1 00:00:00,200 --> 00:00:03,720 Speaker 1: Thinking Sideways is not brought to you by Jerk pork Sausage. 2 00:00:04,320 --> 00:00:07,960 Speaker 1: Instead is supported by the generous contributions of people like you, 3 00:00:08,119 --> 00:00:12,360 Speaker 1: our listeners on Patreon. Visit patreon dot com slash thinking 4 00:00:12,400 --> 00:00:23,000 Speaker 1: sideways to learn more Thinking Sideways. I'm you never know 5 00:00:27,760 --> 00:00:30,440 Speaker 1: stories of things we simply don't know the answer too. 6 00:00:32,800 --> 00:00:35,800 Speaker 1: Hey there everybody, and welcome again to another episode of 7 00:00:35,840 --> 00:00:41,000 Speaker 1: Thinking Sideways. As the cat runs through the road, I 8 00:00:41,000 --> 00:00:44,800 Speaker 1: am I am Steve, as always, I am joined by 9 00:00:46,040 --> 00:00:49,000 Speaker 1: O and Devin. He was pointing at me, was it? 10 00:00:49,320 --> 00:00:50,920 Speaker 1: It was sort of pointing in between us. So I 11 00:00:50,960 --> 00:00:56,080 Speaker 1: just as always, we have another mystery for you. Uh, 12 00:00:56,120 --> 00:00:58,760 Speaker 1: this is a listener suggestion before I get too far in, 13 00:00:58,840 --> 00:01:01,240 Speaker 1: because we seem to be trying to forget mentioning that 14 00:01:01,240 --> 00:01:04,400 Speaker 1: their listeners suggestions. Lately, there's just too many suggestions. Sometimes 15 00:01:04,400 --> 00:01:07,479 Speaker 1: you just formissed that it's a suggestion. Yeah, well then 16 00:01:07,560 --> 00:01:13,520 Speaker 1: you suggestion by Joel. So Joel suggested the topic today, 17 00:01:13,560 --> 00:01:16,640 Speaker 1: which is the Glasgow effect, or you may see it 18 00:01:16,720 --> 00:01:20,640 Speaker 1: referred to as the Scottish effect. But it's more Glasgow 19 00:01:20,640 --> 00:01:25,119 Speaker 1: than anywhere else, right it is, and we're we're saying that, right, 20 00:01:25,720 --> 00:01:33,360 Speaker 1: I'm Glasgow. It's not Glasgow or like Glasgow. Listen, do 21 00:01:33,440 --> 00:01:36,560 Speaker 1: we have to go and start angry emails in the 22 00:01:36,600 --> 00:01:41,280 Speaker 1: first two minutes? You too? Yes, damn it. Well, this 23 00:01:41,319 --> 00:01:44,080 Speaker 1: mystery is a little bit different than normal. It's not 24 00:01:44,160 --> 00:01:48,560 Speaker 1: a murder mystery. There's there's a lot of death. It's 25 00:01:48,600 --> 00:01:53,840 Speaker 1: it's more of an unknown health situation, socioeconomic mystery. Maybe 26 00:01:54,000 --> 00:01:57,320 Speaker 1: I don't know how to classify it. Steve Special, it's 27 00:01:57,400 --> 00:02:00,559 Speaker 1: Steve Special. Actually, there we go. That to really appeared 28 00:02:00,560 --> 00:02:03,520 Speaker 1: to be all that socioeconomic. I think it's to do 29 00:02:03,560 --> 00:02:07,680 Speaker 1: with spoilers. Spoilers as we'll find out. All right, Well, 30 00:02:07,760 --> 00:02:11,200 Speaker 1: let's start by explaining the Glasgow Effect. Starting somewhere in 31 00:02:11,240 --> 00:02:14,520 Speaker 1: the your early two thousand's, a bunch of studies started 32 00:02:14,560 --> 00:02:19,840 Speaker 1: cropping up that we're talking about the unexplained poor health 33 00:02:20,200 --> 00:02:25,840 Speaker 1: uh and blow average life expectancy of the residents of Glasgow, Scotland. 34 00:02:26,160 --> 00:02:29,799 Speaker 1: The Glasgow effect is and I quote, a term used 35 00:02:29,800 --> 00:02:33,640 Speaker 1: to describe the higher levels of mortality and poor health 36 00:02:33,760 --> 00:02:38,440 Speaker 1: experienced in Scotland over and above the that explained by 37 00:02:38,840 --> 00:02:43,880 Speaker 1: socio economic circumstances. Evidence of this excess being concentrated in 38 00:02:44,000 --> 00:02:48,120 Speaker 1: West central Scotland has led to discussion of the more 39 00:02:48,400 --> 00:02:54,560 Speaker 1: specific Glasgow effect. Unquote, if anybody driving home hoping for 40 00:02:54,720 --> 00:02:58,680 Speaker 1: you know, something to keep them awake, this might not 41 00:02:58,760 --> 00:03:04,239 Speaker 1: be it. It's definitely more academic. If you're living in Glasgow, 42 00:03:04,320 --> 00:03:06,000 Speaker 1: is probably going to scare the crap out of you, 43 00:03:06,560 --> 00:03:08,840 Speaker 1: or you're already dead, one of the two. But you 44 00:03:08,960 --> 00:03:10,760 Speaker 1: know this is this is definitely much more of an 45 00:03:10,800 --> 00:03:14,280 Speaker 1: academic mystery than than our normal fair So it's a 46 00:03:14,280 --> 00:03:16,760 Speaker 1: good one for the people who listen and run at night. Yes, 47 00:03:17,840 --> 00:03:21,240 Speaker 1: the that quote before I interrupted you Sorry, yeah, well 48 00:03:21,440 --> 00:03:23,320 Speaker 1: I was just gonna say no, is that the quote 49 00:03:23,360 --> 00:03:25,480 Speaker 1: doesn't really do a good job of explaining it. So 50 00:03:25,520 --> 00:03:27,200 Speaker 1: let me try and break this down a little more 51 00:03:27,240 --> 00:03:33,680 Speaker 1: of Layman's term situation UM. Glasgow's mortality rates are considered 52 00:03:33,720 --> 00:03:37,840 Speaker 1: easily the highest in Britain, and they're among the highest 53 00:03:38,000 --> 00:03:42,840 Speaker 1: in Europe. Whether it's death from things like siro cirosis, 54 00:03:42,960 --> 00:03:49,840 Speaker 1: drug abuse, a cancer, murder, suicide, life expectancy at birth 55 00:03:49,960 --> 00:03:55,440 Speaker 1: in Glasgow is lower than average, and for men that 56 00:03:55,520 --> 00:03:58,360 Speaker 1: means that the men will live to be an average 57 00:03:58,360 --> 00:04:02,800 Speaker 1: of seventy one point six years, whereas everywhere else in 58 00:04:02,840 --> 00:04:06,280 Speaker 1: the UK they would normally live to an average of 59 00:04:06,360 --> 00:04:10,160 Speaker 1: seventy eight point two years, basically six year difference. And 60 00:04:10,200 --> 00:04:14,600 Speaker 1: also it's it's concentrated in certain areas of Glasgow too. 61 00:04:15,320 --> 00:04:18,440 Speaker 1: There's areas of Glasgow where a white male life expectancy 62 00:04:18,600 --> 00:04:22,440 Speaker 1: is fifty four, yeah, and other areas where the life 63 00:04:22,480 --> 00:04:26,080 Speaker 1: expectancy is actually like eighty three. Correct, So it's all 64 00:04:26,080 --> 00:04:27,479 Speaker 1: over the map. But that's you know, that's the thing 65 00:04:27,520 --> 00:04:30,000 Speaker 1: about statistics that you've got to average the whole thing. 66 00:04:30,800 --> 00:04:32,800 Speaker 1: But let's get back to this. So now if we 67 00:04:32,920 --> 00:04:38,880 Speaker 1: talk about women, they the average for women is four 68 00:04:39,000 --> 00:04:44,080 Speaker 1: years below the national average. So in Glasgow women will 69 00:04:44,120 --> 00:04:47,919 Speaker 1: are expected to average seventy eight years compared to in 70 00:04:47,960 --> 00:04:51,279 Speaker 1: the UK the average of eighty two point three. And 71 00:04:51,360 --> 00:04:55,080 Speaker 1: these are just to help frame it. That's these are significant, right, 72 00:04:55,120 --> 00:04:57,320 Speaker 1: it's not I mean there and they must be. They 73 00:04:57,360 --> 00:05:00,800 Speaker 1: must be significant enough that there's there's a total effects 74 00:05:00,880 --> 00:05:02,920 Speaker 1: named after it. But you know, when when you talk 75 00:05:02,960 --> 00:05:05,400 Speaker 1: about the difference of four years life expectancy, that doesn't 76 00:05:05,480 --> 00:05:09,000 Speaker 1: sound that outrageous. Okay, well let me know, so let 77 00:05:09,000 --> 00:05:11,320 Speaker 1: me try to break this down and so it makes 78 00:05:11,320 --> 00:05:14,440 Speaker 1: a little more sense than all right, you've got a 79 00:05:14,480 --> 00:05:17,839 Speaker 1: city that on its own people. And this is you know, 80 00:05:17,920 --> 00:05:20,760 Speaker 1: in the developed world, we've got a city where people 81 00:05:20,880 --> 00:05:25,000 Speaker 1: in general aren't living as long. Now. The easy thing, 82 00:05:25,080 --> 00:05:27,480 Speaker 1: and this is something that will come up in the theories, 83 00:05:27,640 --> 00:05:32,240 Speaker 1: is people say, oh, well, it's the impoverished, it's the poor. 84 00:05:32,480 --> 00:05:35,520 Speaker 1: They don't live a good lifestyle, they don't eat right, 85 00:05:35,560 --> 00:05:39,720 Speaker 1: so no wonder they die early. Well, it turns out 86 00:05:40,120 --> 00:05:44,279 Speaker 1: that the upper ten percent of the of Glasgow, the 87 00:05:44,320 --> 00:05:46,240 Speaker 1: people who are in that upper ten percent of the 88 00:05:47,279 --> 00:05:54,200 Speaker 1: economic bracket, they also die younger than their cohorts that significantly, yeah, 89 00:05:54,279 --> 00:05:57,599 Speaker 1: in in other cities. So it's not as if it's 90 00:05:57,680 --> 00:06:01,280 Speaker 1: this one demographic that's holding all the numbers down. And 91 00:06:01,320 --> 00:06:03,760 Speaker 1: that's what's got everybody kind of scratching their head is 92 00:06:04,160 --> 00:06:07,560 Speaker 1: wait a minute, So it's all across the board. It's 93 00:06:07,640 --> 00:06:12,479 Speaker 1: all walks of life. It's not just one group. They 94 00:06:12,520 --> 00:06:17,119 Speaker 1: should do some research on this they I bet they have. 95 00:06:18,279 --> 00:06:22,960 Speaker 1: I'm pretty sure I read some of it. Actually, um yeah, 96 00:06:23,000 --> 00:06:24,599 Speaker 1: well no, actually, you know, that's a good point to 97 00:06:24,600 --> 00:06:27,280 Speaker 1: bring up. There is a bunch of research on it. 98 00:06:27,480 --> 00:06:30,080 Speaker 1: And one of the places that I will cite because 99 00:06:30,120 --> 00:06:34,480 Speaker 1: they put out so much great information is the Glasgow 100 00:06:34,520 --> 00:06:38,320 Speaker 1: Center for population health. They have study after study after 101 00:06:38,320 --> 00:06:41,680 Speaker 1: study after study. If you want some good nighttime reading, 102 00:06:42,120 --> 00:06:46,040 Speaker 1: I have a couple of reports that are pages long 103 00:06:46,800 --> 00:06:52,600 Speaker 1: that are they are just they will deriveting. So the 104 00:06:52,640 --> 00:06:54,880 Speaker 1: people that are maintaining this side, are they all still alive? 105 00:06:55,600 --> 00:06:59,440 Speaker 1: I think, I guess won't that much longer, right, Yeah, No, 106 00:07:00,200 --> 00:07:02,400 Speaker 1: it's it's gonna be up for a while. Now that 107 00:07:02,440 --> 00:07:05,159 Speaker 1: we've kind of explained the mystery, there's a there's some 108 00:07:05,200 --> 00:07:08,080 Speaker 1: details we should probably give some people. Uh, first of which, 109 00:07:08,440 --> 00:07:12,200 Speaker 1: for folks who don't know Glasgow is in Scotland and 110 00:07:12,440 --> 00:07:16,040 Speaker 1: Scotland is part of the UK, it's what would you say, 111 00:07:16,080 --> 00:07:19,760 Speaker 1: it's about the upper third of the island. It's ballpark 112 00:07:19,960 --> 00:07:22,320 Speaker 1: that But with some people, you know, the geography isn't 113 00:07:22,360 --> 00:07:24,600 Speaker 1: there their gigs. So I just always try to point 114 00:07:24,640 --> 00:07:27,080 Speaker 1: that out to the island you're talking about. It's not 115 00:07:27,120 --> 00:07:31,120 Speaker 1: the UK though, right Britain. Yeah okay, oh yeah, no, 116 00:07:31,200 --> 00:07:33,520 Speaker 1: you're right. It would be Britain. Detail that's going to 117 00:07:33,560 --> 00:07:35,880 Speaker 1: point that out. Yes, you're absolutely right, you're right. I 118 00:07:35,920 --> 00:07:38,480 Speaker 1: would have I would have got us on that one. Uh. 119 00:07:38,680 --> 00:07:42,000 Speaker 1: For some there's I pulled census data because I figured 120 00:07:42,000 --> 00:07:44,920 Speaker 1: this would probably be important. It didn't turn out in 121 00:07:45,000 --> 00:07:46,960 Speaker 1: the long run to be as much as I wanted. 122 00:07:47,120 --> 00:07:50,080 Speaker 1: But there's something to keep in mind, which is Glasgow 123 00:07:50,120 --> 00:07:54,080 Speaker 1: is a really big city. Uh. The city itself is 124 00:07:54,480 --> 00:07:57,480 Speaker 1: sixty eight square miles, which is a d seventy five 125 00:07:57,560 --> 00:08:03,280 Speaker 1: square kilometers, but there is also the Greater Glasgow Urban 126 00:08:03,400 --> 00:08:06,360 Speaker 1: Area that means just all the area around the city 127 00:08:06,360 --> 00:08:09,520 Speaker 1: of Glasgow what we call the metro area, called the 128 00:08:09,560 --> 00:08:13,200 Speaker 1: metropolitan area, and that's a hundred forty two square miles 129 00:08:13,320 --> 00:08:18,240 Speaker 1: or three sixty square kilometers. Not nothing, No, it's it's 130 00:08:18,280 --> 00:08:21,040 Speaker 1: a big, big place. And according to the last census 131 00:08:21,120 --> 00:08:25,200 Speaker 1: in Glasgow, which when I pulled it was from there's 132 00:08:25,280 --> 00:08:28,680 Speaker 1: six hundred thousand people in the city. Now I census 133 00:08:28,720 --> 00:08:31,760 Speaker 1: that I pulled for the urban area was from two 134 00:08:31,760 --> 00:08:34,000 Speaker 1: thousand one, but at that point it was one point 135 00:08:34,000 --> 00:08:37,440 Speaker 1: two million people. So it's a big city. It's not 136 00:08:37,600 --> 00:08:41,120 Speaker 1: the biggest city in the world in terms of population density. 137 00:08:41,280 --> 00:08:44,160 Speaker 1: There's what did I figure it out here, There's like 138 00:08:45,040 --> 00:08:48,520 Speaker 1: hundred people per square mile or something like that, but 139 00:08:48,920 --> 00:08:54,160 Speaker 1: it is of Scotland's population lives in that city, so 140 00:08:54,240 --> 00:08:59,920 Speaker 1: it's it's kind of the major city. Yeah, A lot. Now, 141 00:09:00,040 --> 00:09:02,760 Speaker 1: I pointed out that there's the city of Glasgow and 142 00:09:02,800 --> 00:09:07,120 Speaker 1: then there's the Glasgow greater urban area. That's kind of 143 00:09:07,160 --> 00:09:10,960 Speaker 1: important to know because if you do ever go dig 144 00:09:11,000 --> 00:09:15,280 Speaker 1: into the studies, you'll see some studies refer to just 145 00:09:15,400 --> 00:09:18,360 Speaker 1: the city of Glasgow and some of them that pull 146 00:09:18,520 --> 00:09:22,600 Speaker 1: from the greater urban area. UM. Now, that's important because 147 00:09:22,640 --> 00:09:25,600 Speaker 1: it are they using the smaller pool of people or 148 00:09:25,640 --> 00:09:28,800 Speaker 1: the larger pool of people to to get their data 149 00:09:28,880 --> 00:09:35,360 Speaker 1: and to get their results. I've seen some conflicting reports, 150 00:09:35,400 --> 00:09:37,000 Speaker 1: but most of them, even when they pull it from 151 00:09:37,000 --> 00:09:40,640 Speaker 1: the greater urban area, the effects still seems to be present. 152 00:09:41,080 --> 00:09:42,840 Speaker 1: But it's something to be aware of. If you do 153 00:09:42,880 --> 00:09:46,120 Speaker 1: the reading statistics, you gotta love them if you can 154 00:09:46,160 --> 00:09:49,960 Speaker 1: work them. However, you need to the other bit of 155 00:09:49,960 --> 00:09:52,280 Speaker 1: technical information that you need to know here. If you 156 00:09:52,360 --> 00:09:55,120 Speaker 1: do go in any of the reporting, you're gonna see 157 00:09:55,120 --> 00:09:57,480 Speaker 1: a phrase which I believe it or not, took people 158 00:09:57,520 --> 00:10:01,360 Speaker 1: all the figure out, and that is excess deaths. I 159 00:10:01,400 --> 00:10:03,160 Speaker 1: didn't understand that. I was like, it wasn't every one 160 00:10:03,160 --> 00:10:06,360 Speaker 1: of them just neccess And yeah, now it turns out 161 00:10:06,400 --> 00:10:09,559 Speaker 1: that is the number above and beyond what the expected 162 00:10:09,679 --> 00:10:13,640 Speaker 1: average is gonna be. So we're gonna get into some 163 00:10:13,720 --> 00:10:17,280 Speaker 1: more sexy numbers here. I can see the look on 164 00:10:17,360 --> 00:10:25,640 Speaker 1: Devon's face. She is excited about percentages. Alrighty, So what 165 00:10:25,679 --> 00:10:29,240 Speaker 1: I'm gonna give you here is the percent of excess 166 00:10:29,400 --> 00:10:32,959 Speaker 1: deaths in the Glasgow area above and beyond what the 167 00:10:33,040 --> 00:10:35,440 Speaker 1: national average is. And this is going to be for 168 00:10:35,520 --> 00:10:39,760 Speaker 1: all age groups, so from zero to one hundred or 169 00:10:40,240 --> 00:10:44,040 Speaker 1: I guess it's one, but yeah, well I guess it 170 00:10:44,080 --> 00:10:47,760 Speaker 1: could be. Yeah, Well you get the point. So we 171 00:10:47,880 --> 00:10:52,079 Speaker 1: have above the average death of cancer is twenty three 172 00:10:53,840 --> 00:10:58,720 Speaker 1: the sorry, so it's uh that much above average? Right? 173 00:10:58,760 --> 00:11:01,720 Speaker 1: So average is zero in this case. Let's say the 174 00:11:01,840 --> 00:11:06,160 Speaker 1: average was a thousand. Okay, so there's an the average 175 00:11:06,200 --> 00:11:10,120 Speaker 1: of a thousand deaths a year from cancer is expected normal. 176 00:11:10,600 --> 00:11:13,120 Speaker 1: Then it would be two d and thirty two because 177 00:11:13,120 --> 00:11:17,319 Speaker 1: that's more more right. So yeah, I guess I was 178 00:11:17,360 --> 00:11:19,679 Speaker 1: saying that, like, you put average at zero, so the 179 00:11:21,400 --> 00:11:25,000 Speaker 1: is above average? Correct, got it? All? Right? So then 180 00:11:25,040 --> 00:11:28,880 Speaker 1: we have deaths from circulatory issues, which I would take 181 00:11:28,960 --> 00:11:33,200 Speaker 1: to mean things anywhere from heart attacks to strokes. But 182 00:11:33,520 --> 00:11:38,479 Speaker 1: that is five. I never actually got a good explanation 183 00:11:38,520 --> 00:11:42,000 Speaker 1: of what they meant by that, and then alcohol related 184 00:11:42,280 --> 00:11:45,720 Speaker 1: that is higher than expected, so that'd be alcoholism and 185 00:11:45,760 --> 00:11:49,760 Speaker 1: sorrosism and stuff like that. Any deaths related to alcohol, yes, 186 00:11:49,840 --> 00:11:53,120 Speaker 1: exactly does that? I'm sorry, does that include like car crashes? 187 00:11:54,160 --> 00:11:56,160 Speaker 1: To be quite honest, that is one of the things. 188 00:11:56,240 --> 00:12:00,400 Speaker 1: So there's a bunch of phrases used that are never 189 00:12:00,480 --> 00:12:03,360 Speaker 1: the same from one report to the next. So sometimes 190 00:12:03,360 --> 00:12:06,640 Speaker 1: it's a little difficult to know if you're comparing apples 191 00:12:06,640 --> 00:12:10,400 Speaker 1: to apples or apples to oranges. So I can't answer 192 00:12:10,920 --> 00:12:13,920 Speaker 1: exactly what it is. But if we do, if we 193 00:12:13,960 --> 00:12:16,840 Speaker 1: look at the numbers, and we were then to remove 194 00:12:17,000 --> 00:12:20,679 Speaker 1: anybody who is sixty five and over, as our British 195 00:12:20,679 --> 00:12:23,880 Speaker 1: friends like to say, the pensioners, you take them out, 196 00:12:24,400 --> 00:12:28,480 Speaker 1: and we have people who die from alcohol related issues, 197 00:12:28,640 --> 00:12:32,840 Speaker 1: only it's higher. So it seems like the younger generation 198 00:12:32,920 --> 00:12:36,400 Speaker 1: maybe is is boozing it up more. Um. And then 199 00:12:36,440 --> 00:12:39,319 Speaker 1: the other thing that's notable for that group is drug 200 00:12:39,360 --> 00:12:43,920 Speaker 1: related issues, which is seventeen percent higher than expected. Yeah, 201 00:12:44,000 --> 00:12:47,160 Speaker 1: although you know, I've I've read that they've done studies 202 00:12:47,200 --> 00:12:52,480 Speaker 1: and the other other comparable like, um, British towns, there's 203 00:12:52,480 --> 00:12:55,559 Speaker 1: actually uh, there's no more drinking in Glasgow than in 204 00:12:55,640 --> 00:12:59,199 Speaker 1: other towns. No. Actually, it turns out in Glasgow they 205 00:12:59,240 --> 00:13:03,480 Speaker 1: actually drink inc They have less binge drinking and it 206 00:13:03,520 --> 00:13:06,319 Speaker 1: seems like there's less drinking there than the other towns 207 00:13:06,280 --> 00:13:08,240 Speaker 1: of the talent that you're talking about that are in 208 00:13:08,280 --> 00:13:12,120 Speaker 1: the reports in the research, that's going to be Liverpool 209 00:13:12,320 --> 00:13:16,319 Speaker 1: and Manchester. Yeah, to be the favorite. Yeah, because well 210 00:13:16,320 --> 00:13:19,880 Speaker 1: they seem to through the data somehow they seem to 211 00:13:19,920 --> 00:13:22,720 Speaker 1: match up in terms of I'm guessing something to do 212 00:13:22,760 --> 00:13:26,720 Speaker 1: with population size and then the spectrum in terms of 213 00:13:27,679 --> 00:13:31,400 Speaker 1: demographics from you know, way below the poverty line to 214 00:13:31,559 --> 00:13:35,800 Speaker 1: making x an amount or more a year, probably similar 215 00:13:36,360 --> 00:13:41,600 Speaker 1: you know, male female ratios, all those and all that stuff. Yeah, 216 00:13:41,640 --> 00:13:43,760 Speaker 1: I mean I've got to presume that's why they would 217 00:13:43,760 --> 00:13:47,040 Speaker 1: be selected. Otherwise it wouldn't make any sense to select them. 218 00:13:47,160 --> 00:13:50,600 Speaker 1: Um that right there, though, Believe it or not, that's 219 00:13:50,600 --> 00:13:53,160 Speaker 1: one of our shortest mysteries, because that is the mystery, 220 00:13:53,240 --> 00:13:54,880 Speaker 1: is that we've got all these people who are just 221 00:13:55,040 --> 00:13:59,840 Speaker 1: dying younger than they should and we don't know why. 222 00:14:00,640 --> 00:14:02,160 Speaker 1: I don't know if you mentioned this. This this whole 223 00:14:02,160 --> 00:14:06,360 Speaker 1: thing actually started in about nineteen fifty. We haven't got 224 00:14:06,360 --> 00:14:08,679 Speaker 1: to that, but you're absolutely right, Yeah, you gonna mention that, 225 00:14:08,760 --> 00:14:10,320 Speaker 1: like we can do it and we can talk about 226 00:14:10,360 --> 00:14:12,160 Speaker 1: now that's not a problem at all. You're right, Joe. 227 00:14:12,240 --> 00:14:14,040 Speaker 1: And one of the things that I'm kind of intrigued 228 00:14:14,040 --> 00:14:17,640 Speaker 1: by since we're heading into theories anyways, and probably somebody 229 00:14:17,679 --> 00:14:19,640 Speaker 1: has thought to check this, but what are there any 230 00:14:19,640 --> 00:14:23,560 Speaker 1: major population movements starting about nineteen the whole bunch of 231 00:14:23,560 --> 00:14:25,440 Speaker 1: people move away or a whole bunch of people move in. 232 00:14:25,600 --> 00:14:30,400 Speaker 1: So there have been migrations. Um, Glasgow itself, it's always 233 00:14:30,480 --> 00:14:35,440 Speaker 1: been or traditionally it was a large industrial city and 234 00:14:35,480 --> 00:14:38,000 Speaker 1: they were known for a couple of things, one of 235 00:14:38,000 --> 00:14:41,160 Speaker 1: which was shipbuilding. That's what brought a lot of people 236 00:14:41,240 --> 00:14:44,360 Speaker 1: to the city. Um, there was a huge migration push 237 00:14:44,560 --> 00:14:47,560 Speaker 1: in the eighteen hundreds. There a lot of people came in. 238 00:14:48,080 --> 00:14:50,920 Speaker 1: And when you're in that, um what is that? That 239 00:14:51,000 --> 00:14:54,280 Speaker 1: era called the Industrial Revolution? Thank you that we're just 240 00:14:54,320 --> 00:14:56,200 Speaker 1: skipped right out of my head as soon as I wanted. 241 00:14:56,440 --> 00:14:59,040 Speaker 1: When the Industrial Revolution hit, you know, it's it's kind 242 00:14:59,080 --> 00:15:05,000 Speaker 1: of that trip typical growing city situation. Everybody came in 243 00:15:05,520 --> 00:15:09,320 Speaker 1: and it was a dirty, jammed, gross place, but they 244 00:15:09,360 --> 00:15:12,480 Speaker 1: made a lot of stuff and then, but also one 245 00:15:12,480 --> 00:15:14,840 Speaker 1: can presume not much more. I mean, it wasn't more 246 00:15:14,880 --> 00:15:18,720 Speaker 1: dirty or jammed than many other major cities that we No, No, 247 00:15:19,240 --> 00:15:21,960 Speaker 1: it wasn't. It wasn't in any way that I can 248 00:15:21,960 --> 00:15:26,760 Speaker 1: tell in the research crazier or more dangerous or dirtier 249 00:15:26,840 --> 00:15:30,040 Speaker 1: or anything like that. And it was kind of average. 250 00:15:30,040 --> 00:15:32,960 Speaker 1: You're right until Joe was saying, is that in the fifties, 251 00:15:33,640 --> 00:15:36,880 Speaker 1: And at that point that's when they started to see 252 00:15:36,920 --> 00:15:39,800 Speaker 1: that people were dying younger there than they should have. 253 00:15:40,600 --> 00:15:44,920 Speaker 1: At the same time, there was migration out of the area, 254 00:15:44,960 --> 00:15:48,600 Speaker 1: but there's also been migration into the area, because, like 255 00:15:48,600 --> 00:15:51,160 Speaker 1: I said, it started with ship building, and then they 256 00:15:51,200 --> 00:15:56,120 Speaker 1: had chemical processing and then I can't remember. I want 257 00:15:56,120 --> 00:15:57,880 Speaker 1: to say, it's a textile. I've got it somewhere in 258 00:15:57,880 --> 00:15:59,320 Speaker 1: my notes here. I'll find it in a bit. I 259 00:15:59,360 --> 00:16:01,960 Speaker 1: can't with the third industry was but there were three industries. 260 00:16:02,000 --> 00:16:04,200 Speaker 1: I thought it was like plutonium mining and handling or 261 00:16:04,240 --> 00:16:07,840 Speaker 1: something like that. It wasn't that, but that would just 262 00:16:07,880 --> 00:16:11,080 Speaker 1: be the answer. Then. But are clean industries, so it 263 00:16:11,120 --> 00:16:15,080 Speaker 1: makes sense that they're they're workers are likely to be sicker, 264 00:16:15,680 --> 00:16:19,280 Speaker 1: except that over time things clean up. But it's it's 265 00:16:19,280 --> 00:16:22,400 Speaker 1: no worse than any other industrial It shouldn't be any 266 00:16:22,440 --> 00:16:26,480 Speaker 1: worse than any other industrial towns. And that's that's again 267 00:16:26,520 --> 00:16:32,280 Speaker 1: the problem. Those industries started moving away. So as these 268 00:16:32,280 --> 00:16:34,960 Speaker 1: people who are now dying in their fifties and sixties, 269 00:16:35,320 --> 00:16:38,880 Speaker 1: they were probably born at a time when those industries 270 00:16:38,920 --> 00:16:41,280 Speaker 1: were just getting out of town. It doesn't necessarily mean 271 00:16:41,320 --> 00:16:43,920 Speaker 1: I mean something, so they should have been breathing or 272 00:16:43,960 --> 00:16:47,520 Speaker 1: anything that these nobody would spit out. The genetic donor 273 00:16:47,640 --> 00:16:51,400 Speaker 1: that created them, had something like that that caused their 274 00:16:51,680 --> 00:16:53,880 Speaker 1: you know, the DNA that they were given to reproduce 275 00:16:53,920 --> 00:16:57,920 Speaker 1: a way, that's something that they do know. But I mean, again, 276 00:16:58,000 --> 00:17:00,440 Speaker 1: this is like we're probably way into your theories at 277 00:17:00,440 --> 00:17:02,480 Speaker 1: this point. No, actually, no, this is this is actually 278 00:17:02,560 --> 00:17:04,480 Speaker 1: I'm glad Joe brought it up. I hadn't thought about 279 00:17:04,520 --> 00:17:06,320 Speaker 1: the fact that this is probably should be talked about 280 00:17:06,320 --> 00:17:08,400 Speaker 1: in the and the onset of this before we get 281 00:17:08,400 --> 00:17:11,320 Speaker 1: into theories. But yeah, you know, and and just so 282 00:17:11,480 --> 00:17:15,720 Speaker 1: people know, is that, yeah, people were coming in. The 283 00:17:15,760 --> 00:17:20,800 Speaker 1: cultural demographic of the area has changed over time. So 284 00:17:21,080 --> 00:17:25,160 Speaker 1: as with any any city, um, it's changed over time. 285 00:17:25,240 --> 00:17:28,960 Speaker 1: So it's a completely different gene pool now than it 286 00:17:29,080 --> 00:17:34,000 Speaker 1: was fifty and a hundred years at least statistically significant, Yes, 287 00:17:34,040 --> 00:17:37,160 Speaker 1: a significant, significant enough that I would I would say 288 00:17:37,160 --> 00:17:41,320 Speaker 1: it's notable. Um so that stuff has happened. And then yeah, no, 289 00:17:41,480 --> 00:17:44,960 Speaker 1: you know, the the economy has changed. All of the 290 00:17:45,080 --> 00:17:47,800 Speaker 1: big industries, most of the big industries. I think it's 291 00:17:47,880 --> 00:17:51,760 Speaker 1: sixties some percent of it started leaving as of I 292 00:17:51,800 --> 00:17:54,960 Speaker 1: think nineteen sixty or sixty one. They started leaving, and 293 00:17:54,960 --> 00:17:59,120 Speaker 1: it's you know, thirty some of what they originally had 294 00:17:59,240 --> 00:18:02,359 Speaker 1: is is industrial jobs. Is what's still there. They do 295 00:18:02,440 --> 00:18:04,600 Speaker 1: like to put those industries in places where the government's 296 00:18:04,640 --> 00:18:10,840 Speaker 1: care a little less about regulations. That's one reason. Um so, yeah, so, 297 00:18:10,920 --> 00:18:12,720 Speaker 1: I mean that's you know, that's had an effect on it, 298 00:18:12,720 --> 00:18:17,080 Speaker 1: which is why you see cultural migrations. Because if I 299 00:18:17,119 --> 00:18:21,520 Speaker 1: am a chip builder and there's no more ship building jobs, 300 00:18:21,800 --> 00:18:24,120 Speaker 1: I'm gonna go somewhere else where I can build ships, 301 00:18:24,840 --> 00:18:27,800 Speaker 1: make that money for building ships rather than flipping burgers 302 00:18:27,800 --> 00:18:29,960 Speaker 1: at a McDonald's or something. And then here's the deal, 303 00:18:30,160 --> 00:18:34,399 Speaker 1: is that the people that migrated out might have actually 304 00:18:34,400 --> 00:18:38,640 Speaker 1: been uh might have actually been a little smarter, little 305 00:18:38,640 --> 00:18:40,119 Speaker 1: more hard working. I don't want to I don't want 306 00:18:40,119 --> 00:18:43,560 Speaker 1: to offend anybody from Glasgow, but I don't think that 307 00:18:43,600 --> 00:18:46,800 Speaker 1: would have any effect on it. I don't know. You know, 308 00:18:46,840 --> 00:18:49,600 Speaker 1: actually would be a fascinating thing to study, but it 309 00:18:49,600 --> 00:18:52,840 Speaker 1: seems like it's mostly a health issue. Well you never know, 310 00:18:52,880 --> 00:18:54,800 Speaker 1: it might be a genetic issue, who knows. But it 311 00:18:54,840 --> 00:18:56,760 Speaker 1: would be interesting to track down all the people who 312 00:18:57,000 --> 00:19:01,160 Speaker 1: left Glasgow and see how long they lived. Leaving Glasgow 313 00:19:01,200 --> 00:19:05,600 Speaker 1: actually extend your lifespan. It seems like something that they 314 00:19:05,640 --> 00:19:08,320 Speaker 1: should have done and at some point. But I don't 315 00:19:08,320 --> 00:19:10,280 Speaker 1: know how easy that is though it would be tough 316 00:19:10,320 --> 00:19:12,320 Speaker 1: to track. What you need to do is you have to, 317 00:19:12,359 --> 00:19:19,480 Speaker 1: like on ancestry dot com that like, for fifty bucks 318 00:19:19,560 --> 00:19:22,359 Speaker 1: or whatever it is, we could figure this out. I 319 00:19:22,400 --> 00:19:26,119 Speaker 1: think I'm charging I'm charging to read the Wikipedia page 320 00:19:26,160 --> 00:19:30,040 Speaker 1: of you know, different cases right now. So, uh, I 321 00:19:30,040 --> 00:19:32,960 Speaker 1: think we'd charge more than fifty to solve this one. True. Yeah, 322 00:19:33,160 --> 00:19:37,119 Speaker 1: that sounds fair. Let's now that we've gone through that, 323 00:19:37,160 --> 00:19:39,480 Speaker 1: let's get into the theories, because I think that's that's 324 00:19:39,520 --> 00:19:43,280 Speaker 1: the next logical step for us. Um So we're going 325 00:19:43,320 --> 00:19:46,720 Speaker 1: to start with the first theory, which is poverty, because 326 00:19:46,960 --> 00:19:49,080 Speaker 1: as I said, that's the big one that you will 327 00:19:49,119 --> 00:19:52,840 Speaker 1: see people point at is that people who are in 328 00:19:52,920 --> 00:19:56,760 Speaker 1: a lower economic station in life, they don't have the money, 329 00:19:56,800 --> 00:19:59,280 Speaker 1: so they're not going to eat as well, they're gonna 330 00:19:59,400 --> 00:20:03,080 Speaker 1: do things that aren't good for them. So I'm gonna 331 00:20:03,119 --> 00:20:08,600 Speaker 1: work in those shipyards or in the platonium platonium holding 332 00:20:10,080 --> 00:20:12,560 Speaker 1: in here. Yeah, yeah, I mean that's just I mean, 333 00:20:12,600 --> 00:20:15,800 Speaker 1: that is just a reality that we know. Yeah, yeahs 334 00:20:15,920 --> 00:20:18,760 Speaker 1: things have changed. Yeah, and also just the stuff of 335 00:20:18,800 --> 00:20:21,600 Speaker 1: you know, the different stresses and the incredible toll that 336 00:20:21,600 --> 00:20:23,439 Speaker 1: that can take on your lifespan. Is if you know 337 00:20:23,560 --> 00:20:27,560 Speaker 1: you're living paycheck to paycheck, or in unstable housing, or 338 00:20:27,680 --> 00:20:30,480 Speaker 1: or if you're if you're on the doll as they say, 339 00:20:30,520 --> 00:20:34,480 Speaker 1: Because here's something to keep in mind is that in Glasgow, 340 00:20:35,040 --> 00:20:38,320 Speaker 1: one out of five people are out of work and 341 00:20:38,400 --> 00:20:43,280 Speaker 1: one out of four are getting assistance. So that's that's 342 00:20:43,320 --> 00:20:47,040 Speaker 1: a lot of joblessness, and that means that's a lot 343 00:20:47,080 --> 00:20:49,840 Speaker 1: of people, as you said, we're kind of scraping by. Yeah. 344 00:20:50,200 --> 00:20:52,040 Speaker 1: And the and the added stress on that I know, 345 00:20:52,440 --> 00:20:55,119 Speaker 1: we've they've done so many studies all over the world 346 00:20:55,160 --> 00:20:59,080 Speaker 1: on all that stress significantly affects the health levels that 347 00:20:59,119 --> 00:21:02,280 Speaker 1: you'll see. Yeah, we've and generations down and even actually 348 00:21:02,520 --> 00:21:05,000 Speaker 1: interesting fund side fact, I think I heard this on 349 00:21:05,080 --> 00:21:07,359 Speaker 1: like NPR or something like that, so I may have 350 00:21:07,440 --> 00:21:10,800 Speaker 1: my facts wrong. I'm just recalling, so please don't tell 351 00:21:10,840 --> 00:21:12,680 Speaker 1: me that I'm lying or anything like that. But I'm 352 00:21:12,680 --> 00:21:15,160 Speaker 1: pretty sure that they've done studies on the stress levels 353 00:21:15,200 --> 00:21:18,960 Speaker 1: of pregnant mothers and how it affects the obesity rate 354 00:21:19,280 --> 00:21:21,760 Speaker 1: of their children, which is so interesting. I actually have 355 00:21:21,840 --> 00:21:23,960 Speaker 1: some of that at this point, So that's yeah, no, 356 00:21:24,040 --> 00:21:26,480 Speaker 1: you're but you're on track. It does, it does make 357 00:21:26,480 --> 00:21:30,760 Speaker 1: a huge difference. Um, so let's talk about we talked 358 00:21:31,240 --> 00:21:33,280 Speaker 1: ahead and sorry, So I just mean that that's something 359 00:21:33,359 --> 00:21:35,680 Speaker 1: to keep in mind when you say, well, even if 360 00:21:35,800 --> 00:21:38,280 Speaker 1: you know the families are doing better and better, just 361 00:21:38,359 --> 00:21:40,720 Speaker 1: because that's the case, it doesn't mean that today doesn't 362 00:21:40,720 --> 00:21:46,640 Speaker 1: mean yea. Um, So if we take a look at 363 00:21:47,040 --> 00:21:49,320 Speaker 1: the history in Glasgow. You remember I told you there 364 00:21:49,359 --> 00:21:52,120 Speaker 1: was that big cultural migration in the eighteen hundreds. Well, 365 00:21:52,119 --> 00:21:56,679 Speaker 1: in the nineteen fifties there was this thought that we 366 00:21:56,760 --> 00:21:59,399 Speaker 1: need to build the city, we need to change the city, 367 00:21:59,400 --> 00:22:03,359 Speaker 1: and so the government actually built a bunch of high 368 00:22:03,480 --> 00:22:06,480 Speaker 1: rise tenement housing, kind of like we did here in 369 00:22:06,480 --> 00:22:08,280 Speaker 1: the States. And we die. Yeah, Chicago is the one 370 00:22:08,320 --> 00:22:10,639 Speaker 1: that comes to mind for me, and it was a 371 00:22:10,680 --> 00:22:15,439 Speaker 1: situation where it was government owned and these people were 372 00:22:15,480 --> 00:22:19,359 Speaker 1: living in it, and conditions weren't always healthy, they weren't clean. 373 00:22:19,400 --> 00:22:23,920 Speaker 1: I'm not blaming anybody for this, it's just what happened sometimes, 374 00:22:24,040 --> 00:22:27,200 Speaker 1: as we've seen all over the globe with this kind 375 00:22:27,200 --> 00:22:31,679 Speaker 1: of housing situation. So just to be clear, the comparison 376 00:22:31,840 --> 00:22:38,320 Speaker 1: is that this kind of housing would be the projects essentially. Yeah, yeah, yeah, 377 00:22:38,400 --> 00:22:43,399 Speaker 1: it's it's it's it becomes a slum in a way. Um, 378 00:22:43,440 --> 00:22:46,199 Speaker 1: you know that they've gone. They've now come back. I 379 00:22:46,240 --> 00:22:48,280 Speaker 1: think in the last twenty or thirty years they started 380 00:22:48,280 --> 00:22:52,920 Speaker 1: tearing those buildings down. They're trying to fix things up. Unfortunately, 381 00:22:53,040 --> 00:22:57,480 Speaker 1: it's left this poverty stricken area because if you can 382 00:22:57,600 --> 00:23:01,399 Speaker 1: afford not to live in that building, you're you're gonna escape. 383 00:23:01,440 --> 00:23:06,359 Speaker 1: You know, people flee that people who can't can't. And 384 00:23:06,400 --> 00:23:09,720 Speaker 1: so this is something that gets pointed out. It's more 385 00:23:09,760 --> 00:23:12,400 Speaker 1: of a you see it pointed out more than anywhere 386 00:23:12,400 --> 00:23:15,440 Speaker 1: else in the news reporting of this. When you get 387 00:23:15,480 --> 00:23:20,520 Speaker 1: into the actual data, it's it's actually admirable the amount 388 00:23:20,640 --> 00:23:24,359 Speaker 1: of work that every researcher does to just kick the 389 00:23:24,520 --> 00:23:28,560 Speaker 1: living crap out of this theory because they've taken they 390 00:23:28,640 --> 00:23:31,399 Speaker 1: if they take this what they it's referred to as 391 00:23:31,400 --> 00:23:34,880 Speaker 1: a socio economic factor. That means you're station in life, 392 00:23:34,880 --> 00:23:38,159 Speaker 1: your income level against the poverty line. And when they 393 00:23:38,200 --> 00:23:40,560 Speaker 1: balance through that and they take it out of the equation, 394 00:23:41,480 --> 00:23:45,480 Speaker 1: people in that area are still dying sooner than people 395 00:23:45,640 --> 00:23:48,720 Speaker 1: in similar cities with at the same time when they 396 00:23:48,720 --> 00:23:50,880 Speaker 1: take it and they put it in an evil, uh 397 00:23:51,000 --> 00:23:53,439 Speaker 1: even playing field. Yeah. That The thing about this, this 398 00:23:53,480 --> 00:23:57,600 Speaker 1: particular mystery is is U policy advocates usually, you know, 399 00:23:58,280 --> 00:23:59,680 Speaker 1: use it as an excuse to ride there on the 400 00:23:59,760 --> 00:24:03,240 Speaker 1: law abby horse. So if you're a big anti poverty advocate, 401 00:24:03,600 --> 00:24:05,600 Speaker 1: well you're going to jump right on this, you know. 402 00:24:05,680 --> 00:24:08,040 Speaker 1: And well and it seems like a really easy thing 403 00:24:08,080 --> 00:24:11,920 Speaker 1: to blame it on. Oh yeah, you know, really easy. Yeah, 404 00:24:11,960 --> 00:24:15,280 Speaker 1: I'm sorry. But the impoverished or what is it that 405 00:24:15,600 --> 00:24:18,960 Speaker 1: they get referred to? Disenfranchised I think is one of 406 00:24:19,000 --> 00:24:21,160 Speaker 1: the words that I've seen used. And there's another one. 407 00:24:21,240 --> 00:24:24,680 Speaker 1: I think that disenfranchise is kind of inappropriate though, well, 408 00:24:25,000 --> 00:24:28,720 Speaker 1: you know, isn't the word that I'm looking for. It's 409 00:24:28,920 --> 00:24:31,160 Speaker 1: it's in here. But there's a couple of different terms 410 00:24:31,160 --> 00:24:34,000 Speaker 1: that are used, but it is just basically it's pointing 411 00:24:34,040 --> 00:24:36,840 Speaker 1: at deprived all that stuff. Deprived, thank you. That was 412 00:24:36,880 --> 00:24:38,480 Speaker 1: the word that I was looking for. They call it 413 00:24:38,480 --> 00:24:41,560 Speaker 1: a deprived neighborhood. The Yeah, the term that you you 414 00:24:41,680 --> 00:24:45,159 Speaker 1: use in social work, at least in America is you 415 00:24:45,200 --> 00:24:47,679 Speaker 1: say that these people are experiencing this, not that they 416 00:24:47,720 --> 00:24:51,119 Speaker 1: are this. Oh it's a good point. Yeah, that somebody 417 00:24:51,240 --> 00:24:55,040 Speaker 1: is experiencing homelessness or experiencing poverty, not that they are 418 00:24:55,359 --> 00:24:57,600 Speaker 1: the poverty or they are homeless. And it's like you 419 00:24:57,640 --> 00:25:00,120 Speaker 1: know those people that are experiencing stab wounds and stuff 420 00:25:00,160 --> 00:25:07,920 Speaker 1: that kind. Yeah, okay, it's equally painful problem a lot 421 00:25:07,920 --> 00:25:10,920 Speaker 1: of times. But just as a you know, point of interest. 422 00:25:10,960 --> 00:25:15,879 Speaker 1: But yeah, and just because just because somebody's poor doesn't 423 00:25:16,680 --> 00:25:18,680 Speaker 1: I mean, I don't because you don't die, you don't 424 00:25:18,680 --> 00:25:20,800 Speaker 1: make that much money. But one of the things is 425 00:25:20,880 --> 00:25:22,600 Speaker 1: Joe said, is when you're an advocate of these things 426 00:25:22,600 --> 00:25:24,679 Speaker 1: and you really want to go after something, one of 427 00:25:24,680 --> 00:25:27,280 Speaker 1: the things that you'll see pointed out a lot is 428 00:25:27,440 --> 00:25:31,680 Speaker 1: you'll see you'll see behaviors. So eating behaviors will get 429 00:25:31,680 --> 00:25:35,720 Speaker 1: pointed at drinking behaviors and alcohol is what I'm getting 430 00:25:35,720 --> 00:25:39,960 Speaker 1: at here will be pointed at, and smoking and drugs, 431 00:25:40,040 --> 00:25:42,119 Speaker 1: so those those are things to get pointed out a 432 00:25:42,119 --> 00:25:46,320 Speaker 1: lot as well. It's this group that does that which 433 00:25:46,359 --> 00:25:49,760 Speaker 1: is not right. But that's why, that's why I say that. 434 00:25:49,840 --> 00:25:55,360 Speaker 1: I like so much every researcher that just went so 435 00:25:55,480 --> 00:25:58,199 Speaker 1: far to just obliterate this thing. That's good, you know, 436 00:25:58,200 --> 00:26:00,840 Speaker 1: because it is it's so easy to just say, even 437 00:26:00,840 --> 00:26:02,720 Speaker 1: as somebody who's trying to deal with this in their city, 438 00:26:02,760 --> 00:26:05,280 Speaker 1: to say, well, it's just those poor people, it's their fault. 439 00:26:05,560 --> 00:26:07,920 Speaker 1: We don't have to do anything. There's not actually anything wrong. 440 00:26:07,920 --> 00:26:10,160 Speaker 1: It's just these poor people. They are all their fault 441 00:26:10,560 --> 00:26:12,840 Speaker 1: and if their lifestyle, they just live that way and 442 00:26:12,840 --> 00:26:15,480 Speaker 1: then they die early and that's fine. So I'm glad 443 00:26:15,520 --> 00:26:19,480 Speaker 1: to hear that most researchers think that's bunk. Yeah, there's bunk. 444 00:26:20,119 --> 00:26:22,879 Speaker 1: Speaking of some bunk. Can we get onto the next theory? 445 00:26:23,160 --> 00:26:25,040 Speaker 1: I just wanted to point out the other The other 446 00:26:25,080 --> 00:26:27,480 Speaker 1: instance where this kind of association has made is in 447 00:26:27,520 --> 00:26:30,400 Speaker 1: the link between poverty and crime, which is a very 448 00:26:30,400 --> 00:26:34,320 Speaker 1: popular theory. Absolutely not based on anything. Yeah, yeah, I 449 00:26:34,320 --> 00:26:36,880 Speaker 1: mean not at all. I mean there ain't no link, 450 00:26:37,080 --> 00:26:41,320 Speaker 1: I mean no causal link anyway. Yeah, yeah, I agree. Yeah, 451 00:26:41,480 --> 00:26:42,800 Speaker 1: it's just a bunch of people want to come up 452 00:26:42,800 --> 00:26:44,160 Speaker 1: with a reason that, like, you know, get the government 453 00:26:44,200 --> 00:26:46,560 Speaker 1: to throw a bunch of money at poverty. Yeah. So 454 00:26:46,720 --> 00:26:50,119 Speaker 1: theory number two, Yeah, I actually put this in. I 455 00:26:50,160 --> 00:26:52,080 Speaker 1: put some of the theories in here in very specific 456 00:26:52,160 --> 00:26:54,360 Speaker 1: orders because I figured we have a lot of fun 457 00:26:54,400 --> 00:26:56,359 Speaker 1: with them. I like this one because I think it 458 00:26:56,400 --> 00:27:00,359 Speaker 1: might apply to us too. So the next theory that 459 00:27:00,440 --> 00:27:05,840 Speaker 1: we have is that it is due to vitamin D deficiency, 460 00:27:06,520 --> 00:27:10,119 Speaker 1: meaning okay, well, if you ever look at the weather 461 00:27:10,359 --> 00:27:14,879 Speaker 1: for that area you hear about in in England, it 462 00:27:15,040 --> 00:27:17,800 Speaker 1: is gloomy, it is gray, it is rainy. You don't 463 00:27:17,840 --> 00:27:21,240 Speaker 1: hear about how sunny and warm it is all the time. 464 00:27:21,600 --> 00:27:24,800 Speaker 1: So it's an it's it's a very easy anecdote to make, 465 00:27:24,880 --> 00:27:28,000 Speaker 1: and you actually only ever see it refer to anecdotally, 466 00:27:28,000 --> 00:27:30,520 Speaker 1: always see or it could be this, and then they 467 00:27:30,560 --> 00:27:33,119 Speaker 1: go on to the next thing. They never actually explain it. 468 00:27:33,640 --> 00:27:35,920 Speaker 1: My total problem with this theory is if it was 469 00:27:36,040 --> 00:27:40,600 Speaker 1: vitamin D deficiency, we should see this in other places, 470 00:27:40,880 --> 00:27:45,119 Speaker 1: namely where we live as a giant part of Russia. Yeah, 471 00:27:45,160 --> 00:27:47,680 Speaker 1: where this should be happening all the time, where it's 472 00:27:47,720 --> 00:27:51,119 Speaker 1: cold and cloudy and crutty, well a lot of the time, 473 00:27:51,320 --> 00:27:53,679 Speaker 1: you know, I think they could they could answer this one. 474 00:27:53,720 --> 00:27:57,240 Speaker 1: And they need to select a thousand residents of Glasgow 475 00:27:57,920 --> 00:28:00,679 Speaker 1: and just grab him, you know, put him in calicars 476 00:28:00,680 --> 00:28:02,439 Speaker 1: and take them somewhere sunny and just make them live 477 00:28:02,480 --> 00:28:04,119 Speaker 1: there for fifty or six Do you know how they 478 00:28:04,160 --> 00:28:05,840 Speaker 1: do it is they just put vitamin D in the 479 00:28:05,880 --> 00:28:08,080 Speaker 1: drinking water. And that's what would be another thing to do. 480 00:28:08,200 --> 00:28:11,720 Speaker 1: I think you can do that, right, they do it before. Yeah, 481 00:28:11,880 --> 00:28:14,240 Speaker 1: well but they're different, I mean, you know, the different molecules, 482 00:28:14,240 --> 00:28:16,040 Speaker 1: and also they don't do that here. So calm down. 483 00:28:17,040 --> 00:28:20,720 Speaker 1: Like I like vitamin D efficiency because I I once 484 00:28:20,760 --> 00:28:22,560 Speaker 1: head a doctor who said, well, if you're gonna live 485 00:28:22,560 --> 00:28:25,360 Speaker 1: in Portland, you should definitely take at least five milligrams 486 00:28:25,480 --> 00:28:29,720 Speaker 1: vitamin D a day year round. And I thought, Okay, 487 00:28:30,240 --> 00:28:35,080 Speaker 1: I guess I could do that. Okay, okay, And I'm 488 00:28:35,119 --> 00:28:37,919 Speaker 1: down on the whole vitamin thing, Okay, not buying it. 489 00:28:38,160 --> 00:28:41,520 Speaker 1: So let's move to the next theory, which is poor 490 00:28:41,640 --> 00:28:45,720 Speaker 1: diet equals poor health, which logically makes sense and we 491 00:28:45,840 --> 00:28:48,200 Speaker 1: kind of talked about that under poverty. Well we did 492 00:28:48,800 --> 00:28:50,640 Speaker 1: in a different way, right, but in a different way 493 00:28:50,680 --> 00:28:53,680 Speaker 1: because this this does actually come to some of the stuff. 494 00:28:53,720 --> 00:28:55,320 Speaker 1: This is where some of the stuff that Devon was 495 00:28:55,320 --> 00:28:58,040 Speaker 1: talking about actually comes in. And there's there's a couple 496 00:28:58,120 --> 00:29:02,120 Speaker 1: of different ways that this can be earned. Um, it 497 00:29:02,240 --> 00:29:06,480 Speaker 1: is a known fact that people in Glasgow do have 498 00:29:07,080 --> 00:29:11,760 Speaker 1: greens available to them, but they don't eat them as often. 499 00:29:11,960 --> 00:29:15,200 Speaker 1: So in other words, it's it's not that the healthy 500 00:29:15,240 --> 00:29:19,320 Speaker 1: food isn't available, it's that it is not chosen interesting, 501 00:29:19,360 --> 00:29:24,440 Speaker 1: and that's across all different socio demographics as an average Okay, 502 00:29:24,440 --> 00:29:28,760 Speaker 1: well we're talking. We are talking in averages. So that 503 00:29:28,800 --> 00:29:30,600 Speaker 1: would be something interesting to check out, would be to 504 00:29:30,600 --> 00:29:33,440 Speaker 1: go to go to grocery stores in Glasgow and check 505 00:29:33,440 --> 00:29:36,160 Speaker 1: out the vegetable apartment. You would expect it to be smaller, 506 00:29:36,520 --> 00:29:40,200 Speaker 1: significantly smaller than in other cities because of the line demand. 507 00:29:40,360 --> 00:29:43,120 Speaker 1: And then you would also expect that that that would 508 00:29:43,160 --> 00:29:45,720 Speaker 1: probably have like a cause and effect sort of situation 509 00:29:45,800 --> 00:29:49,640 Speaker 1: where people would buy it less, so they'd be less available. 510 00:29:50,240 --> 00:29:52,880 Speaker 1: So people would buy it less because it's less available, 511 00:29:53,640 --> 00:29:58,240 Speaker 1: diminishing returns, yes, no, no, absolutely, and then and then 512 00:29:58,280 --> 00:30:01,640 Speaker 1: there's the flip side, which is everybody points out you 513 00:30:01,680 --> 00:30:05,120 Speaker 1: shouldn't be eating so many processed foods. Don't buy the 514 00:30:05,160 --> 00:30:08,959 Speaker 1: frozen pizzas and the burritos just because they're fast. And 515 00:30:09,360 --> 00:30:12,200 Speaker 1: yeah it says it's a veggie egg roll, but it's 516 00:30:12,200 --> 00:30:15,960 Speaker 1: still processed to the end degree. So that is one 517 00:30:15,960 --> 00:30:17,920 Speaker 1: of the things that gets pointed at is that there's 518 00:30:18,280 --> 00:30:22,360 Speaker 1: this is what's happening and if that was such a problem, 519 00:30:22,640 --> 00:30:28,280 Speaker 1: then we should have huge rates of obesity and diabetes 520 00:30:28,680 --> 00:30:34,600 Speaker 1: in that region in the Glasgow, except that again it's 521 00:30:34,680 --> 00:30:38,120 Speaker 1: not anywhere above and beyond what would be expected of 522 00:30:38,400 --> 00:30:42,840 Speaker 1: the average. As a matter of fact, yes, the obesity 523 00:30:42,920 --> 00:30:47,440 Speaker 1: rate is actually lower in Glasgow than the other cities 524 00:30:47,760 --> 00:30:52,160 Speaker 1: in the in Britain. That that doesn't pan out. The 525 00:30:52,240 --> 00:30:55,160 Speaker 1: math on that doesn't work. It's not necessarily any worse. Okay, 526 00:30:55,520 --> 00:30:59,760 Speaker 1: I guess, yeah that's probably true. Yeah, yeah, I mean 527 00:30:59,800 --> 00:31:01,720 Speaker 1: it's struggle with that. Then it's like on the flip side, 528 00:31:01,760 --> 00:31:03,160 Speaker 1: it's like, does that mean that you actually have a 529 00:31:03,200 --> 00:31:06,440 Speaker 1: lot of malnourished people? Right? If you don't have a 530 00:31:06,480 --> 00:31:09,440 Speaker 1: lot of obese people, but we know that they aren't eating, well, 531 00:31:09,480 --> 00:31:11,640 Speaker 1: does that mean that actually the people who should be 532 00:31:11,680 --> 00:31:15,880 Speaker 1: obese are just malnourished, and so that's something else that's 533 00:31:15,880 --> 00:31:18,560 Speaker 1: going on there. But that seems like that would be 534 00:31:18,640 --> 00:31:20,400 Speaker 1: like the first thing that you would do as a 535 00:31:20,440 --> 00:31:23,680 Speaker 1: research scientist to saying, oh, look at how malnourished these 536 00:31:23,720 --> 00:31:26,080 Speaker 1: people are. Although I would agree with that to argue 537 00:31:26,080 --> 00:31:31,040 Speaker 1: against myself, I also don't think that a lot of 538 00:31:31,080 --> 00:31:35,400 Speaker 1: people realize that they're malnourished necessarily. I think if in 539 00:31:35,480 --> 00:31:38,000 Speaker 1: terms of mild cases of malnourishment, obviously, right, we're not 540 00:31:38,040 --> 00:31:41,040 Speaker 1: talking like African children who are literally starving to death. 541 00:31:41,040 --> 00:31:43,800 Speaker 1: We're talking about adults who are just living on food 542 00:31:43,840 --> 00:31:45,880 Speaker 1: they shouldn't be living on, not getting the nutrients they 543 00:31:45,920 --> 00:31:49,920 Speaker 1: should be. You just feel kind of tired and run 544 00:31:50,000 --> 00:31:53,160 Speaker 1: down and grumpy and you know all that stuff. But 545 00:31:53,240 --> 00:31:54,840 Speaker 1: I don't know that you would necessarily go to the 546 00:31:54,880 --> 00:31:57,160 Speaker 1: doctor and the doctor would say, well, what exactly are 547 00:31:57,160 --> 00:32:00,440 Speaker 1: you eating? Oh, you might be malnoursed. That that would 548 00:32:00,480 --> 00:32:03,400 Speaker 1: be the kind of thing that would come out in Uh, 549 00:32:03,760 --> 00:32:07,240 Speaker 1: it's self reported happiness is one of the things. That's 550 00:32:07,280 --> 00:32:08,760 Speaker 1: one of the things that you'll say are if they 551 00:32:08,800 --> 00:32:10,760 Speaker 1: do study that, it's one of the things that is 552 00:32:10,760 --> 00:32:12,800 Speaker 1: studied and one of the things that has asked. But 553 00:32:13,400 --> 00:32:17,680 Speaker 1: the funny thing about self reported happiness is that people 554 00:32:18,040 --> 00:32:22,120 Speaker 1: almost always, as an average, unless there's, you know, a 555 00:32:22,160 --> 00:32:25,400 Speaker 1: giant meltdown in the area, I think they report on 556 00:32:25,440 --> 00:32:28,080 Speaker 1: average something like six and a half to eight. Yeah, 557 00:32:28,800 --> 00:32:33,120 Speaker 1: it's no range. So unless the city has just burned down, 558 00:32:33,160 --> 00:32:37,040 Speaker 1: everybody's like, yeah, seven. So okay, this is um. I'm 559 00:32:37,040 --> 00:32:39,120 Speaker 1: going to use some anecdote that has nothing to do 560 00:32:39,160 --> 00:32:41,600 Speaker 1: with this to prove a point I have had Tonight's 561 00:32:41,680 --> 00:32:45,600 Speaker 1: my entire life. I hear ringing in my ears far yeah, 562 00:32:45,640 --> 00:32:47,840 Speaker 1: all the time, as for literally as long as I 563 00:32:47,880 --> 00:32:52,120 Speaker 1: can remember. And I thought, literally until like five years ago, 564 00:32:52,640 --> 00:32:56,040 Speaker 1: that was a thing that everybody had. No I genuinely did. 565 00:32:56,040 --> 00:32:59,440 Speaker 1: I thought everybody they have had this conversation. So I 566 00:32:59,480 --> 00:33:01,600 Speaker 1: think there's also some argument to be made. I think 567 00:33:01,640 --> 00:33:04,160 Speaker 1: that's a bit of human nature. I think a lot 568 00:33:04,160 --> 00:33:07,480 Speaker 1: of people kind of feel that way, especially awkward people, 569 00:33:07,680 --> 00:33:11,080 Speaker 1: especially uh, you know, people from the United Kingdom who 570 00:33:11,080 --> 00:33:15,440 Speaker 1: are stereotypically awkward. I'm kidding, I'm sorry, no, but I 571 00:33:15,440 --> 00:33:17,640 Speaker 1: think that's a human Part two is to just say, well, 572 00:33:17,920 --> 00:33:19,920 Speaker 1: maybe I feel tired, but maybe this is just how 573 00:33:19,960 --> 00:33:22,600 Speaker 1: people feel. I don't know, and if a lot of 574 00:33:22,600 --> 00:33:25,160 Speaker 1: people around you are feeling that way, I'm just going 575 00:33:25,200 --> 00:33:30,280 Speaker 1: to keep arguing. You guys, stop me. So I think 576 00:33:30,320 --> 00:33:31,560 Speaker 1: they just need to give them all a lot of 577 00:33:31,560 --> 00:33:35,280 Speaker 1: itemins clear it all up. It's possible. But is there 578 00:33:35,320 --> 00:33:38,360 Speaker 1: is there any evidence that actually people in Glasgow eat 579 00:33:38,360 --> 00:33:41,960 Speaker 1: any worse than people in say Chicago or London or Manchester. 580 00:33:42,360 --> 00:33:46,000 Speaker 1: I can see yeah, no, I mean it's again, if 581 00:33:46,040 --> 00:33:49,840 Speaker 1: they were eating that badly, it should show up in 582 00:33:50,160 --> 00:33:55,360 Speaker 1: other very easy to identify health issues. But but those 583 00:33:55,400 --> 00:33:59,440 Speaker 1: things that they're looking for specifically aren't showing up. So 584 00:33:59,520 --> 00:34:02,960 Speaker 1: that's why it appears to not be such a poor 585 00:34:03,080 --> 00:34:06,720 Speaker 1: diet issue. Now, part of the diet is, of course, 586 00:34:06,920 --> 00:34:09,640 Speaker 1: like we talked about, there is the consideration of how 587 00:34:09,719 --> 00:34:13,279 Speaker 1: much do people drinking smoke. We talked about the fact 588 00:34:13,440 --> 00:34:17,399 Speaker 1: that people in Glasgow appear to actually drink less than 589 00:34:17,840 --> 00:34:24,720 Speaker 1: the other British cities. Maybe that's the problem we also 590 00:34:24,880 --> 00:34:28,120 Speaker 1: have in there, something we briefly touched on in the beginning, 591 00:34:28,320 --> 00:34:31,360 Speaker 1: and this is also it kind of got lumped into 592 00:34:31,520 --> 00:34:38,040 Speaker 1: the diet, but that's drug use. Turns out the drug 593 00:34:38,200 --> 00:34:43,480 Speaker 1: of choice is of all things heroin, What do you 594 00:34:43,520 --> 00:34:46,080 Speaker 1: mean of all things? It's like literally the most addictive 595 00:34:46,080 --> 00:34:48,799 Speaker 1: thing you could ever do. It's the worst damn thing 596 00:34:48,840 --> 00:34:52,520 Speaker 1: that you could ever do, because people do well, I 597 00:34:52,520 --> 00:34:54,319 Speaker 1: don't know, people who get on heroin to have a 598 00:34:54,320 --> 00:34:57,040 Speaker 1: pretty hard time and it it rides them for a 599 00:34:57,160 --> 00:35:00,720 Speaker 1: lot longer. People can go a lot longer falling down 600 00:35:00,840 --> 00:35:04,160 Speaker 1: the well to hit bottom, at least in the people 601 00:35:04,239 --> 00:35:08,680 Speaker 1: that I've known. Then people on meth because tweakers are 602 00:35:08,719 --> 00:35:11,560 Speaker 1: easy to spot and they usually burn out and get 603 00:35:11,600 --> 00:35:17,360 Speaker 1: themselves caught pretty fast, whereas it's people on heroin, it's 604 00:35:17,560 --> 00:35:20,120 Speaker 1: kind of a you know, it's chasing the dragon. I 605 00:35:20,120 --> 00:35:22,279 Speaker 1: believe it's what is what they refer to it as. 606 00:35:22,920 --> 00:35:25,520 Speaker 1: But either way, I mean, both of those drugs they 607 00:35:25,600 --> 00:35:29,680 Speaker 1: kill people, they do terrible things to and that there 608 00:35:29,719 --> 00:35:34,040 Speaker 1: are things that get looked at. Eence that people in 609 00:35:34,080 --> 00:35:36,719 Speaker 1: Glasgow do more hair I wanted other people, not that 610 00:35:36,800 --> 00:35:40,480 Speaker 1: I can find. I mean, drugs are an issue. If 611 00:35:40,520 --> 00:35:43,360 Speaker 1: we if we go back to that stat from the 612 00:35:43,440 --> 00:35:50,520 Speaker 1: beginning with the excess deaths, yeah and under it was 613 00:35:52,480 --> 00:35:57,680 Speaker 1: good memory. So I mean obviously there's something going on. Well, 614 00:35:57,719 --> 00:36:00,879 Speaker 1: it is true. I mean heroin is Whitely touted as 615 00:36:00,920 --> 00:36:03,239 Speaker 1: literally the most addictive drug. I'm not I'm not just 616 00:36:03,440 --> 00:36:06,560 Speaker 1: like saying that. The thing they do studies on it. 617 00:36:06,560 --> 00:36:08,720 Speaker 1: It's you know, people get addicted way faster to heroine 618 00:36:08,719 --> 00:36:11,399 Speaker 1: than they do to most other drugs, and especially if 619 00:36:12,000 --> 00:36:14,600 Speaker 1: there is a higher usage. Again we're saying we don't 620 00:36:14,600 --> 00:36:16,759 Speaker 1: actually know if there's a higher usage or not, but 621 00:36:17,160 --> 00:36:19,560 Speaker 1: it seems like, you know, four of your friends are 622 00:36:19,600 --> 00:36:22,839 Speaker 1: doing it and they seem fine, Well, maybe you'll try 623 00:36:22,880 --> 00:36:24,759 Speaker 1: it too, because you know your life's not going so 624 00:36:24,800 --> 00:36:27,440 Speaker 1: great and you want to high. So that addiction can 625 00:36:27,520 --> 00:36:33,160 Speaker 1: kind of you know, snowball, Yeah, that much greater. Yeah, No, 626 00:36:33,280 --> 00:36:36,719 Speaker 1: it's I I've known several people who have managed to 627 00:36:36,800 --> 00:36:40,200 Speaker 1: kick it, and both of them were deathly afraid of it, 628 00:36:40,239 --> 00:36:42,440 Speaker 1: and one of them to the point that of getting 629 00:36:42,480 --> 00:36:46,960 Speaker 1: addicted to anything that for years she wouldn't take any medication. 630 00:36:47,680 --> 00:36:50,840 Speaker 1: And it turned out years later she was you know, 631 00:36:50,960 --> 00:36:55,440 Speaker 1: found out through health issues what had actually done. And 632 00:36:55,520 --> 00:36:57,359 Speaker 1: I mean, you know, she was on it for only 633 00:36:57,400 --> 00:37:00,680 Speaker 1: a couple of years. So stuff does. And that's part 634 00:37:00,719 --> 00:37:02,520 Speaker 1: of the reason that I bring up the heroine is 635 00:37:02,600 --> 00:37:07,200 Speaker 1: that it can have a long range effects. So even 636 00:37:07,239 --> 00:37:08,920 Speaker 1: if somebody does it for a couple of years and 637 00:37:08,920 --> 00:37:12,239 Speaker 1: then is lucky enough to kick it, gets the help 638 00:37:12,320 --> 00:37:15,439 Speaker 1: they need and gets off of it. It still can 639 00:37:15,600 --> 00:37:19,839 Speaker 1: have done the damage that nobody knows right away, and 640 00:37:19,840 --> 00:37:24,240 Speaker 1: then five, ten, twenty years down the line, those effects 641 00:37:24,360 --> 00:37:27,239 Speaker 1: wear their ugly head. Yeah and again. But again it 642 00:37:27,280 --> 00:37:30,560 Speaker 1: does seem like you know, I mean, they know they 643 00:37:30,600 --> 00:37:35,200 Speaker 1: do demographic studies on is this area, you know, the 644 00:37:35,280 --> 00:37:39,120 Speaker 1: Scotland capital of Heroin. I mean, it may very well be, 645 00:37:39,200 --> 00:37:44,239 Speaker 1: but that seems like something they would mention. Yeah, I don't. 646 00:37:44,280 --> 00:37:46,520 Speaker 1: I don't see any evidence to that. No, I don't either, 647 00:37:46,680 --> 00:37:49,640 Speaker 1: But but it's it's the drug that you get that 648 00:37:49,719 --> 00:37:52,239 Speaker 1: always gets brought up. So that's why I wanted to 649 00:37:52,239 --> 00:37:56,920 Speaker 1: bring it up, so that we're not leaving anything behind. Okay. 650 00:37:57,160 --> 00:37:58,600 Speaker 1: Another thing that seems to be killing a lot of 651 00:37:58,600 --> 00:38:01,000 Speaker 1: people as murder. Yes, yeah, it used to be in 652 00:38:01,000 --> 00:38:04,520 Speaker 1: the murder capital of Western Europe. He was at one point. Yeah, yeah, 653 00:38:04,640 --> 00:38:07,680 Speaker 1: but now some murder has gone down. I understand quite, 654 00:38:07,800 --> 00:38:11,160 Speaker 1: but it was it was murders that were guns are illegal, 655 00:38:11,520 --> 00:38:13,680 Speaker 1: so they can't have a gun there, so it was 656 00:38:13,800 --> 00:38:17,600 Speaker 1: knife things or beatings and stuff like that. So I'm 657 00:38:17,600 --> 00:38:20,040 Speaker 1: just like for people in the US, when you hear 658 00:38:20,400 --> 00:38:25,160 Speaker 1: murder capital, we always automatically assume that they were shooting everybody, 659 00:38:25,400 --> 00:38:27,560 Speaker 1: which is not the case. I just want to get 660 00:38:27,600 --> 00:38:29,520 Speaker 1: that on the table so we know what we're talking about, 661 00:38:29,520 --> 00:38:32,480 Speaker 1: put it into proper context. I mean, people can get 662 00:38:32,520 --> 00:38:37,399 Speaker 1: illegal guns. There are murders, sarcastic air quotes. It's not 663 00:38:37,440 --> 00:38:41,000 Speaker 1: as rampant. Yeah, on the ship for possession, I should 664 00:38:41,040 --> 00:38:45,040 Speaker 1: say possession of firearms is not nearly as rampant or 665 00:38:45,080 --> 00:38:48,440 Speaker 1: prevalent as it is here. I think two of the 666 00:38:48,440 --> 00:38:51,960 Speaker 1: three of us have guns in our home. Yeah, so 667 00:38:52,000 --> 00:38:54,080 Speaker 1: it's pretty I mean, it's pretty strong statistic not to 668 00:38:54,120 --> 00:38:57,120 Speaker 1: say that, you know, all Americans are like, I have guns. Yeah, 669 00:38:57,160 --> 00:39:01,319 Speaker 1: Well there's Texas, but there's that, and then there's the 670 00:39:01,320 --> 00:39:04,200 Speaker 1: rest of the United States. But I mean I think 671 00:39:04,280 --> 00:39:08,800 Speaker 1: that's that's a pretty fair statistical thing. Yeah. Here in 672 00:39:08,840 --> 00:39:10,800 Speaker 1: the West, I mean a lot of people own guns. 673 00:39:10,840 --> 00:39:14,319 Speaker 1: I know towns of people that own guns. Yeah, but 674 00:39:14,800 --> 00:39:19,840 Speaker 1: I mean that's about what. Let's move on to another theory. 675 00:39:19,880 --> 00:39:23,120 Speaker 1: All right, let's move on to a awesome theory. This 676 00:39:23,160 --> 00:39:24,799 Speaker 1: is another one you just kept in here for fun. 677 00:39:24,880 --> 00:39:28,760 Speaker 1: Is I didn't totally did uh, and that is that 678 00:39:29,080 --> 00:39:32,640 Speaker 1: the theory is the cause is an environmental factor and 679 00:39:32,680 --> 00:39:36,799 Speaker 1: that's temperature. I'm not buying this one. Let me tell 680 00:39:36,800 --> 00:39:39,520 Speaker 1: people about first time. Come on, man, don't don't don't 681 00:39:39,640 --> 00:39:41,560 Speaker 1: build it up then tear it down. Is what you 682 00:39:41,640 --> 00:39:45,319 Speaker 1: told me before. Okay, Okay, So it turns out that 683 00:39:45,640 --> 00:39:50,240 Speaker 1: it is actually pretty chilly in in Glasgow in the winter. 684 00:39:50,600 --> 00:39:55,880 Speaker 1: The highs as an average are five degrees celsius or 685 00:39:56,200 --> 00:40:00,680 Speaker 1: forty four degrees fahrenheit five degrees celsius. I'm just doing 686 00:40:00,719 --> 00:40:02,800 Speaker 1: a little writh of take that sounds right. Put it 687 00:40:02,840 --> 00:40:06,920 Speaker 1: into the Google calculator. I know how to I know 688 00:40:06,960 --> 00:40:13,800 Speaker 1: how to convert. Did you do it on March Fools Day? Okay? 689 00:40:13,840 --> 00:40:18,600 Speaker 1: So that's that's the winter highs and the summertime average 690 00:40:18,640 --> 00:40:24,560 Speaker 1: temperature is nineteen degrees c or sixty six degrees f. Yeah, 691 00:40:24,640 --> 00:40:28,319 Speaker 1: but like what is it in Moscow? Like let's talk 692 00:40:28,360 --> 00:40:31,319 Speaker 1: about so right, and Moscow is much larger. So if 693 00:40:31,520 --> 00:40:33,759 Speaker 1: I'm sorry not to like tear this down before you 694 00:40:33,840 --> 00:40:37,640 Speaker 1: builds as I could do. But if you if you're 695 00:40:37,640 --> 00:40:39,920 Speaker 1: gonna argue that it's an environmental factor and that it's 696 00:40:40,000 --> 00:40:42,600 Speaker 1: it's just too cold all the time. There are so 697 00:40:42,640 --> 00:40:45,160 Speaker 1: many other places that you would be seeing things like 698 00:40:45,200 --> 00:40:47,760 Speaker 1: this happening, I guess. I mean it's possible that people 699 00:40:47,840 --> 00:40:51,080 Speaker 1: just don't notice in Russia. I know, I can agree 700 00:40:51,160 --> 00:40:53,440 Speaker 1: with your point that again, this is just like the 701 00:40:54,200 --> 00:40:57,719 Speaker 1: Yeah I checked. I checked just three countries randomly that 702 00:40:57,760 --> 00:41:03,200 Speaker 1: are way north and colder Iceland, Norway in Finland and yeah, 703 00:41:03,239 --> 00:41:07,000 Speaker 1: Iceland life expectancy eighty three years old. Norway I think 704 00:41:07,000 --> 00:41:08,920 Speaker 1: it was about eighty two and a half, and I 705 00:41:08,960 --> 00:41:16,520 Speaker 1: think it is that what it is. Okay, Yeah, temperature now, 706 00:41:16,640 --> 00:41:20,480 Speaker 1: because they're women are also more beautiful cold. I'm sorry, 707 00:41:20,640 --> 00:41:22,839 Speaker 1: I'm trying really hard not to offend anyone. I didn't 708 00:41:22,880 --> 00:41:25,440 Speaker 1: mean that in an offensive way. Scottish women are very beautiful. 709 00:41:25,520 --> 00:41:28,239 Speaker 1: Scottish women are very beautiful. I mean every country has 710 00:41:28,239 --> 00:41:30,920 Speaker 1: the most beautiful women, that's true. Yeah, let's get a 711 00:41:31,000 --> 00:41:35,160 Speaker 1: move on now after that debacle to the next we 712 00:41:35,239 --> 00:41:38,280 Speaker 1: have to actually have two environmental factors theories. The second 713 00:41:38,280 --> 00:41:42,719 Speaker 1: one is pollution. Yeah, so as we talked about, we 714 00:41:42,800 --> 00:41:48,000 Speaker 1: had the shipyards, we had the chemical processing um and 715 00:41:48,080 --> 00:41:49,640 Speaker 1: it looks like you know what I was right, it 716 00:41:49,680 --> 00:41:53,319 Speaker 1: was textiles. They don't specify exactly what the textiles were 717 00:41:53,320 --> 00:41:55,920 Speaker 1: in some of the stuff that I was reading. But 718 00:41:56,000 --> 00:41:59,120 Speaker 1: we talked about this. They're not exactly clean. They're not 719 00:41:59,239 --> 00:42:02,480 Speaker 1: really good about keeping the city around them nice. They 720 00:42:02,560 --> 00:42:05,920 Speaker 1: dump everything in the river. I'm saying historically, not today. 721 00:42:06,360 --> 00:42:09,040 Speaker 1: I'm sorry, Can I share it today? I learned today? 722 00:42:09,080 --> 00:42:12,440 Speaker 1: I learned that Victoria doesn't have a waste treatment plant Victoria, BC. No, 723 00:42:12,520 --> 00:42:15,600 Speaker 1: they just dump it right into the river. Are you serious? Yeah, 724 00:42:16,120 --> 00:42:19,359 Speaker 1: they dump it into the harbor or what the harbor? Yeah, 725 00:42:19,520 --> 00:42:22,840 Speaker 1: apparently apparently the state of Washington is considering like a 726 00:42:22,880 --> 00:42:25,160 Speaker 1: no travel ban on them to say, like, you have 727 00:42:25,320 --> 00:42:28,520 Speaker 1: to start treating this stuff. Anyway, that's my Today. I 728 00:42:28,600 --> 00:42:34,160 Speaker 1: learned some crazy poop. Yeah, I've been I find that 729 00:42:34,200 --> 00:42:36,239 Speaker 1: hard to believe because I've been to Victoria quite a 730 00:42:36,280 --> 00:42:39,239 Speaker 1: few times and I've never seen poop floating in the harbor. Yeah, 731 00:42:39,239 --> 00:42:42,000 Speaker 1: but you can't smell anything. Well, you've been there, did 732 00:42:42,000 --> 00:42:45,280 Speaker 1: you smell anything? No? But I was drunk. Okay, actually 733 00:42:45,320 --> 00:42:48,040 Speaker 1: it wasn't. That's just my go to excuse. Okay, Well, 734 00:42:48,120 --> 00:42:51,960 Speaker 1: let's keep going with this, uh, with this pollution. So 735 00:42:52,600 --> 00:42:56,879 Speaker 1: if that was if pollution was responsible for the higher mortality, rate, 736 00:42:57,239 --> 00:43:01,120 Speaker 1: then you would expect that we would see higher levels 737 00:43:01,280 --> 00:43:05,720 Speaker 1: of cancers, which cancer does kill at a higher level 738 00:43:05,880 --> 00:43:09,040 Speaker 1: than the average expected. One of the things I kept 739 00:43:09,080 --> 00:43:13,279 Speaker 1: seeing called out is they always said lung cancers, but 740 00:43:13,320 --> 00:43:16,440 Speaker 1: they never said exactly what it was. So I was 741 00:43:16,440 --> 00:43:19,279 Speaker 1: always curious if that might be something to do with it. 742 00:43:19,480 --> 00:43:24,240 Speaker 1: Lung cancers plural or lung cancer. Uh, you know that's 743 00:43:24,280 --> 00:43:26,799 Speaker 1: now that you specify, I'm not sure which it was. 744 00:43:27,120 --> 00:43:29,279 Speaker 1: Let's just say lung cancer. I believe there is one. 745 00:43:29,280 --> 00:43:31,480 Speaker 1: More more than one there is, I mean there's multiple 746 00:43:31,520 --> 00:43:33,759 Speaker 1: there's muth cancers that can be in your lungs. Then 747 00:43:33,800 --> 00:43:36,800 Speaker 1: that might be. As much as I love our British friends, 748 00:43:36,960 --> 00:43:41,240 Speaker 1: they have different ways of phrasing things sometimes, and so 749 00:43:41,600 --> 00:43:44,960 Speaker 1: I'm not always sure if it's just phrasing for the 750 00:43:44,960 --> 00:43:47,759 Speaker 1: way I would normally expect it to be, or if 751 00:43:47,800 --> 00:43:51,720 Speaker 1: it's something slightly different. So I wasn't positive. But again, 752 00:43:52,000 --> 00:43:54,759 Speaker 1: how do we have any evidence that pollution there is 753 00:43:55,200 --> 00:43:59,239 Speaker 1: stronger or no, not really than anywhere else, certainly not 754 00:43:59,280 --> 00:44:04,600 Speaker 1: more than Southeast Portland. Yeah, yeah, well, I mean it's London. 755 00:44:04,680 --> 00:44:07,440 Speaker 1: At one time was considered one of the filthiest cities 756 00:44:07,480 --> 00:44:11,440 Speaker 1: in the world, and it's super clean China and well 757 00:44:11,440 --> 00:44:14,640 Speaker 1: I'm just thinking about in the UK and then you 758 00:44:14,680 --> 00:44:18,480 Speaker 1: go up to Glasgow and it's pretty clean. Yeah, I'm 759 00:44:18,480 --> 00:44:20,759 Speaker 1: sure the pollution back back in the day was a 760 00:44:20,800 --> 00:44:22,719 Speaker 1: lot worse. Yeah. I mean, if we look at the 761 00:44:22,760 --> 00:44:27,200 Speaker 1: at the nineteenth century or even the twentieth century, they 762 00:44:27,200 --> 00:44:30,279 Speaker 1: didn't care. It was stuff everywhere, you know, it was 763 00:44:30,640 --> 00:44:33,120 Speaker 1: it was the cold snow, I believe it. It was 764 00:44:33,160 --> 00:44:35,520 Speaker 1: the ash was so thick that it was like snow. 765 00:44:36,320 --> 00:44:39,520 Speaker 1: But that's I don't think that is that dirty anymore. 766 00:44:39,600 --> 00:44:42,400 Speaker 1: And I guess this it feels like this isn't easy 767 00:44:42,480 --> 00:44:45,480 Speaker 1: to prove or disprove theory. You just take some samples 768 00:44:45,560 --> 00:44:49,160 Speaker 1: of the air, and if it's super contaminated you can 769 00:44:49,239 --> 00:44:53,400 Speaker 1: start to say, well that might be a reason, or 770 00:44:53,680 --> 00:44:56,360 Speaker 1: it's not super contaminated, so that may not be a reason, 771 00:44:57,200 --> 00:45:01,280 Speaker 1: you know. Yeah, but also it's not there not strong evidence. 772 00:45:01,320 --> 00:45:04,400 Speaker 1: There's not. And it's also not as though lung cancer 773 00:45:04,560 --> 00:45:07,160 Speaker 1: is the thing that is killing this many more people. 774 00:45:07,360 --> 00:45:10,960 Speaker 1: I mean, it's it's cancer in general is higher, but 775 00:45:11,120 --> 00:45:15,680 Speaker 1: its general that are higher in general to like alcohol, 776 00:45:15,760 --> 00:45:17,000 Speaker 1: is that well yeah, but I was gonna say it's 777 00:45:17,000 --> 00:45:21,120 Speaker 1: if it's cancer in general, then you can't find as 778 00:45:21,160 --> 00:45:25,640 Speaker 1: easily a specific cause because certain things tend to cause 779 00:45:25,719 --> 00:45:29,640 Speaker 1: certain kinds of cancers and other things tend to cause 780 00:45:29,800 --> 00:45:34,800 Speaker 1: other kinds of cancers. But if it's if it's cancers 781 00:45:34,880 --> 00:45:39,000 Speaker 1: in general, then it makes me think that it might 782 00:45:39,040 --> 00:45:42,320 Speaker 1: not just be from one factor, which in this theory 783 00:45:42,360 --> 00:45:45,080 Speaker 1: would be the pollution. But but but but also the 784 00:45:45,120 --> 00:45:48,720 Speaker 1: other thing is that people aren't just dying of cancer, 785 00:45:48,800 --> 00:45:50,839 Speaker 1: where they're dying about a whole lot of other sects too. 786 00:45:51,000 --> 00:45:54,120 Speaker 1: So yeah, and even if I mean, I guess I 787 00:45:54,160 --> 00:45:56,279 Speaker 1: don't know how you necessarily could find this out, but 788 00:45:56,320 --> 00:46:00,520 Speaker 1: you know, there is certainly the the idea that but 789 00:46:00,719 --> 00:46:03,480 Speaker 1: just because you have cancer, you can die of something else. Right, 790 00:46:03,920 --> 00:46:06,279 Speaker 1: you have cancer in your heart gives out, you die 791 00:46:06,280 --> 00:46:08,360 Speaker 1: of that heart attack, So your cause of death is 792 00:46:08,360 --> 00:46:11,440 Speaker 1: the heart attack, but you still had cancer. Uh, but 793 00:46:11,480 --> 00:46:13,920 Speaker 1: I don't know if that's tracked in these records, So 794 00:46:13,960 --> 00:46:16,160 Speaker 1: I don't know if that's taken into effect that these 795 00:46:16,160 --> 00:46:18,880 Speaker 1: people also had. Can I think cause of death is 796 00:46:18,920 --> 00:46:21,279 Speaker 1: cause of death. So if you crash your car and 797 00:46:21,400 --> 00:46:26,440 Speaker 1: die and you just happen to have a terminal disease, 798 00:46:27,000 --> 00:46:30,520 Speaker 1: they say your cause of death vehicle in that case. Yes, 799 00:46:30,600 --> 00:46:34,120 Speaker 1: but doesn't that seem like that would be really important 800 00:46:34,200 --> 00:46:37,000 Speaker 1: factor to find out for Glasgow in terms of the 801 00:46:37,040 --> 00:46:39,719 Speaker 1: Glasgow effect if somebody were that like, even if you 802 00:46:39,800 --> 00:46:42,080 Speaker 1: crashed your car at seventeen and you had a terminal 803 00:46:42,120 --> 00:46:44,280 Speaker 1: case of cancer, it's important that you have the terminal 804 00:46:44,320 --> 00:46:46,319 Speaker 1: case of cancer just as much as it is that 805 00:46:46,360 --> 00:46:48,479 Speaker 1: your cause of death was a car crash. But that's 806 00:46:48,560 --> 00:46:50,239 Speaker 1: that's the problem, is that, right? And this is what 807 00:46:50,280 --> 00:46:52,799 Speaker 1: this is what's now starting to go on, is that 808 00:46:52,880 --> 00:46:55,200 Speaker 1: they're starting to have to do like what you're suggesting 809 00:46:55,239 --> 00:46:57,040 Speaker 1: is they have to they're having to go deeper because 810 00:46:57,080 --> 00:47:00,560 Speaker 1: they've got the surface data the easy numbers, and the 811 00:47:00,600 --> 00:47:03,680 Speaker 1: easy numbers aren't making sense. And so yeah, I mean 812 00:47:03,719 --> 00:47:05,880 Speaker 1: that is one of the things there's Uh, there was 813 00:47:05,920 --> 00:47:09,520 Speaker 1: a report that was due out at the beginning of 814 00:47:10,640 --> 00:47:12,880 Speaker 1: It's one of the reasons actually held off on this 815 00:47:12,920 --> 00:47:15,719 Speaker 1: story for a while because I wanted to get that 816 00:47:15,840 --> 00:47:19,319 Speaker 1: report and as of you know, this is March now 817 00:47:19,360 --> 00:47:24,960 Speaker 1: when we're recording and report out, so I you know, 818 00:47:25,000 --> 00:47:28,160 Speaker 1: I was really hoping that there was gonna be that 819 00:47:28,480 --> 00:47:32,280 Speaker 1: shining answering. But I think it's likely this. The report 820 00:47:32,320 --> 00:47:35,200 Speaker 1: will come out next week probably after we're done. We'll 821 00:47:35,239 --> 00:47:39,040 Speaker 1: follow up, we'll do a short Okay, so pollution I 822 00:47:39,120 --> 00:47:41,279 Speaker 1: think is out. Yeah, yeah, I think I'm right. So 823 00:47:41,360 --> 00:47:43,880 Speaker 1: let's go ahead and let's move on down the line 824 00:47:43,960 --> 00:47:47,720 Speaker 1: to our next one, which is again a Devin special. 825 00:47:47,840 --> 00:47:52,319 Speaker 1: It is food scarcity and then the stress levels which 826 00:47:52,320 --> 00:47:56,399 Speaker 1: are which are notably higher in this town. Okay, Well, 827 00:47:56,560 --> 00:47:58,560 Speaker 1: the reason that this is brought up is because we 828 00:47:58,719 --> 00:48:02,520 Speaker 1: just we talked about earlier is the the amount of 829 00:48:02,560 --> 00:48:06,719 Speaker 1: people who are unemployed and who are on public assistance. 830 00:48:07,239 --> 00:48:12,719 Speaker 1: So chances are if they have any other reason, the 831 00:48:12,880 --> 00:48:15,120 Speaker 1: things that they want to spend their money on, whether 832 00:48:15,160 --> 00:48:20,040 Speaker 1: it be booze, smokes, naked women, whatever the case may be, 833 00:48:20,160 --> 00:48:24,959 Speaker 1: if they've got some other vice, some other vice, then 834 00:48:25,360 --> 00:48:27,600 Speaker 1: they are going to be spending money on that. So 835 00:48:27,680 --> 00:48:30,680 Speaker 1: therefore they're not going to be spending as much on food, 836 00:48:31,560 --> 00:48:36,200 Speaker 1: and that's gonna then cascade down through a household, because 837 00:48:36,200 --> 00:48:39,239 Speaker 1: if the household doesn't have as much money, then everybody's 838 00:48:39,400 --> 00:48:41,520 Speaker 1: you know, a little unsure of where their next meal 839 00:48:41,600 --> 00:48:43,520 Speaker 1: is going to come from. So that's where this is, 840 00:48:43,600 --> 00:48:46,040 Speaker 1: That's what this is based on. Yeah, I have to 841 00:48:46,080 --> 00:48:48,560 Speaker 1: say that being on the doll is not healthy in 842 00:48:48,640 --> 00:48:52,360 Speaker 1: many sense, many senses, it's not good for your self esteem, 843 00:48:52,440 --> 00:48:55,120 Speaker 1: and it's not you know. The thing about having a 844 00:48:55,200 --> 00:48:58,160 Speaker 1: job that's good besides you don't have an income, is 845 00:48:58,200 --> 00:49:01,480 Speaker 1: that it gives you reason to sort of like stay 846 00:49:01,520 --> 00:49:03,359 Speaker 1: on top of yourself, you know. I mean, you can't 847 00:49:03,360 --> 00:49:05,400 Speaker 1: be you can't be sleeping until three in the afternoon 848 00:49:05,400 --> 00:49:07,120 Speaker 1: every day, and you can't be starting drinking at ten 849 00:49:07,160 --> 00:49:10,040 Speaker 1: in the morning. It you got to rself in order. 850 00:49:10,239 --> 00:49:14,759 Speaker 1: Negative cycles can can manifest your well I mean. And 851 00:49:14,760 --> 00:49:17,319 Speaker 1: then the other thing too, that happens often. I know 852 00:49:17,400 --> 00:49:19,600 Speaker 1: that I've I've gone through this when I've been on 853 00:49:19,920 --> 00:49:22,480 Speaker 1: or under employed. You know, right now, I have a 854 00:49:22,480 --> 00:49:26,040 Speaker 1: steady job, however much I like it or not. But 855 00:49:26,360 --> 00:49:29,000 Speaker 1: I wake up at the same time every day. I 856 00:49:29,040 --> 00:49:31,080 Speaker 1: go to sleep about the same time every day. I 857 00:49:31,120 --> 00:49:34,239 Speaker 1: have a routine. When I'm not employed, I wake up 858 00:49:34,280 --> 00:49:36,279 Speaker 1: whenever I go to sleep, whenever it starts to mess 859 00:49:36,280 --> 00:49:41,480 Speaker 1: with the sleep cycle. And and there are a lot 860 00:49:41,520 --> 00:49:44,839 Speaker 1: of studies about how a messed up circadian rhythm can 861 00:49:44,960 --> 00:49:49,200 Speaker 1: really mess with your body. And that's that's another thing too, 862 00:49:49,239 --> 00:49:51,120 Speaker 1: is if you don't have the schedule that you need 863 00:49:51,160 --> 00:49:54,239 Speaker 1: to stick to, at least me. I think you guys 864 00:49:54,280 --> 00:49:57,440 Speaker 1: would agree. It's really easy to just slip out of 865 00:49:58,239 --> 00:50:00,680 Speaker 1: that and then it just starts to kind of with 866 00:50:00,800 --> 00:50:03,000 Speaker 1: your body. And the last time I was out of work, 867 00:50:03,040 --> 00:50:05,560 Speaker 1: it was quite well back, but it was amazing how 868 00:50:05,640 --> 00:50:08,120 Speaker 1: quickly I adapted to staying up till two every night 869 00:50:08,160 --> 00:50:13,879 Speaker 1: and slipping intil ten every morning. So easy. Well, let's 870 00:50:13,960 --> 00:50:18,360 Speaker 1: let's talk about the I've got some stuff here about 871 00:50:19,200 --> 00:50:23,880 Speaker 1: the food shortage cycle. Actually, since I've been yambering on 872 00:50:23,920 --> 00:50:25,960 Speaker 1: this whole time, Devin, do you mind reading this quote? 873 00:50:26,400 --> 00:50:29,200 Speaker 1: The cycle of having enough food followed by food shortage 874 00:50:29,360 --> 00:50:32,520 Speaker 1: is thought to play a direct role in dietary compromise, 875 00:50:32,600 --> 00:50:37,360 Speaker 1: accumulation of visceral fat and weight gain. Inadequate nutrient nutrition 876 00:50:37,840 --> 00:50:40,839 Speaker 1: and weight gain play a direct role in the development 877 00:50:40,880 --> 00:50:44,520 Speaker 1: of chronic diseases. Stress plays an active role in metabolism 878 00:50:44,600 --> 00:50:48,759 Speaker 1: chronic disease. Animal models suggest mice exposed to stress conditions 879 00:50:48,760 --> 00:50:51,400 Speaker 1: in the presence of high fat, high sugar food secrete 880 00:50:51,400 --> 00:50:55,120 Speaker 1: stress hormones and insulin, which leads to a subcutaneous fat 881 00:50:55,160 --> 00:50:57,399 Speaker 1: and weight gain just by being near the high fat, 882 00:50:57,440 --> 00:51:00,520 Speaker 1: high sugar food I don't know exacts as two means 883 00:51:00,520 --> 00:51:05,239 Speaker 1: are eating it. Okay, okay. Quote. Food insecurity is inconsistently 884 00:51:05,280 --> 00:51:09,480 Speaker 1: associated with overweight and obesity among women. However, several studies 885 00:51:09,520 --> 00:51:12,799 Speaker 1: have found a significant association between food and security and 886 00:51:12,880 --> 00:51:17,560 Speaker 1: diabetes and poor diabetes management. For example, a significantly higher 887 00:51:17,560 --> 00:51:21,440 Speaker 1: percentage of adults with diabetes from food insecure households report 888 00:51:21,480 --> 00:51:26,120 Speaker 1: difficulty following a diabetic diet, decreased confidence in their ability 889 00:51:26,160 --> 00:51:29,040 Speaker 1: to manage their diabetes, and a higher score for emotional 890 00:51:29,040 --> 00:51:33,960 Speaker 1: distress related to diabetes. Food insecurity during pregnancy is associated 891 00:51:34,000 --> 00:51:37,440 Speaker 1: with higher levels of stress, anxiety, and depression, just stational 892 00:51:37,520 --> 00:51:40,879 Speaker 1: weight gain and over twice the risk of developing gestational 893 00:51:40,920 --> 00:51:45,800 Speaker 1: diabetes compared with low income food secure women. Unquote, thank you, 894 00:51:45,800 --> 00:51:48,480 Speaker 1: You're welcome. But that that that does play into some 895 00:51:48,480 --> 00:51:50,600 Speaker 1: of the stuff that you were bringing up earlier. It's 896 00:51:50,680 --> 00:51:52,440 Speaker 1: the more articulate way to say all the things I 897 00:51:52,480 --> 00:51:58,560 Speaker 1: was just saying. What sound more smarter, more smarter, more better? Steve, 898 00:52:01,440 --> 00:52:05,400 Speaker 1: all right, so let's uh, I mean we and we 899 00:52:05,440 --> 00:52:08,560 Speaker 1: already know as we talked about the stress is excess 900 00:52:08,560 --> 00:52:11,360 Speaker 1: amounts of stress is bad. Your body is meant to 901 00:52:11,360 --> 00:52:14,160 Speaker 1: deal with stress to a certain degree. But if you 902 00:52:14,239 --> 00:52:17,040 Speaker 1: go ahead and add in lots and lots of it, 903 00:52:17,080 --> 00:52:19,360 Speaker 1: you're in what I would I would just say, let's 904 00:52:19,600 --> 00:52:23,160 Speaker 1: call it fight or flight mode all the time that 905 00:52:23,800 --> 00:52:28,279 Speaker 1: high blood pressure is gonna happen, heart attacks are gonna happen, uh, 906 00:52:28,400 --> 00:52:30,920 Speaker 1: circulation breathing issues. I mean, these are just kind of 907 00:52:30,960 --> 00:52:32,880 Speaker 1: a handful of the things that are going to happen. 908 00:52:33,200 --> 00:52:37,359 Speaker 1: So it plays havoc on the body and the immune system. Yeah, 909 00:52:37,400 --> 00:52:40,440 Speaker 1: I mean it's very well known scientifically. They've looked at 910 00:52:40,440 --> 00:52:42,000 Speaker 1: it and they figured it out, and yeah, it's a 911 00:52:42,000 --> 00:52:45,720 Speaker 1: bad thing for you. But has anybody done, um, any 912 00:52:45,840 --> 00:52:50,560 Speaker 1: surveys on food insecurity in Glasgow? Um? So the reports 913 00:52:50,600 --> 00:52:56,160 Speaker 1: that I read, it's kind of presumed that there's a 914 00:52:56,239 --> 00:52:59,759 Speaker 1: portion of the households that are food insecure and there's 915 00:52:59,760 --> 00:53:04,120 Speaker 1: a portion that are food secure. What the ratio is 916 00:53:04,160 --> 00:53:07,880 Speaker 1: and what those numbers are. I didn't see that specifically 917 00:53:07,920 --> 00:53:10,480 Speaker 1: called out, but that may have been because I didn't. 918 00:53:10,680 --> 00:53:13,480 Speaker 1: I wasn't on page sixty eight and one specific table. 919 00:53:13,680 --> 00:53:16,880 Speaker 1: It's also it's also hard since we're talking about cross 920 00:53:16,920 --> 00:53:21,200 Speaker 1: generational stuff, right, We're talking about how a parents food 921 00:53:21,200 --> 00:53:26,640 Speaker 1: insecurity can affect a child. For instance, that data certainly 922 00:53:26,680 --> 00:53:29,640 Speaker 1: probably wasn't really I mean, that wasn't a thing that 923 00:53:29,680 --> 00:53:33,440 Speaker 1: people really thought about in previous generations, especially if we 924 00:53:33,480 --> 00:53:35,799 Speaker 1: start talking about a couple of generations back. I mean, 925 00:53:36,160 --> 00:53:39,359 Speaker 1: I'm so, I'm third second generation from my grandma, right, 926 00:53:39,880 --> 00:53:43,719 Speaker 1: and she was born in like nineteen hundred, and that's 927 00:53:43,760 --> 00:53:47,240 Speaker 1: a long time ago, and there's one person in between 928 00:53:47,239 --> 00:53:49,839 Speaker 1: me and her, and when she was growing up, they 929 00:53:50,040 --> 00:53:53,799 Speaker 1: just called it being hungry. It wasn't food insecurity and 930 00:53:54,000 --> 00:53:56,239 Speaker 1: stress levels and all that stuff. And so when we 931 00:53:56,280 --> 00:53:59,040 Speaker 1: start talking about getting just a couple of generations back, 932 00:53:59,400 --> 00:54:02,080 Speaker 1: those studies aren't being done, so we probably don't have 933 00:54:02,239 --> 00:54:07,200 Speaker 1: and the records are are not there, and frankly, like 934 00:54:07,320 --> 00:54:10,080 Speaker 1: it's kind of an embarrassing thing. I have to say 935 00:54:10,080 --> 00:54:12,960 Speaker 1: it to somebody. Yeah, yeah, we don't always have food. 936 00:54:13,840 --> 00:54:16,440 Speaker 1: Yeah no, I mean as a as an adult, Yeah, 937 00:54:16,520 --> 00:54:20,279 Speaker 1: it's just not something talk about now. People don't want 938 00:54:20,280 --> 00:54:22,919 Speaker 1: to talk about that, or you may think you are. 939 00:54:23,560 --> 00:54:26,959 Speaker 1: You may say I'm doing the best I can, and yeah, 940 00:54:27,000 --> 00:54:29,799 Speaker 1: it's enough, but it turns out it's you know, mac 941 00:54:29,800 --> 00:54:34,880 Speaker 1: and cheese from or a half portion every other day. Listen, 942 00:54:34,920 --> 00:54:38,359 Speaker 1: that's what we've got. We have food. I mean, there's 943 00:54:38,440 --> 00:54:39,880 Speaker 1: there's a whole I mean, I don't want to go 944 00:54:39,920 --> 00:54:41,840 Speaker 1: too far down this because there's a whole number of 945 00:54:41,840 --> 00:54:44,480 Speaker 1: ways that that can play out, but that does have 946 00:54:44,920 --> 00:54:47,879 Speaker 1: as you were pointing out, that long term effect. One 947 00:54:47,920 --> 00:54:50,680 Speaker 1: of the long term effects that I actually saw brought 948 00:54:50,800 --> 00:54:54,640 Speaker 1: up in some of the research is epigenetics. And I 949 00:54:54,719 --> 00:54:57,040 Speaker 1: don't know if you guys, do you guys know much 950 00:54:57,080 --> 00:55:00,359 Speaker 1: about epigenetics. I read it and I'm okay, well, then 951 00:55:01,320 --> 00:55:05,200 Speaker 1: I did that. I took the reading and I've boiled 952 00:55:05,239 --> 00:55:08,880 Speaker 1: it down here because it's DNA stuff and that is 953 00:55:09,040 --> 00:55:12,480 Speaker 1: above my pay grade. I admit this right now. But 954 00:55:12,719 --> 00:55:15,600 Speaker 1: the way that I understand it is that in the 955 00:55:15,760 --> 00:55:21,520 Speaker 1: super simplified explanation is epogenetics would be the study of 956 00:55:21,960 --> 00:55:27,640 Speaker 1: environmental effects on the body and whether or not it 957 00:55:27,640 --> 00:55:32,200 Speaker 1: influences certain genes to turn on or off. So, in 958 00:55:32,239 --> 00:55:35,440 Speaker 1: other words, how does at a at a base level, 959 00:55:35,880 --> 00:55:37,960 Speaker 1: how does the body react, and then what does that 960 00:55:38,040 --> 00:55:42,120 Speaker 1: do to it? And it's future generations. I've seen some 961 00:55:42,560 --> 00:55:45,319 Speaker 1: actually well, and it's it's interesting because I've seen some 962 00:55:45,360 --> 00:55:50,600 Speaker 1: studies that say, um that at times it can make 963 00:55:50,680 --> 00:55:55,879 Speaker 1: people prone to obesity and diabetes, and then at other 964 00:55:56,360 --> 00:55:59,440 Speaker 1: studies that say, if it's time correctly, and that's that that, 965 00:55:59,520 --> 00:56:02,319 Speaker 1: by the way, is not necessarily that person, but their 966 00:56:02,400 --> 00:56:07,399 Speaker 1: offspring or their second generation forward, or it can if 967 00:56:07,440 --> 00:56:10,799 Speaker 1: it hits in the right time, it can actually make 968 00:56:11,120 --> 00:56:14,120 Speaker 1: their offspring or the second as well as or the 969 00:56:14,120 --> 00:56:18,960 Speaker 1: second generation have factors that make them healthier individuals, so 970 00:56:19,000 --> 00:56:22,440 Speaker 1: they're less prone to overeating or more prone to overeating. 971 00:56:23,040 --> 00:56:26,000 Speaker 1: So it's it's a really for me, it's kind of 972 00:56:26,040 --> 00:56:29,680 Speaker 1: a gray area. But it's also just that right. I mean, 973 00:56:29,719 --> 00:56:33,040 Speaker 1: it affects literally every part. I mean, but when you 974 00:56:33,080 --> 00:56:36,239 Speaker 1: look at how it reacts. So I mean, we've all 975 00:56:36,600 --> 00:56:40,560 Speaker 1: I've done this where I've gone and eaten something and said, well, 976 00:56:40,600 --> 00:56:43,120 Speaker 1: that's all I need to eat. And then I've gone 977 00:56:43,160 --> 00:56:45,520 Speaker 1: and said I've eaten that and that's all I needed 978 00:56:45,520 --> 00:56:48,160 Speaker 1: to eat. But I'm going to eat more anyway. And 979 00:56:48,200 --> 00:56:54,839 Speaker 1: there are, because of some genetic predispositions, times where there 980 00:56:54,840 --> 00:56:57,839 Speaker 1: will be people who always feel like feed, like feel 981 00:56:57,840 --> 00:56:59,000 Speaker 1: like they need to eat more. I mean, I've got 982 00:56:59,040 --> 00:57:02,200 Speaker 1: a cat who always sits the cat bowl, even though 983 00:57:02,400 --> 00:57:06,000 Speaker 1: she gets enough food every day, sits at the capitol 984 00:57:06,080 --> 00:57:09,080 Speaker 1: for six hours there the food bull staring at me, like, dude, 985 00:57:09,400 --> 00:57:11,880 Speaker 1: I totally need more food. It's but that is to 986 00:57:12,000 --> 00:57:15,960 Speaker 1: a degree, can be dictated at the genetic level, and 987 00:57:16,000 --> 00:57:18,720 Speaker 1: that's where this is coming from. Yeah, I mean, like 988 00:57:18,760 --> 00:57:22,120 Speaker 1: I was kind of saying, it's not just obesity, It's 989 00:57:22,120 --> 00:57:24,840 Speaker 1: not just that. I can also you can also predisposition 990 00:57:24,880 --> 00:57:27,520 Speaker 1: your kids almost anything, right, I mean one of the 991 00:57:27,560 --> 00:57:30,720 Speaker 1: things they talked about two is to be less able 992 00:57:30,800 --> 00:57:34,240 Speaker 1: to handle stress, you know, just because of the way, 993 00:57:34,320 --> 00:57:36,400 Speaker 1: which is one of those scary things as a woman, right, 994 00:57:36,440 --> 00:57:38,600 Speaker 1: you're kind of like, oh my god, I could literally 995 00:57:38,880 --> 00:57:44,040 Speaker 1: ruin my child's life by just breathing something, you know. 996 00:57:44,520 --> 00:57:48,040 Speaker 1: So that's but that's terrifying. But it's also might get 997 00:57:48,640 --> 00:57:52,320 Speaker 1: they might but so but that seems like the sort 998 00:57:52,320 --> 00:57:55,120 Speaker 1: of thing also that it would come out and studies. 999 00:57:55,920 --> 00:57:59,280 Speaker 1: But but that's the problem is that epi genetics they're 1000 00:57:59,400 --> 00:58:02,440 Speaker 1: just learning how to study some of this stuff. So 1001 00:58:02,480 --> 00:58:05,320 Speaker 1: it's very it's very difficult to say, well, let's just 1002 00:58:05,400 --> 00:58:09,000 Speaker 1: look back, ye And and as you said, it's hard, 1003 00:58:09,000 --> 00:58:11,200 Speaker 1: it's really hard to go historically and say, well, this 1004 00:58:11,360 --> 00:58:15,680 Speaker 1: family was suffering from food and security or extra stress 1005 00:58:15,760 --> 00:58:18,840 Speaker 1: levels or whatever. And you were saying that there's there 1006 00:58:18,920 --> 00:58:23,640 Speaker 1: is a really high unemployment rates high there, but yeah, 1007 00:58:24,000 --> 00:58:27,200 Speaker 1: and also there again the the murder rate. Now that'll 1008 00:58:27,280 --> 00:58:30,919 Speaker 1: that'll stress you a little bit too. Yeah. Well initially, well, 1009 00:58:30,960 --> 00:58:32,480 Speaker 1: and I think the thing that we need to look 1010 00:58:32,520 --> 00:58:34,680 Speaker 1: at you actually we're starting to talk about this a 1011 00:58:34,680 --> 00:58:37,920 Speaker 1: little bit devon is the effect is that if we 1012 00:58:37,960 --> 00:58:42,280 Speaker 1: look at current generation of children and maybe how that's 1013 00:58:42,280 --> 00:58:46,920 Speaker 1: going to play forward on them, because um, if so, 1014 00:58:46,960 --> 00:58:51,520 Speaker 1: I pulled some stats on children in two thousand and six, 1015 00:58:52,480 --> 00:58:57,120 Speaker 1: more than six of the children uh in the Greater 1016 00:58:57,160 --> 00:59:00,000 Speaker 1: Glasgow area we're from families that were out of work. 1017 00:59:00,440 --> 00:59:03,120 Speaker 1: So that's as we talked about the insecurity the stress 1018 00:59:03,160 --> 00:59:08,360 Speaker 1: there in ninety between nine six to two thousand and eight, 1019 00:59:09,040 --> 00:59:12,680 Speaker 1: there was a trend in what they referred to as 1020 00:59:12,880 --> 00:59:16,880 Speaker 1: looked after children, which means that that as children who 1021 00:59:17,080 --> 00:59:22,760 Speaker 1: are under the care of nanny's nurseries, going to preschool, 1022 00:59:23,480 --> 00:59:26,400 Speaker 1: talking to foster care and foster this is this is 1023 00:59:26,520 --> 00:59:30,520 Speaker 1: looked after children. This is this means this is state 1024 00:59:31,080 --> 00:59:33,600 Speaker 1: are aren't able to take care of them, and basically 1025 00:59:33,600 --> 00:59:36,240 Speaker 1: the state has taken them in and taken them away 1026 00:59:36,240 --> 00:59:39,320 Speaker 1: from their their family. That's a lot. Yeah, so that 1027 00:59:39,320 --> 00:59:45,240 Speaker 1: that well, it's it's the number. Yeah. So in two 1028 00:59:45,240 --> 00:59:48,640 Speaker 1: thousand and eight there were forty hundred looked after children 1029 00:59:48,760 --> 00:59:53,160 Speaker 1: in the Greater Glasgow area. So this is a generation 1030 00:59:53,480 --> 00:59:57,640 Speaker 1: that is their children. So we don't know, if you know, 1031 00:59:57,720 --> 00:59:59,800 Speaker 1: once they go into that situation, does that mean there're 1032 00:59:59,840 --> 01:00:03,800 Speaker 1: no longer food insecure because you're being looked after, Whereas 1033 01:00:03,800 --> 01:00:07,080 Speaker 1: in the past maybe that wasn't available so they just 1034 01:00:07,200 --> 01:00:11,160 Speaker 1: had to I guess I might. I know, I just 1035 01:00:11,240 --> 01:00:14,840 Speaker 1: rolled my eyes that. But I think that that comes 1036 01:00:14,920 --> 01:00:19,040 Speaker 1: from just at least the system in America. I don't 1037 01:00:19,040 --> 01:00:21,080 Speaker 1: know how it is in Glasgow. I don't know how 1038 01:00:21,120 --> 01:00:24,840 Speaker 1: it is in Scotland, but just the foster care system 1039 01:00:24,960 --> 01:00:30,040 Speaker 1: or social services in America that just because child is 1040 01:00:30,080 --> 01:00:32,760 Speaker 1: in foster care doesn't mean that they are no longer 1041 01:00:32,800 --> 01:00:37,680 Speaker 1: food insecure or that that looked I understand it's deemed 1042 01:00:37,680 --> 01:00:40,920 Speaker 1: to be more able to take care, but that doesn't 1043 01:00:40,960 --> 01:00:43,120 Speaker 1: necessarily mean that they're going to be out of the 1044 01:00:43,120 --> 01:00:45,120 Speaker 1: woods with that sort of stuff. But again I don't 1045 01:00:45,120 --> 01:00:47,200 Speaker 1: know how it works in Glasgow. I don't know if 1046 01:00:47,200 --> 01:00:50,960 Speaker 1: it means they actually are getting three square healthy meals 1047 01:00:51,000 --> 01:00:53,880 Speaker 1: a day and the help they need and the sleep 1048 01:00:53,920 --> 01:00:56,760 Speaker 1: they need, and they're also not stressed out about the 1049 01:00:56,760 --> 01:00:59,760 Speaker 1: fact that they aren't with their parents anymore. I really 1050 01:01:00,080 --> 01:01:03,280 Speaker 1: the only way the boots on the ground is you know, 1051 01:01:03,480 --> 01:01:06,360 Speaker 1: the people who were there and in those situations, those 1052 01:01:06,400 --> 01:01:08,560 Speaker 1: are the only ones who could answer that. And I 1053 01:01:08,560 --> 01:01:11,360 Speaker 1: imagine that that is Again, this is where I feel 1054 01:01:11,440 --> 01:01:14,720 Speaker 1: like the next step in the research process is that 1055 01:01:14,760 --> 01:01:17,680 Speaker 1: they're probably going to start drilling into these things, because 1056 01:01:17,680 --> 01:01:21,800 Speaker 1: again they're they're doing the high level numbers. Drill down 1057 01:01:21,840 --> 01:01:24,040 Speaker 1: that deep. I mean, okay, if it's if it really 1058 01:01:24,160 --> 01:01:27,800 Speaker 1: is stress from food and security and all that stuff, 1059 01:01:28,320 --> 01:01:30,400 Speaker 1: just look at the family history of people who die young, 1060 01:01:30,480 --> 01:01:32,800 Speaker 1: and that's all you gotta do. That's not that, but 1061 01:01:32,880 --> 01:01:36,560 Speaker 1: that's not that easy to find, especially after they died. 1062 01:01:37,120 --> 01:01:40,360 Speaker 1: You need to get to them right before they die. Well, 1063 01:01:40,400 --> 01:01:45,040 Speaker 1: I think that I guess the good news about this 1064 01:01:45,200 --> 01:01:47,960 Speaker 1: is that it's we're aware of it, and they are. 1065 01:01:48,120 --> 01:01:50,640 Speaker 1: They're taking care of the data right now. Right there's 1066 01:01:50,640 --> 01:01:52,959 Speaker 1: a lot more tracking happening right now trying to figure 1067 01:01:52,960 --> 01:01:54,680 Speaker 1: out what they're really trying to figure out what's going on. 1068 01:01:54,760 --> 01:01:56,960 Speaker 1: They'll probably do all the testing that would be required 1069 01:01:57,120 --> 01:02:01,080 Speaker 1: from day one, but it's taken eight to ten years 1070 01:02:01,120 --> 01:02:04,000 Speaker 1: to get to the understanding level that we have at 1071 01:02:04,000 --> 01:02:06,680 Speaker 1: this point, so it's hard to say how long we're 1072 01:02:06,800 --> 01:02:10,320 Speaker 1: it's going to take generations before, you know, before it's 1073 01:02:10,320 --> 01:02:13,760 Speaker 1: like let's try this that worked or crap that didn't work. 1074 01:02:13,800 --> 01:02:17,320 Speaker 1: So it's probably be an industry. Yeah, but it will be. 1075 01:02:17,360 --> 01:02:18,720 Speaker 1: I mean it has to be. You have to study 1076 01:02:18,760 --> 01:02:20,720 Speaker 1: that generation as they come up and see if that 1077 01:02:20,800 --> 01:02:25,720 Speaker 1: generation also continues to die on average young, and if 1078 01:02:25,720 --> 01:02:28,880 Speaker 1: they do, then you start saying, okay, well we tracked 1079 01:02:28,920 --> 01:02:32,280 Speaker 1: all of this stuff, so what's the common threat here, 1080 01:02:32,480 --> 01:02:34,200 Speaker 1: which means that if you've got a bunch of children 1081 01:02:34,200 --> 01:02:36,880 Speaker 1: who are under you know, let's say twelve and under, 1082 01:02:37,320 --> 01:02:41,160 Speaker 1: that means we've got to wait another seventy or eighty 1083 01:02:41,280 --> 01:02:43,840 Speaker 1: years before we're going to see if any of the 1084 01:02:43,840 --> 01:02:47,280 Speaker 1: things that are being tried today have an influence. So 1085 01:02:47,320 --> 01:02:52,320 Speaker 1: it is literally an entire generation has to go by, 1086 01:02:52,360 --> 01:02:54,560 Speaker 1: and I don't mean one generation in the next. So 1087 01:02:54,800 --> 01:02:57,800 Speaker 1: one breeds and they create their next, it's before they 1088 01:02:57,800 --> 01:03:01,120 Speaker 1: live their entire life cycle, and good news is it's 1089 01:03:01,200 --> 01:03:05,680 Speaker 1: much shorter for them. Don't look at me like that. 1090 01:03:05,760 --> 01:03:11,640 Speaker 1: It's just I mean we'll get it six years earlier. Okay, 1091 01:03:11,800 --> 01:03:15,960 Speaker 1: let's move forward. I do have one more and this 1092 01:03:16,040 --> 01:03:19,760 Speaker 1: is actually a really easy one, um. And it's actually 1093 01:03:19,800 --> 01:03:23,040 Speaker 1: it's it's a hard one because A it's hard to 1094 01:03:23,080 --> 01:03:26,160 Speaker 1: track and be it's just hard to think about. Is 1095 01:03:26,200 --> 01:03:30,760 Speaker 1: that it's there is a certain amount of cultural alienation 1096 01:03:31,080 --> 01:03:34,320 Speaker 1: that goes on, and that is keep the stiff upper lip, 1097 01:03:34,520 --> 01:03:38,080 Speaker 1: don't tell anybody your problems. You can just handle it 1098 01:03:38,120 --> 01:03:42,360 Speaker 1: on your own. Yeah, and I, you know, I don't 1099 01:03:42,440 --> 01:03:45,920 Speaker 1: reach out for help. So then people feel alienated and 1100 01:03:46,000 --> 01:03:47,920 Speaker 1: they're they're stuck and there they've got to deal with 1101 01:03:47,960 --> 01:03:51,680 Speaker 1: it themselves. So that could be part of it. There's 1102 01:03:51,760 --> 01:03:55,800 Speaker 1: also there is, um, there is an issue with suicide, 1103 01:03:56,400 --> 01:04:00,080 Speaker 1: and there there are suicides. Most of the suicide I 1104 01:04:00,240 --> 01:04:03,280 Speaker 1: seemed to be linked back to drug and alcohol problems 1105 01:04:03,480 --> 01:04:05,320 Speaker 1: and I don't know if that's correct or not, but 1106 01:04:05,440 --> 01:04:09,960 Speaker 1: that's where the data is leading people. I forget how 1107 01:04:10,080 --> 01:04:13,120 Speaker 1: but how much higher is suicide in Glasgow than everywhere 1108 01:04:13,120 --> 01:04:17,040 Speaker 1: else in the UK. He didn't have that number. I 1109 01:04:17,080 --> 01:04:20,600 Speaker 1: had that number and I don't have it anymore. It 1110 01:04:20,760 --> 01:04:24,880 Speaker 1: is higher, right, it is higher, Yes, significantly higher. It's 1111 01:04:25,720 --> 01:04:29,960 Speaker 1: fifteen Let's say it's it's a it's a significant enough 1112 01:04:30,040 --> 01:04:33,520 Speaker 1: number that it gets raised. So that's the cause of death. 1113 01:04:33,840 --> 01:04:36,600 Speaker 1: I mean it's not that, oh I jumped off a bridge, 1114 01:04:36,640 --> 01:04:38,600 Speaker 1: but my cause of death was cancer because I had it, 1115 01:04:38,720 --> 01:04:43,040 Speaker 1: as previously mentioned, right, So that's enough. I was dying 1116 01:04:43,080 --> 01:04:46,400 Speaker 1: because I had cirrhosis and my liver was about to 1117 01:04:46,480 --> 01:04:49,560 Speaker 1: give out. So yeah, I mean, we don't know. We 1118 01:04:49,680 --> 01:04:53,040 Speaker 1: don't have that because again the data. I'm sorry, I 1119 01:04:53,080 --> 01:04:54,520 Speaker 1: don't know the answer to this. I don't know if 1120 01:04:54,560 --> 01:04:56,120 Speaker 1: either of you know the answer to this. But does 1121 01:04:56,160 --> 01:05:00,600 Speaker 1: Glasgow have any kind of right to life? No right 1122 01:05:00,920 --> 01:05:05,840 Speaker 1: idea with you. I never even would have thought to 1123 01:05:05,840 --> 01:05:09,080 Speaker 1: look at that because I wonder because it's technically suicide. 1124 01:05:09,160 --> 01:05:12,960 Speaker 1: But I don't know what happens with that. Yeah, I 1125 01:05:13,000 --> 01:05:15,040 Speaker 1: don't know. I mean Europe tends to be a little 1126 01:05:15,280 --> 01:05:19,080 Speaker 1: a little more flexible about that than conservative America is. 1127 01:05:19,080 --> 01:05:21,320 Speaker 1: So I don't know, okay, I I don't know if 1128 01:05:21,360 --> 01:05:23,840 Speaker 1: that would count account for Also, if if there is 1129 01:05:23,880 --> 01:05:28,360 Speaker 1: this much higher instance in terminal cases of things, if 1130 01:05:28,400 --> 01:05:30,840 Speaker 1: the reason you know, if you stay, well, okay, I'm 1131 01:05:30,840 --> 01:05:32,440 Speaker 1: gonna end my life because I don't want to deal 1132 01:05:32,480 --> 01:05:33,800 Speaker 1: with this. I don't know if that has something to 1133 01:05:33,840 --> 01:05:36,680 Speaker 1: do with the suicide, right, it's it's but it's an 1134 01:05:36,720 --> 01:05:41,440 Speaker 1: interesting thing. It's intriguing that more burger, more suicide, but 1135 01:05:41,560 --> 01:05:46,400 Speaker 1: also more cancer and more just health problems in general. Everything. Yeah, 1136 01:05:47,360 --> 01:05:51,600 Speaker 1: And the screwy part is it's more of everything in general. 1137 01:05:51,880 --> 01:05:53,440 Speaker 1: So I would say that it's could be one of 1138 01:05:53,520 --> 01:05:56,160 Speaker 1: two things. Uh, and I don't buy any of these series, 1139 01:05:56,200 --> 01:05:57,800 Speaker 1: but might have been to your poverty or any of 1140 01:05:57,800 --> 01:06:01,840 Speaker 1: that crap. It's all crap. Either a migration of a 1141 01:06:01,880 --> 01:06:07,040 Speaker 1: significantly different, genetically different population into the area at some point, 1142 01:06:07,200 --> 01:06:10,320 Speaker 1: like around the turn of the twentieth century, or a 1143 01:06:10,440 --> 01:06:14,320 Speaker 1: change in their water supply. Um, you know, they might 1144 01:06:14,360 --> 01:06:17,280 Speaker 1: have started started sourcing their water supply somewhere else. I mean, hey, 1145 01:06:17,840 --> 01:06:20,960 Speaker 1: I probably checked the water. I think that it's probably 1146 01:06:21,000 --> 01:06:24,520 Speaker 1: a combination of several of these things. I also think 1147 01:06:24,560 --> 01:06:27,280 Speaker 1: that you're the migration is a good thing to point 1148 01:06:27,320 --> 01:06:32,760 Speaker 1: out because until what was it the I mean, in 1149 01:06:32,880 --> 01:06:39,400 Speaker 1: terms of massive migrations of people from genetically different areas, 1150 01:06:39,760 --> 01:06:42,520 Speaker 1: you didn't see a whole lot of that happening until 1151 01:06:42,600 --> 01:06:45,680 Speaker 1: I guess maybe the less hundred years on a grand scale. 1152 01:06:46,160 --> 01:06:49,280 Speaker 1: And so it may be that the people who were 1153 01:06:49,320 --> 01:06:53,240 Speaker 1: there all so genetically similar that that is part of it. 1154 01:06:53,400 --> 01:06:56,920 Speaker 1: We won't and we won't see that change until after 1155 01:06:57,080 --> 01:06:59,040 Speaker 1: we've got you know this, I'm just gonna call it 1156 01:06:59,080 --> 01:07:03,439 Speaker 1: the new gene pool introduction is then going to bring 1157 01:07:03,480 --> 01:07:06,680 Speaker 1: in the different genes that are then going to make 1158 01:07:06,720 --> 01:07:10,400 Speaker 1: it so that you're not as prone to getting one 1159 01:07:10,480 --> 01:07:13,400 Speaker 1: of these things that everybody seems to be having. Yeah, 1160 01:07:13,440 --> 01:07:15,680 Speaker 1: but I guess when we're really talking about that, right, 1161 01:07:15,680 --> 01:07:19,120 Speaker 1: we're just talking about the percentages above average, Right, so 1162 01:07:19,160 --> 01:07:22,959 Speaker 1: we're saying the population shift was about population shift, which 1163 01:07:23,040 --> 01:07:28,720 Speaker 1: is is significant statistically, but realistically, I mean with a 1164 01:07:28,720 --> 01:07:31,959 Speaker 1: lot of the like refugee migrations that are happening right now, 1165 01:07:32,480 --> 01:07:35,480 Speaker 1: I'm sure that you see cities that are changing population 1166 01:07:35,520 --> 01:07:38,720 Speaker 1: demographics like that these days. And so it would be 1167 01:07:38,720 --> 01:07:43,560 Speaker 1: interesting to see was there something like a famine or something, 1168 01:07:44,600 --> 01:07:47,880 Speaker 1: you know, within a hundred years of when we're seeing 1169 01:07:47,920 --> 01:07:51,840 Speaker 1: this that pushed of the population to be genetically different 1170 01:07:51,920 --> 01:07:55,200 Speaker 1: that just happened to have a shorter lifespan anyway, shorter 1171 01:07:55,440 --> 01:07:58,360 Speaker 1: anticipated lifespan, or you know the fact that they were 1172 01:07:58,360 --> 01:08:00,960 Speaker 1: fleeing a famine and they had food and security and 1173 01:08:01,080 --> 01:08:04,640 Speaker 1: they've passed that down to generations and that may work 1174 01:08:04,680 --> 01:08:08,040 Speaker 1: itself out. I mean, those are all things that I think, 1175 01:08:08,080 --> 01:08:10,560 Speaker 1: to us, because we're so used to having the Internet 1176 01:08:10,840 --> 01:08:13,120 Speaker 1: and all of this information, seems like it would be 1177 01:08:13,200 --> 01:08:15,640 Speaker 1: really easy to find out. But I think probably that's 1178 01:08:15,680 --> 01:08:22,200 Speaker 1: just almost impossible. Yeah, it's difficult, but it's it could go. 1179 01:08:22,400 --> 01:08:25,040 Speaker 1: I mean, I am I realized I'm about to do 1180 01:08:25,080 --> 01:08:26,920 Speaker 1: what you just did earlier, which is I'm about to 1181 01:08:27,040 --> 01:08:32,200 Speaker 1: question my own theory because it's been seen before where 1182 01:08:32,200 --> 01:08:35,879 Speaker 1: when you get an influx of people who were genetically different, 1183 01:08:36,200 --> 01:08:39,360 Speaker 1: and let's say that they were fleeing an area where 1184 01:08:39,400 --> 01:08:43,080 Speaker 1: they always had a bit of a food scarcity. So 1185 01:08:43,200 --> 01:08:47,360 Speaker 1: from an a genetic level, they were inclined to acquire 1186 01:08:47,439 --> 01:08:50,520 Speaker 1: more body fat because that is the way you survive, 1187 01:08:51,320 --> 01:08:55,839 Speaker 1: and suddenly to be put into this food rich environment 1188 01:08:56,000 --> 01:09:00,120 Speaker 1: or over rich environment, that could then push them into 1189 01:09:00,320 --> 01:09:05,360 Speaker 1: some other unhealthy spectrum. I mean, I also don't know. 1190 01:09:05,720 --> 01:09:07,320 Speaker 1: Think I throw my hands up because it's like I'm 1191 01:09:07,360 --> 01:09:09,040 Speaker 1: damned if I do it, I damned if I don't. Yeah, 1192 01:09:09,040 --> 01:09:11,080 Speaker 1: I think I think that really the key to this 1193 01:09:11,120 --> 01:09:13,439 Speaker 1: is genetics. They need to just like you know, you know, 1194 01:09:13,560 --> 01:09:15,760 Speaker 1: grab a bunch of these. I don't know how to 1195 01:09:16,240 --> 01:09:20,120 Speaker 1: call glass legions. I don't know, so I'll just say 1196 01:09:20,120 --> 01:09:25,280 Speaker 1: people from Glasgow, for example, size. I think they need 1197 01:09:25,280 --> 01:09:27,920 Speaker 1: to like and they need to like look at start 1198 01:09:27,920 --> 01:09:30,439 Speaker 1: looking at their jeans and seeing what makes if they're 1199 01:09:30,439 --> 01:09:33,640 Speaker 1: actually different, because I haven't bet than they are, I think, 1200 01:09:34,400 --> 01:09:36,360 Speaker 1: And it's probably just like I said, due to some 1201 01:09:36,640 --> 01:09:42,879 Speaker 1: migration or the plutonium processing facility things. The Scottis showmer 1202 01:09:42,880 --> 01:09:46,559 Speaker 1: Simpson or no, it's cousin Willie. That's who it is. 1203 01:09:47,560 --> 01:09:50,559 Speaker 1: Groundskeeper Willie, ground groundskeeper will He didn't actually do any 1204 01:09:50,600 --> 01:09:53,639 Speaker 1: plutonium stuff. He took care of the school. Yeah, that's 1205 01:09:53,640 --> 01:09:56,720 Speaker 1: because he got out of Glasgow. Yeah, as smart as 1206 01:09:56,880 --> 01:10:02,280 Speaker 1: can be. Well, uh, let's go ahead and give folks here, 1207 01:10:02,320 --> 01:10:04,280 Speaker 1: because that's really all we've got in our theories and 1208 01:10:04,479 --> 01:10:08,280 Speaker 1: are debating here. We've got some pertinent details. As always. 1209 01:10:08,439 --> 01:10:13,400 Speaker 1: We have our website, which is Thinking Sideways podcast dot com. 1210 01:10:13,479 --> 01:10:17,000 Speaker 1: You can find this episode, any past episode will have 1211 01:10:17,080 --> 01:10:20,519 Speaker 1: some of our research links on there um and of 1212 01:10:20,560 --> 01:10:22,800 Speaker 1: course on the right hand side bar we've got some 1213 01:10:22,880 --> 01:10:26,679 Speaker 1: other things on the website. There is the PayPal button, 1214 01:10:26,760 --> 01:10:31,280 Speaker 1: There is the link for merchandise and for Patreon PayPal 1215 01:10:31,640 --> 01:10:36,120 Speaker 1: one time donation, which you're totally you can totally do. 1216 01:10:36,240 --> 01:10:39,320 Speaker 1: We appreciate that, that'd be really awesome, but it is 1217 01:10:39,600 --> 01:10:45,880 Speaker 1: again volunteering. We have shirts, coffee cops, phone cases, merchandise 1218 01:10:46,000 --> 01:10:49,519 Speaker 1: like that available through Zazzle. There's a link to that 1219 01:10:49,560 --> 01:10:52,680 Speaker 1: on the website. And then Patreon is on their Patreon 1220 01:10:52,720 --> 01:10:55,400 Speaker 1: dot com. So if you would like to give to 1221 01:10:55,439 --> 01:10:59,439 Speaker 1: the show at a recurring basis, that is available. Yeah, 1222 01:10:59,479 --> 01:11:02,880 Speaker 1: phone ring drinking if you want to go straight to 1223 01:11:03,080 --> 01:11:04,680 Speaker 1: the link will take you to it, but it is 1224 01:11:04,720 --> 01:11:09,479 Speaker 1: Patreon dot com. Slash thinking sideways strictly optional. And don't 1225 01:11:09,479 --> 01:11:12,160 Speaker 1: forget when you pledge, you're not just giving us like 1226 01:11:12,360 --> 01:11:15,160 Speaker 1: five bucks. You're giving you're pledging like five bucks in episodes. 1227 01:11:15,200 --> 01:11:19,680 Speaker 1: So remember remember that is by episode, So just keep 1228 01:11:19,720 --> 01:11:22,000 Speaker 1: that in mind. So when you pledge fifty cents, don't 1229 01:11:22,000 --> 01:11:25,320 Speaker 1: feel cheap a lot of money. And if you pledge 1230 01:11:25,360 --> 01:11:29,880 Speaker 1: fifty bucks, well more, that would be great, but just 1231 01:11:29,920 --> 01:11:32,519 Speaker 1: be careful. Um. Now, when you find us out on 1232 01:11:32,600 --> 01:11:35,280 Speaker 1: the wild world of the Internet, you'll find us in 1233 01:11:35,320 --> 01:11:38,200 Speaker 1: a number of places, one of those being iTunes. If 1234 01:11:38,200 --> 01:11:40,800 Speaker 1: you're on iTunes and you use it, go ahead and 1235 01:11:40,880 --> 01:11:44,519 Speaker 1: leave us a comment and a rating and subscribe. We 1236 01:11:44,560 --> 01:11:47,360 Speaker 1: are of course on all of the streaming sites, so 1237 01:11:47,479 --> 01:11:50,679 Speaker 1: you can get us through there as well. We are 1238 01:11:50,760 --> 01:11:53,439 Speaker 1: on social media, so we're on Facebook. We've got the 1239 01:11:53,439 --> 01:11:57,160 Speaker 1: Facebook group and the Facebook page, and we're also on Twitter, 1240 01:11:57,360 --> 01:11:59,920 Speaker 1: which is Thinking Sideways without the G in the mid. 1241 01:12:00,840 --> 01:12:03,720 Speaker 1: And we've also got sub Reddit, which is always fun. 1242 01:12:04,560 --> 01:12:11,000 Speaker 1: Interesting you've never been there, sure feel like I don't 1243 01:12:11,000 --> 01:12:13,720 Speaker 1: even know how to type the word going on out 1244 01:12:13,760 --> 01:12:20,519 Speaker 1: there Reddit. It's like, yeah, there's a silent in there. 1245 01:12:21,040 --> 01:12:22,599 Speaker 1: I knew it. I knew that. That's why I can't 1246 01:12:22,600 --> 01:12:26,280 Speaker 1: find it. Yeah, And of course if you want to, 1247 01:12:26,400 --> 01:12:28,759 Speaker 1: you can always send us an email. Our email address 1248 01:12:28,880 --> 01:12:33,840 Speaker 1: is Thinking Thinking Sideways podcast at gmail dot com. Uh So, 1249 01:12:33,960 --> 01:12:38,519 Speaker 1: if you've got suggestions for stories, you've got feedback, anything 1250 01:12:38,560 --> 01:12:40,960 Speaker 1: like that, definitely feel free to send us an email. 1251 01:12:41,520 --> 01:12:44,760 Speaker 1: And I think that is all of those details, so 1252 01:12:44,840 --> 01:12:48,680 Speaker 1: anything else you guys, I'm all right, Well, that's it, 1253 01:12:48,840 --> 01:12:50,760 Speaker 1: thanks everybody, and we'll talk to you again next week. 1254 01:12:51,080 --> 01:13:00,400 Speaker 1: Byeye bye guys. Three