:46,800 --> 00:11:50,760 Speaker 3: It's education sound like I'm trying to lecture to people, 207 00:11:50,760 --> 00:11:56,200 Speaker 3: which I'm not. I really really hate Ritchie self help books, 208 00:11:57,240 --> 00:12:02,400 Speaker 3: you know, it did really really turned me off. I 209 00:12:03,920 --> 00:12:06,920 Speaker 3: sort of think of it more of you as invested 210 00:12:07,000 --> 00:12:15,280 Speaker 3: investigative journalism with some self help stuff or how to 211 00:12:15,320 --> 00:12:18,400 Speaker 3: apply this at the end of it. You know, so 212 00:12:18,600 --> 00:12:22,440 Speaker 3: this is all terribly interesting, but what does it mean 213 00:12:22,840 --> 00:12:25,840 Speaker 3: to you and me? And I don't like to just 214 00:12:26,120 --> 00:12:28,680 Speaker 3: do the research and not be able to do that, 215 00:12:29,000 --> 00:12:34,440 Speaker 3: and so it's yeah, it's mostly yeah, it's that it's 216 00:12:34,480 --> 00:12:39,720 Speaker 3: not education. Sounds a little bit creachy, like I'm trying 217 00:12:39,720 --> 00:12:41,839 Speaker 3: to teach you something, like like I know it and 218 00:12:41,880 --> 00:12:45,439 Speaker 3: you don't, and I've got to teach you. And usually 219 00:12:45,480 --> 00:12:48,240 Speaker 3: in my books, I don't know the answer before I start. 220 00:12:49,440 --> 00:12:52,960 Speaker 3: I just have a sense that there's something wrong in 221 00:12:53,000 --> 00:12:58,280 Speaker 3: what we're being told about how something works, and I 222 00:12:58,400 --> 00:13:01,920 Speaker 3: like to dig in, and the book ends up being 223 00:13:02,720 --> 00:13:09,320 Speaker 3: the documentation of what I found. And there's been many 224 00:13:10,080 --> 00:13:15,839 Speaker 3: starts at books where I find, actually what we're being 225 00:13:15,840 --> 00:13:18,160 Speaker 3: told about this is the sum of our knowledge on this, 226 00:13:18,400 --> 00:13:22,680 Speaker 3: and there is no other evidence. And so there really 227 00:13:22,720 --> 00:13:28,000 Speaker 3: is no point writing a book that says, well, you know, 228 00:13:28,160 --> 00:13:30,680 Speaker 3: everything the Heart Foundation says is absolutely correct. 229 00:13:31,800 --> 00:13:35,240 Speaker 1: You know who's buying that, yeah, yeah, or a book 230 00:13:35,320 --> 00:13:37,760 Speaker 1: that says, hey, the other books were right, You're welcome 231 00:13:38,080 --> 00:13:39,120 Speaker 1: the next time. 232 00:13:39,120 --> 00:13:42,640 Speaker 3: The less boat into it. I have looked into it 233 00:13:42,679 --> 00:13:43,600 Speaker 3: and they were right. 234 00:13:44,600 --> 00:13:49,480 Speaker 1: I can I can confirm your honor. Yeah, I for me, 235 00:13:49,640 --> 00:13:52,880 Speaker 1: one of them consider I was going to say battles. 236 00:13:52,920 --> 00:13:55,560 Speaker 1: It's not a fucking battle. But one of my constant 237 00:13:55,600 --> 00:13:59,840 Speaker 1: considerations is like, even like I did a gig recently 238 00:14:00,120 --> 00:14:03,640 Speaker 1: for actually for a supplement company down here, but it 239 00:14:03,720 --> 00:14:06,760 Speaker 1: wasn't We didn't talk about their supplements. It's just an 240 00:14:06,920 --> 00:14:13,800 Speaker 1: education night for blokes, you know, in that health, fitness, wellness, performance, aging, 241 00:14:14,080 --> 00:14:19,200 Speaker 1: anti aging, just general stuff, you know, food, exercise, lifestyle, sleep, stress, anxiety, 242 00:14:19,280 --> 00:14:24,840 Speaker 1: self management, all that stuff. And I'm constantly going, so, 243 00:14:24,920 --> 00:14:28,080 Speaker 1: here's something that's worth thinking about, or here's some information, 244 00:14:29,160 --> 00:14:31,680 Speaker 1: here's what we know, here's a bit of research. But 245 00:14:31,760 --> 00:14:33,480 Speaker 1: then I've kind of got to go so what can 246 00:14:33,520 --> 00:14:34,280 Speaker 1: we do about that? 247 00:14:34,320 --> 00:14:37,320 Speaker 2: Though? So that's all well and good, but now what 248 00:14:37,360 --> 00:14:39,840 Speaker 2: does that mean to do to you? And what can 249 00:14:39,880 --> 00:14:42,320 Speaker 2: you do with that? Because I think as well as 250 00:14:42,320 --> 00:14:48,720 Speaker 2: presenting potentially information and problems and current flowared thinking or 251 00:14:49,480 --> 00:14:50,360 Speaker 2: dodgy science. 252 00:14:50,440 --> 00:14:53,520 Speaker 1: You've still got to say. You've still got to give 253 00:14:53,560 --> 00:14:57,920 Speaker 1: them some hope or direction or information or some answers 254 00:14:58,000 --> 00:15:00,920 Speaker 1: that they might be able to, at the very least say, well, 255 00:15:00,960 --> 00:15:03,560 Speaker 1: I'm going to try this because what he spoke about, 256 00:15:03,600 --> 00:15:07,320 Speaker 1: I'm dealing with that. So starting tomorrow, I'm going to whatever. 257 00:15:07,320 --> 00:15:09,160 Speaker 1: I'm going to walk for fifteen minutes a day for 258 00:15:09,200 --> 00:15:10,960 Speaker 1: the next hundred days and see what happens. 259 00:15:11,000 --> 00:15:14,600 Speaker 2: You know, just so people have got a little bit 260 00:15:14,640 --> 00:15:15,680 Speaker 2: of an. 261 00:15:15,560 --> 00:15:20,000 Speaker 3: Action plan at least that applies generally except for the 262 00:15:20,040 --> 00:15:23,960 Speaker 3: topics like the one we're going to discus today, which 263 00:15:24,000 --> 00:15:28,640 Speaker 3: is about drugs. And you know, I don't want anyone 264 00:15:29,160 --> 00:15:31,520 Speaker 3: to be asking me, like you, for example, at the 265 00:15:31,600 --> 00:15:34,080 Speaker 3: end of what we discussed today, so what does this 266 00:15:34,200 --> 00:15:37,560 Speaker 3: mean we should do? Because my answer will be talk 267 00:15:37,560 --> 00:15:42,240 Speaker 3: to your doctor, because I don't want to get into 268 00:15:42,280 --> 00:15:45,480 Speaker 3: a space where I'm telling someone to take a drug 269 00:15:45,560 --> 00:15:49,880 Speaker 3: or not take a drug. In this particular space, what 270 00:15:50,000 --> 00:15:52,920 Speaker 3: we're talking about is what is the evidence actually say? 271 00:15:53,600 --> 00:15:58,720 Speaker 3: And I guess what does it say about us? Given 272 00:15:58,760 --> 00:15:59,320 Speaker 3: the evidence? 273 00:16:00,720 --> 00:16:03,360 Speaker 1: All right, well, let's jump into it. We're talking about writing. 274 00:16:03,440 --> 00:16:08,040 Speaker 1: Let's talk about some of your writing from a substack. 275 00:16:08,160 --> 00:16:11,000 Speaker 1: So this went up two days ago. It's called the 276 00:16:11,000 --> 00:16:14,480 Speaker 1: statin delusion. Everyone, So if you don't follow galspo and substack, 277 00:16:15,480 --> 00:16:18,760 Speaker 1: it's free and it's a great resource, so you should 278 00:16:18,760 --> 00:16:22,640 Speaker 1: definitely do that, all right, tell us about the statined delusion. 279 00:16:22,720 --> 00:16:25,480 Speaker 1: We are trading the remote possibility of a heart attack 280 00:16:26,080 --> 00:16:28,400 Speaker 1: for the certainty of metabolic decay. 281 00:16:28,680 --> 00:16:30,240 Speaker 2: Is the kind of subheading. 282 00:16:31,080 --> 00:16:34,560 Speaker 3: Yeah, so, and I start with an analogy in the 283 00:16:35,920 --> 00:16:40,120 Speaker 3: article and can read that. Go ahead, Yeah, yeah. 284 00:16:39,920 --> 00:16:42,240 Speaker 1: I think that might set it up nicely for people. 285 00:16:44,040 --> 00:16:46,240 Speaker 1: Imagine taking your car to the garage for a road 286 00:16:46,240 --> 00:16:50,680 Speaker 1: worthy certificate. The mechanics circles the vehicle and hums. He 287 00:16:50,720 --> 00:16:54,600 Speaker 1: admits the engineers in pristine. The engine is pristine, and 288 00:16:54,640 --> 00:16:58,760 Speaker 1: the car runs perfectly, but he insists on replacing the transmission. 289 00:16:59,160 --> 00:17:02,120 Speaker 1: This is not because is broken. It is because a 290 00:17:02,160 --> 00:17:06,400 Speaker 1: complex algorithm suggests a four percent chance it might shudder 291 00:17:06,680 --> 00:17:08,439 Speaker 1: in two thousand and thirty two. 292 00:17:08,600 --> 00:17:11,560 Speaker 2: That's funny. You'd call the police. You'd call him a 293 00:17:11,600 --> 00:17:12,359 Speaker 2: fraud and a thief. 294 00:17:12,440 --> 00:17:15,200 Speaker 1: Yet we thank doctors when they do the exact same 295 00:17:15,280 --> 00:17:19,399 Speaker 1: thing with our cardiovascular system. We then head to a chemist. 296 00:17:19,760 --> 00:17:22,600 Speaker 1: This is the state of modern medicine in Australia. We 297 00:17:22,640 --> 00:17:27,040 Speaker 1: are witnessing a monumental act in pharmaceutical theatrics. Health is 298 00:17:27,080 --> 00:17:30,080 Speaker 1: treated as a deficiency of medication. 299 00:17:31,000 --> 00:17:32,959 Speaker 2: All right, I could go on, but I'll let you 300 00:17:33,040 --> 00:17:33,560 Speaker 2: jump in. 301 00:17:34,040 --> 00:17:39,800 Speaker 3: So this is about statens and the interesting thing about 302 00:17:39,800 --> 00:17:43,040 Speaker 3: that so well, first of all, what are staturns. So 303 00:17:43,160 --> 00:17:46,960 Speaker 3: statins are the most prescribed drug in Australia today, the 304 00:17:47,119 --> 00:17:54,280 Speaker 3: most prescribed drug, and I think the stats are pretty extraordinary. 305 00:17:54,440 --> 00:18:00,320 Speaker 3: I think it's something like half of everybody over the 306 00:18:00,359 --> 00:18:02,880 Speaker 3: age of sixty five and a significant proportion of those 307 00:18:02,960 --> 00:18:06,240 Speaker 3: under the age of sixty five in Australia are on statins. 308 00:18:08,280 --> 00:18:10,840 Speaker 3: If a person is over the age of sixty five 309 00:18:10,840 --> 00:18:13,080 Speaker 3: and also has type two diabetes, they've got an eighty 310 00:18:13,119 --> 00:18:16,320 Speaker 3: percent chance of being on Staaten's in Australia. So statins 311 00:18:16,359 --> 00:18:20,040 Speaker 3: are handed out like lollipops at the fate. You know 312 00:18:20,119 --> 00:18:23,560 Speaker 3: this is this is a drug that is massively prescribed 313 00:18:23,600 --> 00:18:26,879 Speaker 3: in Australia. Australia is, by the way, the world leader 314 00:18:26,920 --> 00:18:29,480 Speaker 3: in the prescription of statns. There is no one who 315 00:18:29,520 --> 00:18:33,920 Speaker 3: prescribes more of them on a per capita basis than Australia, 316 00:18:34,600 --> 00:18:35,280 Speaker 3: and we've. 317 00:18:36,400 --> 00:18:38,640 Speaker 1: Just sorry for the ten people who are going, what 318 00:18:38,680 --> 00:18:41,200 Speaker 1: are they They treat high cholesterol, right. 319 00:18:41,480 --> 00:18:44,320 Speaker 3: So what they do. What they do is reduce the 320 00:18:44,440 --> 00:18:48,280 Speaker 3: level of LDL cholesterol, which is theoretically the bad cholesterol. 321 00:18:48,320 --> 00:18:52,840 Speaker 3: And we could go into why I say theoretically and 322 00:18:53,160 --> 00:18:58,280 Speaker 3: you're imagining parenthesis around the bad bit there, and we 323 00:18:58,359 --> 00:19:00,320 Speaker 3: might or we might not. We might leave that for 324 00:19:00,400 --> 00:19:04,680 Speaker 3: another show. But what they do is they do definitively 325 00:19:05,280 --> 00:19:07,439 Speaker 3: or a lot of people, not everyone, but for a 326 00:19:07,440 --> 00:19:12,119 Speaker 3: lot of people, lower the level of LDL cholesterol. And 327 00:19:12,680 --> 00:19:15,240 Speaker 3: if you've ever been to a doctor and had a 328 00:19:15,280 --> 00:19:19,399 Speaker 3: blood test, they'll they'll show you a print out that 329 00:19:19,480 --> 00:19:22,320 Speaker 3: will give you a level of LDL cholesterol. It will 330 00:19:22,359 --> 00:19:24,560 Speaker 3: give you sort of total cholesterol, also give you ld 331 00:19:24,640 --> 00:19:29,119 Speaker 3: old cholesterol and sometimes HDL cholesterol, which is theoretically the 332 00:19:29,160 --> 00:19:35,479 Speaker 3: good cholesterol. And Staton's lower for many people the number 333 00:19:35,640 --> 00:19:42,240 Speaker 3: LDL cholesterol. And for a long time now, the accepted 334 00:19:42,359 --> 00:19:47,800 Speaker 3: science has been that that's a good thing. That if 335 00:19:47,840 --> 00:19:51,240 Speaker 3: you lower people's ld OL cholesterol, it should present prevent 336 00:19:51,400 --> 00:19:55,919 Speaker 3: them having fatal heart attacks or any heart attacks, or 337 00:19:55,960 --> 00:19:57,720 Speaker 3: you know, should reduce the number of heart attacks they're 338 00:19:57,800 --> 00:19:59,600 Speaker 3: likely to have or reduce their risk of heart attack, 339 00:19:59,720 --> 00:20:02,439 Speaker 3: or any number of ways of spinning it, but in general, 340 00:20:02,480 --> 00:20:06,240 Speaker 3: the theory is that if you lower LDOL cholesterol, you 341 00:20:06,320 --> 00:20:13,520 Speaker 3: should have less cardiac events in your life. And initially 342 00:20:13,560 --> 00:20:16,119 Speaker 3: these drugs were used when they first sort of hit 343 00:20:16,160 --> 00:20:19,320 Speaker 3: the market in the nineteen eighties or late nineteen eighties 344 00:20:19,359 --> 00:20:22,960 Speaker 3: early nineteen nineties, they were initially used to give to 345 00:20:23,040 --> 00:20:27,520 Speaker 3: people who had already had a heart attack, so they've 346 00:20:27,560 --> 00:20:32,600 Speaker 3: had their first cardiac event, often young, younger people sort 347 00:20:32,600 --> 00:20:35,399 Speaker 3: of around you, under fifty or so, and they were 348 00:20:35,440 --> 00:20:40,000 Speaker 3: given to them as a way of presenting preventing further 349 00:20:40,080 --> 00:20:44,879 Speaker 3: cardiac events. And there were some early studies that suggested 350 00:20:44,920 --> 00:20:48,520 Speaker 3: that they were reasonably effective at that and honestly, those 351 00:20:48,560 --> 00:20:51,400 Speaker 3: studies have not to my knowledge, been debunked in any 352 00:20:51,440 --> 00:20:54,600 Speaker 3: great degree since then, despite some of the problems I'm 353 00:20:54,600 --> 00:21:01,200 Speaker 3: about to discuss with the studies. But the what has 354 00:21:01,240 --> 00:21:03,880 Speaker 3: happened though, is that the drug companies have taken that 355 00:21:04,320 --> 00:21:09,359 Speaker 3: glimmer of success. And you might imagine that people under 356 00:21:09,359 --> 00:21:12,040 Speaker 3: fifty who've had a heart attack, well it's actually only 357 00:21:12,080 --> 00:21:14,879 Speaker 3: men under fifty who've had a heart attack. The studies 358 00:21:14,880 --> 00:21:19,600 Speaker 3: didn't show any definitive benefit for women, but men under 359 00:21:19,640 --> 00:21:24,720 Speaker 3: fifty who've had a heart attack is a relatively small market, 360 00:21:26,119 --> 00:21:28,720 Speaker 3: and it's certainly not getting you anywhere near the numbers 361 00:21:28,760 --> 00:21:30,840 Speaker 3: I just gave you before. You know, with six out 362 00:21:30,880 --> 00:21:33,919 Speaker 3: of ten people over the age of sixty five taking 363 00:21:33,920 --> 00:21:36,760 Speaker 3: a drug every day of the week, you're not getting 364 00:21:36,760 --> 00:21:40,920 Speaker 3: near that. So the drug companies managed to convert that 365 00:21:41,040 --> 00:21:46,879 Speaker 3: glimmer of success into over the last thirty years, a 366 00:21:46,960 --> 00:21:51,680 Speaker 3: widespread program of everyone being given or as many people 367 00:21:51,680 --> 00:21:54,919 Speaker 3: as possible being given these things as a preventative measure. 368 00:21:55,440 --> 00:21:58,320 Speaker 3: So you might feel perfectly well. And this is why 369 00:21:58,359 --> 00:22:01,399 Speaker 3: I use the mechanic analogy. The start, you might feel 370 00:22:01,440 --> 00:22:04,840 Speaker 3: perfectly well. It might you might look perfectly well. There 371 00:22:04,920 --> 00:22:07,000 Speaker 3: might be nothing wrong with your heart to you know, 372 00:22:07,040 --> 00:22:10,280 Speaker 3: the casual observer or the medical observer, but you never know, 373 00:22:11,080 --> 00:22:16,120 Speaker 3: you know, just in case, just in case, take this thing, 374 00:22:16,640 --> 00:22:20,000 Speaker 3: and you know it'll it'll reduce your risk of ever 375 00:22:20,040 --> 00:22:20,959 Speaker 3: having a heart attack. 376 00:22:21,680 --> 00:22:25,280 Speaker 1: Well, based on that logic, I should wear my motorcycle 377 00:22:25,359 --> 00:22:27,919 Speaker 1: helmet on and off the motorbike. I should wear that 378 00:22:28,000 --> 00:22:32,359 Speaker 1: around the house pretty much, same logic, exact same logic, Yeah, 379 00:22:32,480 --> 00:22:38,040 Speaker 1: which is you just never know. And even though you've 380 00:22:38,040 --> 00:22:40,200 Speaker 1: never had a heart attack and you don't seem to 381 00:22:40,240 --> 00:22:43,080 Speaker 1: be at risk of having a heart attack, why not 382 00:22:44,560 --> 00:22:46,960 Speaker 1: And if these and if the drugs that we're talking 383 00:22:46,960 --> 00:22:51,120 Speaker 1: about were completely harmless, like if I was talking about 384 00:22:51,200 --> 00:22:52,320 Speaker 1: here was a sugar pill. 385 00:22:54,040 --> 00:22:58,200 Speaker 3: And it made people feel better to take one every day, 386 00:22:58,359 --> 00:23:01,600 Speaker 3: to you know, you say, oh, you know, I've said 387 00:23:01,680 --> 00:23:03,640 Speaker 3: my three hele Mary's and I've taken a sugar pill, 388 00:23:03,680 --> 00:23:06,600 Speaker 3: So I'm definitely not having a heart attack today. That's 389 00:23:07,520 --> 00:23:10,000 Speaker 3: that would be fine. People can believe what they want 390 00:23:10,040 --> 00:23:14,760 Speaker 3: to believe, but these are not harmless. Their mechanism of 391 00:23:14,800 --> 00:23:20,320 Speaker 3: action is to shut down the liver's production of something 392 00:23:20,320 --> 00:23:23,880 Speaker 3: which is used to produce cholesterol called coenzyme Q ten. 393 00:23:25,320 --> 00:23:28,840 Speaker 3: So coenzyme Q ten you might have heard of before 394 00:23:28,880 --> 00:23:33,160 Speaker 3: if you've ever seen any cosmetics commercials, because it's often 395 00:23:33,200 --> 00:23:35,480 Speaker 3: touted as being something that you want to rub on 396 00:23:35,520 --> 00:23:38,760 Speaker 3: your skin or something. I've never quite followed the logic 397 00:23:38,800 --> 00:23:43,160 Speaker 3: of that, but it's it is actually a pretty handy 398 00:23:43,200 --> 00:23:44,960 Speaker 3: thing to have in your body. It's it's kind of 399 00:23:45,000 --> 00:23:49,480 Speaker 3: regarded in medicine as the starter motor for your cellular metabolism. 400 00:23:50,320 --> 00:23:54,520 Speaker 3: So it's it's the spark that gets cells producing the 401 00:23:54,600 --> 00:23:58,960 Speaker 3: right level of energy, and it's all. It does some 402 00:23:59,000 --> 00:24:01,000 Speaker 3: other things as well as as always the body never 403 00:24:01,080 --> 00:24:04,479 Speaker 3: just does one thing with anything, you know, and some 404 00:24:04,800 --> 00:24:06,880 Speaker 3: one of the others is that it is a very 405 00:24:06,960 --> 00:24:12,520 Speaker 3: very powerful antioxidant. So, and antioxidants are pretty handy. You 406 00:24:12,520 --> 00:24:17,800 Speaker 3: will recall from how many discussions about cancer that antioxidants 407 00:24:17,800 --> 00:24:21,080 Speaker 3: are a big part of stopping that happening because they 408 00:24:23,240 --> 00:24:26,320 Speaker 3: reduce the potential for oxidation within the system, particularly when 409 00:24:26,320 --> 00:24:29,200 Speaker 3: you take things that oxidize easily like seed oils. But 410 00:24:29,240 --> 00:24:31,560 Speaker 3: that's a little bit of the side So the mechanism 411 00:24:31,640 --> 00:24:34,240 Speaker 3: of action for Staton, though, is that they shut down 412 00:24:34,240 --> 00:24:38,639 Speaker 3: the production of coenzon q ten. So, as you might imagine, 413 00:24:38,960 --> 00:24:43,399 Speaker 3: there could be side effects, and the side effects have 414 00:24:43,480 --> 00:24:46,520 Speaker 3: started to become really quite apparent. There's a significant increase 415 00:24:46,600 --> 00:24:49,600 Speaker 3: nine percent increase in the incidence of type two diabetes 416 00:24:49,720 --> 00:24:53,800 Speaker 3: because apparently coinzon q ten is pretty handy in the pancreas, 417 00:24:55,000 --> 00:24:58,560 Speaker 3: and so there is a significant It's so much so 418 00:24:58,680 --> 00:25:00,960 Speaker 3: that the FDA and the United States now requires a 419 00:25:01,000 --> 00:25:07,320 Speaker 3: warning on statins to say that to say that there's 420 00:25:07,359 --> 00:25:13,080 Speaker 3: also many people who take statan's report muscle pain, and 421 00:25:13,359 --> 00:25:18,040 Speaker 3: it's often the reason that people stop taking them. You know, 422 00:25:18,160 --> 00:25:20,639 Speaker 3: much of the spare of the medical profession. You know, 423 00:25:20,880 --> 00:25:23,240 Speaker 3: they call that non compliance. Well, a big reason for 424 00:25:23,320 --> 00:25:26,439 Speaker 3: non compliance is that people experience muscle pain. Some of 425 00:25:26,480 --> 00:25:29,560 Speaker 3: the studies have shown that it's around twenty percent one 426 00:25:29,600 --> 00:25:34,160 Speaker 3: in five people taking statin's experience study experience muscle pain. 427 00:25:34,760 --> 00:25:38,920 Speaker 3: There's some interesting new evidence that suggests that they also 428 00:25:39,000 --> 00:25:42,680 Speaker 3: increase the incidence of stroke, which is a bit ironic 429 00:25:43,040 --> 00:25:46,960 Speaker 3: because you know, it's sort of training avoiding heart disease 430 00:25:47,880 --> 00:25:52,119 Speaker 3: and acquiring a risk of stroke. And these are all 431 00:25:52,240 --> 00:25:55,720 Speaker 3: quite concerning things for something that you may not need 432 00:25:55,760 --> 00:25:58,879 Speaker 3: to be taking at all in the first place. And 433 00:26:00,200 --> 00:26:05,040 Speaker 3: the problem here is with the evidence. Now there's precious 434 00:26:05,840 --> 00:26:11,160 Speaker 3: little objective evidence about the effectiveness of statins, and that's 435 00:26:11,160 --> 00:26:16,200 Speaker 3: because of a really peculiar arrangement between the drug companies 436 00:26:16,960 --> 00:26:23,160 Speaker 3: and the research group who are responsible for I think 437 00:26:23,200 --> 00:26:26,800 Speaker 3: it's twenty seven out of twenty eight of the major 438 00:26:26,840 --> 00:26:33,399 Speaker 3: statin trials analyzed and reported on by something called the 439 00:26:33,400 --> 00:26:36,959 Speaker 3: Clinical Trial Service Unit, which is part of the University 440 00:26:36,960 --> 00:26:41,359 Speaker 3: of Oxford. It's a joint thing between the NHMRC in 441 00:26:41,400 --> 00:26:45,720 Speaker 3: Australia and the University of Oxford, and so almost all 442 00:26:45,760 --> 00:26:48,960 Speaker 3: the data we have on the efficacy of statins comes 443 00:26:49,119 --> 00:26:53,439 Speaker 3: from this group, which in itself isn't necessarily a problem 444 00:26:53,520 --> 00:26:55,320 Speaker 3: except when you start to digging in a little about 445 00:26:55,760 --> 00:27:00,600 Speaker 3: how they're funded. So they're funded essentially by the companies 446 00:27:01,600 --> 00:27:07,240 Speaker 3: and they which once again you'd say, okay, well, that's 447 00:27:07,280 --> 00:27:08,720 Speaker 3: a cause for concerns, So we need to be a 448 00:27:08,760 --> 00:27:12,400 Speaker 3: little bit careful about anything that they say, particularly when 449 00:27:12,480 --> 00:27:15,439 Speaker 3: what they say seems to be at odds with the 450 00:27:15,480 --> 00:27:20,800 Speaker 3: few independent studies that have been done. But maybe that's 451 00:27:20,800 --> 00:27:22,919 Speaker 3: a coincidence, So you need to dig a little bit 452 00:27:22,960 --> 00:27:26,720 Speaker 3: further than that. And one of the big concerns about 453 00:27:26,720 --> 00:27:30,679 Speaker 3: this group is that they never publish the original data, 454 00:27:30,880 --> 00:27:33,919 Speaker 3: the raw data that is being used in the trials, 455 00:27:34,000 --> 00:27:38,920 Speaker 3: So they'll publish their interpretation of the data, but never 456 00:27:38,960 --> 00:27:41,960 Speaker 3: the actual data, so other scientists can't look at the 457 00:27:42,040 --> 00:27:45,080 Speaker 3: data and see if they agree with the conclusions that 458 00:27:45,080 --> 00:27:45,760 Speaker 3: they've come out. 459 00:27:46,560 --> 00:27:50,720 Speaker 1: How is that I mean as and I know, I 460 00:27:50,800 --> 00:27:53,320 Speaker 1: know we've established that psychology is not real And my 461 00:27:53,440 --> 00:27:57,080 Speaker 1: PhD is essentially analogous to getting a Barista qualification. 462 00:27:57,520 --> 00:27:58,560 Speaker 2: We've sorted out. 463 00:27:58,960 --> 00:28:01,800 Speaker 3: But you can make more money with it though. 464 00:28:02,320 --> 00:28:06,280 Speaker 1: Yeah, no, I know, I know, hello, Barista school, it's ups. 465 00:28:08,200 --> 00:28:11,800 Speaker 2: But how is that even a thing? 466 00:28:12,119 --> 00:28:16,400 Speaker 1: Where like, how in twenty twenty five can we have 467 00:28:16,520 --> 00:28:24,320 Speaker 1: companies that have got an extremely huge financial interest in 468 00:28:24,400 --> 00:28:29,720 Speaker 1: the outcome of the research fund the research, knowing that, 469 00:28:30,600 --> 00:28:35,679 Speaker 1: with the academic institution knowing that should they produce data 470 00:28:35,720 --> 00:28:41,080 Speaker 1: that doesn't align with the wants of the bank, the 471 00:28:41,120 --> 00:28:45,200 Speaker 1: pharmaceutical bank, then they're going to get funding cut. I mean, 472 00:28:45,800 --> 00:28:49,280 Speaker 1: it's just like that. Just isn't how science. I mean 473 00:28:49,320 --> 00:28:53,120 Speaker 1: to me, that's not science at all. There's no objectivity 474 00:28:53,160 --> 00:28:56,400 Speaker 1: there like that just and I don't just mean with 475 00:28:56,480 --> 00:29:00,080 Speaker 1: pharma college or pharmaceutical industry, but with all of it. 476 00:29:00,320 --> 00:29:01,640 Speaker 2: Like, if something's. 477 00:29:01,240 --> 00:29:04,720 Speaker 1: Funded by a group that has a financial interest in 478 00:29:04,760 --> 00:29:07,280 Speaker 1: the outcome of the science, who's going to believe that? 479 00:29:07,440 --> 00:29:10,240 Speaker 2: And why is that still a thing? Yeah? 480 00:29:10,280 --> 00:29:13,280 Speaker 3: Well, a good question. This is probably the most egregious 481 00:29:13,320 --> 00:29:19,560 Speaker 3: example of it, but it is rife. There are enormous 482 00:29:19,640 --> 00:29:24,400 Speaker 3: numbers of trials that are covertly funded by Coca Cola 483 00:29:24,480 --> 00:29:27,280 Speaker 3: and Pepsi and some on that come to the conclusion 484 00:29:27,320 --> 00:29:31,280 Speaker 3: that there's nothing wrong with sugar. And you know, they 485 00:29:31,280 --> 00:29:34,000 Speaker 3: don't say this is Cooke's trial on this this is 486 00:29:34,080 --> 00:29:36,840 Speaker 3: you know, it comes from a reputable university, and the 487 00:29:36,880 --> 00:29:40,640 Speaker 3: fundings come from something called ICSI. I can't remember the 488 00:29:40,680 --> 00:29:44,640 Speaker 3: acronym stand for, but it's an international research thing, and 489 00:29:44,800 --> 00:29:47,800 Speaker 3: you have to dig pretty hard to find out who's 490 00:29:47,840 --> 00:29:50,000 Speaker 3: actually paying for it. And you have to really understand 491 00:29:50,080 --> 00:29:53,000 Speaker 3: the study to understand how they've bent the rules a 492 00:29:53,040 --> 00:29:55,120 Speaker 3: bit to make sure that they get the result they want. 493 00:29:56,160 --> 00:29:59,360 Speaker 3: And on that point, one of the big criticisms of 494 00:29:59,440 --> 00:30:02,800 Speaker 3: the studies that these folks produce is that they use 495 00:30:03,280 --> 00:30:06,480 Speaker 3: a way of measuring the results which is not standard. 496 00:30:07,720 --> 00:30:10,840 Speaker 3: So in a normal trial, you just go head to head, 497 00:30:10,840 --> 00:30:12,840 Speaker 3: you say, right, we've got a thousand people taking the drug, 498 00:30:12,880 --> 00:30:15,720 Speaker 3: we've got a thousand people taking the placebo. Let's measure 499 00:30:15,720 --> 00:30:18,840 Speaker 3: the outcomes. You think that would be the That's called 500 00:30:18,840 --> 00:30:23,360 Speaker 3: an intention to treat trial, and that's the way most 501 00:30:23,360 --> 00:30:26,719 Speaker 3: science is done if you want a placebo controlled trial, 502 00:30:26,760 --> 00:30:30,200 Speaker 3: which is what you do with the drug, right, But 503 00:30:30,240 --> 00:30:33,320 Speaker 3: that's not how they do it. So what they do 504 00:30:33,720 --> 00:30:38,680 Speaker 3: is they report their results based on the degree of 505 00:30:38,840 --> 00:30:42,560 Speaker 3: responsiveness to the drug. So the amount that the person's 506 00:30:42,920 --> 00:30:47,000 Speaker 3: LDL was reduced, and they put them in one group 507 00:30:47,560 --> 00:30:50,600 Speaker 3: and the people whose LDL wasn't reduced in another group. 508 00:30:51,080 --> 00:30:55,800 Speaker 3: And these crossover both of the people with the perceibo 509 00:30:56,160 --> 00:30:57,840 Speaker 3: and the non perceivo on. Because you can't see the 510 00:30:57,880 --> 00:31:01,280 Speaker 3: original data, you don't know which is which, and they're 511 00:31:01,360 --> 00:31:06,960 Speaker 3: just saying, of the people whose LDL was reduced, we 512 00:31:07,000 --> 00:31:13,360 Speaker 3: report that they had, you know, ten percent lower incidents 513 00:31:13,400 --> 00:31:17,720 Speaker 3: of maya cardial events ten years later or something like that. 514 00:31:18,160 --> 00:31:21,200 Speaker 3: And because you can't look at the original data and 515 00:31:21,240 --> 00:31:25,600 Speaker 3: you can't essentially do what any study would do, which 516 00:31:25,640 --> 00:31:27,840 Speaker 3: is just put the people who took the perceibo versus 517 00:31:27,880 --> 00:31:30,040 Speaker 3: the people who took the drug side by side and 518 00:31:30,080 --> 00:31:33,320 Speaker 3: see the outcomes, you've just got this muddy in. And 519 00:31:33,720 --> 00:31:36,800 Speaker 3: there is a strong suspicion amongst many researchers that the 520 00:31:36,840 --> 00:31:40,440 Speaker 3: reason it's done that way is to make it that 521 00:31:40,520 --> 00:31:43,480 Speaker 3: you get a positive outcome for statins from their trials 522 00:31:43,760 --> 00:31:50,120 Speaker 3: that otherwise would not be there. So it's that's why 523 00:31:50,680 --> 00:31:53,600 Speaker 3: there's concern in this area. Now there are studies done 524 00:31:53,840 --> 00:31:57,840 Speaker 3: by independent groups. There are independent groups of scientists who 525 00:31:57,880 --> 00:32:00,320 Speaker 3: have looked at as much data as they can find 526 00:32:00,360 --> 00:32:03,400 Speaker 3: on this. Have tried to work back from the data 527 00:32:03,400 --> 00:32:05,800 Speaker 3: that is published about this and have come to the 528 00:32:05,840 --> 00:32:14,640 Speaker 3: conclusion that there's by and large no real preventative benefit. 529 00:32:15,680 --> 00:32:19,040 Speaker 3: They would agree there is a benefit to people who 530 00:32:19,040 --> 00:32:22,440 Speaker 3: have already had a heart attack. There is a benefit. 531 00:32:22,720 --> 00:32:25,720 Speaker 3: It is not a huge one, but there is one. Yes, 532 00:32:26,000 --> 00:32:29,000 Speaker 3: But they would say there just isn't data there to 533 00:32:29,520 --> 00:32:33,560 Speaker 3: support the notion that people taking these things as a 534 00:32:33,600 --> 00:32:37,640 Speaker 3: prophylactic you know, or you you with your motiviing helmet, 535 00:32:38,280 --> 00:32:41,840 Speaker 3: it just makes any difference whatsoever There might even be 536 00:32:42,080 --> 00:32:45,880 Speaker 3: There might even be an argument depending on who's taking it. 537 00:32:46,160 --> 00:32:50,000 Speaker 3: You know, somebody with no history of anything, who's relatively 538 00:32:50,040 --> 00:32:55,240 Speaker 3: fit and healthy and forty years old, the risks might 539 00:32:55,320 --> 00:32:59,600 Speaker 3: be greater than the potential benefits even well, exactly because 540 00:32:59,600 --> 00:33:01,720 Speaker 3: of the risk that I outlined before. So we're talking 541 00:33:01,720 --> 00:33:06,240 Speaker 3: about things like hemorrhagic stroke, type two diabetes. So those 542 00:33:06,280 --> 00:33:10,560 Speaker 3: type two diabetes incidences are relative increase over a person 543 00:33:10,560 --> 00:33:14,000 Speaker 3: who would never have gotten it before. So this is 544 00:33:14,040 --> 00:33:16,240 Speaker 3: a brand new disease that they would not have been 545 00:33:16,840 --> 00:33:19,800 Speaker 3: likely to get prior to taking the drug. And this 546 00:33:19,880 --> 00:33:23,719 Speaker 3: has been established beyond doubt in the research. So you know, 547 00:33:24,200 --> 00:33:28,600 Speaker 3: hemorrhagic stroke, type two diabetes, massive incidents of muscle pain 548 00:33:28,680 --> 00:33:32,000 Speaker 3: one in five with muscle pain that is significant. There's 549 00:33:32,040 --> 00:33:38,320 Speaker 3: some evidence of cognitive decline making dementia worse, so you know, 550 00:33:38,440 --> 00:33:41,880 Speaker 3: it's there are certainly a list of things that we 551 00:33:41,920 --> 00:33:44,040 Speaker 3: should be a bit concerned about with these things, which 552 00:33:44,080 --> 00:33:46,600 Speaker 3: is why I say these are not lollies, these are 553 00:33:46,600 --> 00:33:49,520 Speaker 3: not placebos. It does matter if you take it if 554 00:33:49,520 --> 00:33:53,160 Speaker 3: you don't need to take it. And then besides all 555 00:33:53,200 --> 00:33:57,840 Speaker 3: of this, we've also had a persistent moving of the 556 00:33:57,880 --> 00:34:02,880 Speaker 3: goalposts in terms of what is the target level of LDL. 557 00:34:03,600 --> 00:34:06,120 Speaker 3: So and I put a bit of a history of 558 00:34:06,160 --> 00:34:09,960 Speaker 3: this in the in the article where they you know 559 00:34:10,719 --> 00:34:13,759 Speaker 3: where the goalposts have been moving. The target started at 560 00:34:13,760 --> 00:34:20,240 Speaker 3: three point five and has moved so that these numbers, 561 00:34:20,280 --> 00:34:22,320 Speaker 3: by the way, are the standard numbers that appear on 562 00:34:22,640 --> 00:34:28,040 Speaker 3: Australian you know, blood reports. So when these drugs first 563 00:34:28,040 --> 00:34:31,200 Speaker 3: came out, if you had a total cholesterol count of 564 00:34:31,400 --> 00:34:34,160 Speaker 3: six point five million miles per later you were given 565 00:34:34,160 --> 00:34:35,680 Speaker 3: a clean bill of health and cent on your way. 566 00:34:37,160 --> 00:34:39,879 Speaker 3: But then they said they started moving the target on 567 00:34:39,880 --> 00:34:42,399 Speaker 3: once they discovered LDL and started to be able to say, oh, 568 00:34:42,440 --> 00:34:44,200 Speaker 3: this is the magic thing that needs to be fixed. 569 00:34:45,239 --> 00:34:47,080 Speaker 3: They started at the target of you want to get 570 00:34:47,080 --> 00:34:50,520 Speaker 3: it at three point five, and then it moved to 571 00:34:50,600 --> 00:34:54,200 Speaker 3: two point five, then to one point eight, and today 572 00:34:54,200 --> 00:34:59,719 Speaker 3: it's one point four. So each movement of this target 573 00:35:00,480 --> 00:35:04,000 Speaker 3: increases the number of people in the population who the 574 00:35:04,080 --> 00:35:08,600 Speaker 3: target would suggest need to have this thing right, and 575 00:35:08,640 --> 00:35:12,000 Speaker 3: so steadily, not surprisingly, the number of people in the 576 00:35:12,040 --> 00:35:16,920 Speaker 3: population being prescribed to these things has increased very rapidly, 577 00:35:17,000 --> 00:35:19,120 Speaker 3: until now we are, as I said, top of the 578 00:35:19,200 --> 00:35:23,399 Speaker 3: league in the OECD, We now prescribe more statons per 579 00:35:23,440 --> 00:35:28,239 Speaker 3: person than anyone else in the world. Yes, so, and 580 00:35:28,280 --> 00:35:31,600 Speaker 3: that's a direct result of you know, the well meaning 581 00:35:31,680 --> 00:35:35,280 Speaker 3: GP down the road he sees the official target. Oh, 582 00:35:35,320 --> 00:35:37,719 Speaker 3: it was three point five and now it's one point four. 583 00:35:38,080 --> 00:35:41,399 Speaker 3: I guess before I barely had any patients that were, 584 00:35:41,719 --> 00:35:43,359 Speaker 3: you know, needing to have these things, and now they 585 00:35:43,480 --> 00:35:44,560 Speaker 3: now suddenly all of them do. 586 00:35:45,600 --> 00:35:48,040 Speaker 2: Yeah, yeah, yeah. 587 00:35:48,120 --> 00:35:50,160 Speaker 1: I was just as you were talking, I was trying 588 00:35:50,160 --> 00:35:53,040 Speaker 1: to find I don't know if you've seen you don't 589 00:35:53,080 --> 00:35:56,719 Speaker 1: look at social media much, but it came across my 590 00:35:57,320 --> 00:36:01,319 Speaker 1: or it came to my attention this these papers, that 591 00:36:01,400 --> 00:36:04,320 Speaker 1: these I think it was two guys wrote based purely 592 00:36:04,400 --> 00:36:08,040 Speaker 1: on fraudulent data and fraud, like the whole thing was bullshit. 593 00:36:08,880 --> 00:36:14,359 Speaker 1: So they wrote these papers on these stupid topics, but 594 00:36:14,440 --> 00:36:18,960 Speaker 1: really well written. They are academics, really well written. And 595 00:36:19,080 --> 00:36:21,400 Speaker 1: these papers there was I think it was like nine 596 00:36:21,400 --> 00:36:24,759 Speaker 1: of them got published in like Tier one and two, 597 00:36:25,400 --> 00:36:29,240 Speaker 1: which for my listeners is kind of the gold standard 598 00:36:29,280 --> 00:36:35,960 Speaker 1: Tier one anyway, papers journals, and I just wonder how 599 00:36:36,040 --> 00:36:38,640 Speaker 1: much stuff. And I was just looking then at some 600 00:36:38,800 --> 00:36:41,920 Speaker 1: of the stuff I was trying to find. I was 601 00:36:41,920 --> 00:36:44,080 Speaker 1: trying to find those I can't, but I wonder how 602 00:36:44,160 --> 00:36:50,560 Speaker 1: much just fabrication and kind of you know, I don't know, 603 00:36:51,239 --> 00:36:55,200 Speaker 1: bending bending of the rules, but bending of the truth 604 00:36:55,280 --> 00:36:58,000 Speaker 1: goes on in trying to put these papers together. And 605 00:36:58,440 --> 00:37:01,399 Speaker 1: like I know, one of my friends is going through 606 00:37:01,440 --> 00:37:04,640 Speaker 1: this thing now where they're looking at the data and 607 00:37:04,680 --> 00:37:07,719 Speaker 1: the data is not telling him a lot with his research, 608 00:37:07,960 --> 00:37:10,600 Speaker 1: and so they because he has to produce a paper, 609 00:37:11,400 --> 00:37:15,719 Speaker 1: and he's desperately it's not me, by the way, but 610 00:37:16,440 --> 00:37:21,080 Speaker 1: desperately trying to find something to write a paper on 611 00:37:21,360 --> 00:37:25,560 Speaker 1: and to find some kind of correlation between A and. 612 00:37:25,480 --> 00:37:30,279 Speaker 2: B, because sometimes there's sometimes it just tells you fuck all, Well. 613 00:37:30,160 --> 00:37:33,200 Speaker 3: There's nothing more boring than you have a hypothesis that 614 00:37:34,280 --> 00:37:36,640 Speaker 3: you know, if you do a then B happens, and 615 00:37:36,680 --> 00:37:38,319 Speaker 3: then you go and measure it all and you find 616 00:37:38,360 --> 00:37:43,200 Speaker 3: out that it doesn't, and then your paper consists of, well, 617 00:37:43,200 --> 00:37:44,160 Speaker 3: I guess I was wrong. 618 00:37:45,200 --> 00:37:49,160 Speaker 2: Yeah, yeah, essentially essentially. 619 00:37:49,480 --> 00:37:51,120 Speaker 3: I mean, and we've seen a bit of that in 620 00:37:51,160 --> 00:37:54,080 Speaker 3: the in the in the research on and this comes 621 00:37:54,080 --> 00:37:55,799 Speaker 3: back to this point about the importance of being able 622 00:37:55,800 --> 00:37:58,560 Speaker 3: to see the underlying data. So there was a massive 623 00:38:00,080 --> 00:38:02,719 Speaker 3: study done back in the days when governments did spend 624 00:38:02,719 --> 00:38:04,640 Speaker 3: a lot of money on this sort of thing because 625 00:38:04,640 --> 00:38:08,000 Speaker 3: of the heart disease was absolutely peaking in the late 626 00:38:08,120 --> 00:38:12,360 Speaker 3: nineteen sixties in the United States, the massive rates of 627 00:38:12,400 --> 00:38:15,520 Speaker 3: increase of heart disease. We now know that that was 628 00:38:15,520 --> 00:38:18,440 Speaker 3: because of the massive rates of smoking. But even to 629 00:38:18,440 --> 00:38:20,279 Speaker 3: this day, no one's going to admit that they still 630 00:38:20,280 --> 00:38:22,520 Speaker 3: want to pin it with saturated fat. But they did 631 00:38:23,239 --> 00:38:31,120 Speaker 3: these huge studies where they Minnesota County Experiment for example. 632 00:38:31,520 --> 00:38:32,880 Speaker 3: I can't remember how I think it was close to 633 00:38:32,880 --> 00:38:36,400 Speaker 3: one hundred thousand people were enrolled in it. I can 634 00:38:36,400 --> 00:38:38,880 Speaker 3: you imagine the cost of doing something like that for 635 00:38:39,000 --> 00:38:43,120 Speaker 3: years on end, where they were having half the people 636 00:38:43,239 --> 00:38:47,000 Speaker 3: were eating a normal saturated fat diet and the other 637 00:38:47,080 --> 00:38:49,600 Speaker 3: half had a lower fat diet or eating seed oils 638 00:38:49,640 --> 00:38:53,640 Speaker 3: instead or things like that, and they measured and their 639 00:38:53,680 --> 00:38:56,440 Speaker 3: hypothesis was that the people who were eating the lower 640 00:38:56,480 --> 00:39:02,080 Speaker 3: fat diet and the polyon saturates, etc. Would have less 641 00:39:02,520 --> 00:39:05,919 Speaker 3: coronary events than the people eating the normal the butter, 642 00:39:05,960 --> 00:39:09,520 Speaker 3: the cheese, the milk, et cetera. And it turned out 643 00:39:09,520 --> 00:39:14,000 Speaker 3: it didn't, and so they never published. So this thing 644 00:39:14,600 --> 00:39:18,400 Speaker 3: went on at enormous expense for I think four years, 645 00:39:19,080 --> 00:39:24,719 Speaker 3: huge numbers of people involved, large, you know, and they 646 00:39:24,719 --> 00:39:29,200 Speaker 3: put out a paper that essentially said nothing, so essentially 647 00:39:29,520 --> 00:39:34,400 Speaker 3: didn't publish at all. Recently, the National Institutes of Health 648 00:39:35,000 --> 00:39:38,680 Speaker 3: reinvestigated that and had access to the original data, so 649 00:39:38,719 --> 00:39:42,440 Speaker 3: they went back into the archives, they dug up the data, 650 00:39:42,520 --> 00:39:45,080 Speaker 3: and they did their own reanalysis of it without all 651 00:39:45,080 --> 00:39:47,040 Speaker 3: the preconceptions of the people who were running it in 652 00:39:47,080 --> 00:39:50,240 Speaker 3: the first place, which was to find that eating saturated 653 00:39:50,280 --> 00:39:54,560 Speaker 3: fat cause heart disease. What they found was in fact 654 00:39:54,560 --> 00:39:56,880 Speaker 3: the opposite. What they found was that when you properly 655 00:39:56,920 --> 00:40:00,000 Speaker 3: analyze the data, the people who had more heart disease, 656 00:40:00,239 --> 00:40:03,160 Speaker 3: and in fact the people who died more often. So 657 00:40:03,239 --> 00:40:05,880 Speaker 3: the higher mortality rate was with the people who were 658 00:40:06,000 --> 00:40:09,439 Speaker 3: not eating the standard saturated fat diet, the people who 659 00:40:09,480 --> 00:40:12,680 Speaker 3: were lowering the cholesterol, the people who were having less 660 00:40:12,680 --> 00:40:15,439 Speaker 3: fat and on actually had not just a higher rate 661 00:40:15,520 --> 00:40:18,960 Speaker 3: of cronary events leading to death, but a higher rate 662 00:40:19,040 --> 00:40:22,799 Speaker 3: of all causes death, meaning usually that is another way 663 00:40:22,840 --> 00:40:25,120 Speaker 3: of saying a lot more of them died of cancer 664 00:40:25,160 --> 00:40:29,000 Speaker 3: as well. So you know, we talked some other time 665 00:40:29,040 --> 00:40:32,480 Speaker 3: about why that was. But that's why having access to 666 00:40:32,520 --> 00:40:35,960 Speaker 3: the underlying data is really important, so that other scientists 667 00:40:36,600 --> 00:40:38,960 Speaker 3: can go back and have a look themselves and do 668 00:40:39,000 --> 00:40:41,440 Speaker 3: their own analysis and see if they agree with what 669 00:40:41,480 --> 00:40:42,239 Speaker 3: you came up with. 670 00:40:43,239 --> 00:40:46,120 Speaker 2: Yeah, yeah, well that makes Yeah. 671 00:40:46,480 --> 00:40:49,720 Speaker 1: I wish we could get that kind of second review 672 00:40:49,880 --> 00:40:51,840 Speaker 1: on a lot of research. 673 00:40:53,160 --> 00:40:58,160 Speaker 2: And being dependent on trusting. 674 00:40:57,719 --> 00:41:02,920 Speaker 1: People who have a ender, who have a financial incentive 675 00:41:02,960 --> 00:41:04,360 Speaker 1: to produce certain outcomes. 676 00:41:04,360 --> 00:41:07,279 Speaker 2: It's not like it doesn't work, just doesn't work. 677 00:41:07,320 --> 00:41:09,200 Speaker 1: I don't know if that's going to go away anytime, 678 00:41:09,239 --> 00:41:13,120 Speaker 1: because I know funding for research is not abundant and 679 00:41:13,520 --> 00:41:17,520 Speaker 1: institution's financial Academic institutions have got to stay afloat, so 680 00:41:18,160 --> 00:41:21,160 Speaker 1: they're never going to stop taking money but I don't 681 00:41:21,160 --> 00:41:23,280 Speaker 1: know what the solution is, so that other solution. 682 00:41:23,800 --> 00:41:27,600 Speaker 3: The solution is government money. It has to be fund 683 00:41:27,960 --> 00:41:30,600 Speaker 3: You have to have governments that are prepared to invest 684 00:41:30,680 --> 00:41:36,400 Speaker 3: in research and you know, truly independent money that doesn't 685 00:41:36,440 --> 00:41:39,960 Speaker 3: care about the outcome, that is prepared to pay, you know, 686 00:41:40,320 --> 00:41:45,160 Speaker 3: for agencies like the CSIRO for example, to exist. And 687 00:41:45,200 --> 00:41:48,160 Speaker 3: it always, you know, frustrates me every time I hear 688 00:41:48,200 --> 00:41:51,280 Speaker 3: that the CSIRO's funding is being cut yet again, because 689 00:41:51,320 --> 00:41:53,640 Speaker 3: what inevitably happens there is they have to go and 690 00:41:53,719 --> 00:41:56,800 Speaker 3: seek funding from the private sector. If they have two choices, 691 00:41:56,800 --> 00:41:59,239 Speaker 3: they either start firing people or they get funding from 692 00:41:59,280 --> 00:42:01,400 Speaker 3: the private sector. And the private sector is only going 693 00:42:01,400 --> 00:42:03,080 Speaker 3: to give them money if they produce the results they 694 00:42:03,120 --> 00:42:03,640 Speaker 3: want to see. 695 00:42:04,280 --> 00:42:09,239 Speaker 1: Hmmm, yeah, one hundred uh. The article is called the 696 00:42:09,239 --> 00:42:13,520 Speaker 1: Statin Delusion. His name is David Brian Kevin Patrick Gillespie. 697 00:42:13,800 --> 00:42:14,839 Speaker 1: It's on substack. 698 00:42:15,600 --> 00:42:15,839 Speaker 2: Yeah. 699 00:42:15,880 --> 00:42:17,920 Speaker 3: You can also get to it from Facebook or just 700 00:42:17,960 --> 00:42:20,200 Speaker 3: from my website. Just go to David Gillespie dot org 701 00:42:21,080 --> 00:42:23,600 Speaker 3: and you can get to it from there too. One 702 00:42:23,600 --> 00:42:25,600 Speaker 3: thing I want to say about this article, and I 703 00:42:25,719 --> 00:42:28,000 Speaker 3: mentioned it at the top, and just just to stop 704 00:42:28,040 --> 00:42:32,440 Speaker 3: you and I being sued Craig is. This is not 705 00:42:32,560 --> 00:42:36,520 Speaker 3: medical advice. I am a lawyer. Craig is whatever he is, 706 00:42:36,719 --> 00:42:41,800 Speaker 3: but he's not a doctor and this is not medical advice. 707 00:42:42,680 --> 00:42:47,000 Speaker 3: Before you do anything, assuming you want to, about taking 708 00:42:47,040 --> 00:42:50,080 Speaker 3: statins or not taking statins, you have a conversation with 709 00:42:50,120 --> 00:42:52,640 Speaker 3: your doctor and ask them about this. 710 00:42:54,239 --> 00:42:58,000 Speaker 2: Spoken authorized by David Gillespie, lawyer. Lawyer. 711 00:42:58,680 --> 00:43:00,960 Speaker 1: Yeah, and just for the record, but I disagree with 712 00:43:01,200 --> 00:43:02,239 Speaker 1: everything he said. 713 00:43:03,840 --> 00:43:05,120 Speaker 2: Just fucking with you, mate. 714 00:43:05,160 --> 00:43:07,720 Speaker 1: We'll say goodbye affair as always, but for the minute, 715 00:43:08,080 --> 00:43:10,320 Speaker 1: thank you again and happy New Year Champ. 716 00:43:10,760 --> 00:43:11,960 Speaker 3: Yeah, having new you to you too.