1 00:00:08,960 --> 00:00:13,080 Speaker 1: Hey, everybody, Welcome to another edition of Wisdom Wednesdays. Today, 2 00:00:13,320 --> 00:00:18,520 Speaker 1: I want to have a chat about epidemiological research, especially 3 00:00:18,680 --> 00:00:23,480 Speaker 1: in nutrition, and highlight the limitations of it by looking 4 00:00:23,520 --> 00:00:25,599 Speaker 1: at a study that was just released. But before we 5 00:00:25,640 --> 00:00:28,760 Speaker 1: get into that study, and there's a guy called Professor 6 00:00:28,880 --> 00:00:32,960 Speaker 1: John Eonidis who's at Stanford University. He's a professor there 7 00:00:33,360 --> 00:00:37,640 Speaker 1: and he is the most cited research scientist in the world. 8 00:00:37,800 --> 00:00:41,839 Speaker 1: So this guy is a brilliant research scientist. And he's 9 00:00:41,880 --> 00:00:44,400 Speaker 1: actually written a paper, and I think it's about a 10 00:00:44,400 --> 00:00:49,920 Speaker 1: book as well, called why most published research Findings are False? 11 00:00:50,440 --> 00:00:53,720 Speaker 1: And he highlights in that a whole heap of issues 12 00:00:54,080 --> 00:00:56,480 Speaker 1: such as what's called pe hacking, where you do a 13 00:00:56,480 --> 00:00:59,040 Speaker 1: whole heap of statistics and then you dive in and 14 00:00:59,080 --> 00:01:01,680 Speaker 1: try and find the one that are significant and then 15 00:01:01,760 --> 00:01:04,080 Speaker 1: you talk about them that that's how your study has 16 00:01:04,120 --> 00:01:07,280 Speaker 1: been designed. He also talks about conflicts of interest, and 17 00:01:07,319 --> 00:01:11,440 Speaker 1: I've talked about conflicts of interest in research and especially 18 00:01:11,680 --> 00:01:14,920 Speaker 1: in nutrition. You know, we've got conflicts of interest from 19 00:01:14,959 --> 00:01:18,039 Speaker 1: the dirty industry, from the meat industry sponsoring studies, and 20 00:01:18,160 --> 00:01:21,360 Speaker 1: now a whole heap on the other side from vegans 21 00:01:22,000 --> 00:01:27,880 Speaker 1: and sponsoring studies and real selective reporting, and all of 22 00:01:27,920 --> 00:01:31,679 Speaker 1: this can lead to incorrect, incorrect conclusions being drawn by 23 00:01:31,680 --> 00:01:35,880 Speaker 1: the data. Right now, he has also said, and I 24 00:01:35,920 --> 00:01:41,080 Speaker 1: love this quote, he said, we must recognize that nutritional 25 00:01:41,319 --> 00:01:46,080 Speaker 1: epidemiology is a dead horse and we need to bury 26 00:01:46,160 --> 00:01:46,920 Speaker 1: the carcass. 27 00:01:47,280 --> 00:01:47,480 Speaker 2: Right. 28 00:01:47,640 --> 00:01:53,040 Speaker 1: So what he means by that is observational studies in 29 00:01:53,320 --> 00:01:57,680 Speaker 1: every part of science apart from nutrition. Really we use 30 00:01:57,720 --> 00:02:02,920 Speaker 1: observational studies to generate highypothesis to then go and test hypothesis. 31 00:02:03,200 --> 00:02:06,040 Speaker 1: But in the world of nutritional science, we seem to 32 00:02:06,040 --> 00:02:12,079 Speaker 1: be using observational studies to actually inform public health. And 33 00:02:12,200 --> 00:02:14,600 Speaker 1: the worst one was in the nineteen seventies when there 34 00:02:14,600 --> 00:02:18,120 Speaker 1: was this whole association with cholesterol and heart disease, and 35 00:02:18,200 --> 00:02:20,840 Speaker 1: then this war on fat, which I think has then 36 00:02:21,040 --> 00:02:24,880 Speaker 1: spawned a whole heap of issues because we've switched to 37 00:02:25,680 --> 00:02:28,400 Speaker 1: high carbohydrate diets and a lot of it has been 38 00:02:28,480 --> 00:02:31,280 Speaker 1: ultra processed foods. Right now, that's an issue in and 39 00:02:31,280 --> 00:02:35,239 Speaker 1: of itself, But let's get back and examine those statements 40 00:02:35,280 --> 00:02:38,480 Speaker 1: through the lens of a very recent study that's just 41 00:02:38,680 --> 00:02:43,080 Speaker 1: been published. The title of this study is Meat Consumption 42 00:02:43,320 --> 00:02:48,560 Speaker 1: and Incident Type two diabetes and individual participant federated meta 43 00:02:48,600 --> 00:02:53,079 Speaker 1: analysis at one point ninety seven sorry million adults with 44 00:02:53,080 --> 00:02:57,120 Speaker 1: one hundred thousand incident cases from thirty one cohorts in 45 00:02:57,200 --> 00:03:01,520 Speaker 1: twenty countries, and it's published in Lancet Diabetes Indochronology. So 46 00:03:01,560 --> 00:03:06,880 Speaker 1: that's a very good publication and it's a big meta analysis. 47 00:03:07,160 --> 00:03:10,320 Speaker 1: So what they did, let's have a look at it. 48 00:03:11,320 --> 00:03:13,680 Speaker 1: And we've actually we've been here before, right, where these 49 00:03:13,720 --> 00:03:18,160 Speaker 1: observational studies are made, claims are made about the health risks, 50 00:03:18,280 --> 00:03:20,679 Speaker 1: and in this case of eating meat, the media gets 51 00:03:20,720 --> 00:03:24,679 Speaker 1: hold of it and then suddenly everybody's talking about it, right, 52 00:03:25,240 --> 00:03:28,760 Speaker 1: And so these findings were quickly picked up by the 53 00:03:28,800 --> 00:03:31,400 Speaker 1: New York Times, and now they are in lots of 54 00:03:31,400 --> 00:03:34,280 Speaker 1: different newspapers, and I've read them in a different one, right. 55 00:03:34,360 --> 00:03:36,520 Speaker 2: But let's have a look at the study. 56 00:03:36,600 --> 00:03:38,640 Speaker 1: So what they did was they set out to investigate 57 00:03:38,680 --> 00:03:41,640 Speaker 1: a potential link between meat consumption and diabetes on a 58 00:03:41,680 --> 00:03:45,160 Speaker 1: global scale. So they conducted a meta analysis. So that's 59 00:03:45,200 --> 00:03:47,960 Speaker 1: a study of studies. Here they pull all the data 60 00:03:48,440 --> 00:03:51,160 Speaker 1: and they use data from nearly two million adults across 61 00:03:51,240 --> 00:03:55,200 Speaker 1: thirty one independent groups or cohorts as part of a 62 00:03:55,200 --> 00:03:58,440 Speaker 1: big project called the Interconnect Project, which is an international 63 00:03:58,480 --> 00:04:03,800 Speaker 1: research too explore genetic and environmental risk factors for obesity 64 00:04:03,880 --> 00:04:08,960 Speaker 1: and diabetes. So this study spanned populations from America, Europe, 65 00:04:09,000 --> 00:04:14,040 Speaker 1: Asia and beyond to give a broad perspective on global health, 66 00:04:14,120 --> 00:04:16,039 Speaker 1: eating habits and health outcomes. 67 00:04:16,400 --> 00:04:18,640 Speaker 2: So the diets were self reported, which. 68 00:04:18,480 --> 00:04:20,320 Speaker 1: Is an issue in and of itself which I've talked 69 00:04:20,360 --> 00:04:23,760 Speaker 1: about previously. But then meat consumption was divided into three 70 00:04:23,760 --> 00:04:28,800 Speaker 1: categories unprocessed red meat, processed meat, and poultry. And then 71 00:04:28,880 --> 00:04:31,880 Speaker 1: they looked at the cases of type two diabetes. They 72 00:04:31,920 --> 00:04:35,640 Speaker 1: were tracked using medical records and diabetes medication use and 73 00:04:35,760 --> 00:04:40,560 Speaker 1: other self reports, and then validated with additional checks like 74 00:04:41,000 --> 00:04:44,520 Speaker 1: prescriptions and people's HbA one sea level. 75 00:04:44,520 --> 00:04:45,800 Speaker 2: So they didn't just ask them about it. 76 00:04:45,800 --> 00:04:47,719 Speaker 1: They went and looked at some of the data and 77 00:04:47,800 --> 00:04:50,360 Speaker 1: anybody who had diabetes at the start of the study 78 00:04:50,440 --> 00:04:51,400 Speaker 1: was excluded. 79 00:04:51,440 --> 00:04:52,040 Speaker 2: So they were. 80 00:04:51,920 --> 00:04:56,760 Speaker 1: Looking at the impact of meat consumption on driving type 81 00:04:56,760 --> 00:05:00,599 Speaker 1: two diabetes. And over a median period follow up of 82 00:05:00,720 --> 00:05:03,880 Speaker 1: ten years, there was more than one hundred and seven 83 00:05:04,000 --> 00:05:07,680 Speaker 1: thousand cases of type two diabetes were recorded. So these 84 00:05:07,680 --> 00:05:10,760 Speaker 1: are new cases studying people over time, and they found 85 00:05:10,800 --> 00:05:13,359 Speaker 1: in the study that increased intake of all three types 86 00:05:13,400 --> 00:05:18,320 Speaker 1: of meat, red meat, process meat, and poultry was associated 87 00:05:18,360 --> 00:05:22,839 Speaker 1: with a statistically significant increase in diabetes risk, even after 88 00:05:22,880 --> 00:05:28,680 Speaker 1: adjusting for factors like demographics, smoking, BMI, alcohol consumption, physical activity, 89 00:05:29,040 --> 00:05:31,520 Speaker 1: and other dietary habits. And I've talked about this before 90 00:05:31,560 --> 00:05:34,640 Speaker 1: where they try to use statistics to control for these 91 00:05:34,720 --> 00:05:40,000 Speaker 1: confounding factors, and processmate showed the strongest association, with a 92 00:05:40,200 --> 00:05:45,120 Speaker 1: fifteen percent increase risk for every fifty grams of processed 93 00:05:45,160 --> 00:05:48,560 Speaker 1: meat per day consumed, and the next was red meat, 94 00:05:48,640 --> 00:05:51,800 Speaker 1: and then the next was poultry. They had both smaller 95 00:05:51,880 --> 00:05:56,440 Speaker 1: but still significant increased risk of developing diabetes. Now, this 96 00:05:56,480 --> 00:05:59,440 Speaker 1: is where we need to hit pause and consider one 97 00:05:59,480 --> 00:06:04,080 Speaker 1: of the most important lessons in epidemiological research and especially 98 00:06:04,120 --> 00:06:09,000 Speaker 1: in nutrition. Correlation does not equal causation. So, for an 99 00:06:09,040 --> 00:06:13,000 Speaker 1: example on this ice cream sales are much higher on 100 00:06:13,080 --> 00:06:16,680 Speaker 1: hot days. So are robberies because people tend to be 101 00:06:16,920 --> 00:06:20,760 Speaker 1: out and they get robbed more. But that's a correlation, 102 00:06:21,200 --> 00:06:25,640 Speaker 1: is the increased incidents about ice cream sales and robberies. 103 00:06:26,080 --> 00:06:29,800 Speaker 1: That doesn't mean that ice cream sales cause robberies, right, So. 104 00:06:29,800 --> 00:06:31,760 Speaker 2: That's important distinction to know. 105 00:06:32,440 --> 00:06:35,520 Speaker 1: Now, these results in this study, they show an association 106 00:06:35,680 --> 00:06:38,360 Speaker 1: between red meat intake and the instant diabetes, but they 107 00:06:38,400 --> 00:06:42,680 Speaker 1: don't actually tell us if med meat consumption actually causes diabeties. 108 00:06:42,720 --> 00:06:44,080 Speaker 1: And I'm going to come back to this later because 109 00:06:44,080 --> 00:06:48,720 Speaker 1: it's really important. This distinction is critical. Just because two 110 00:06:48,800 --> 00:06:51,479 Speaker 1: things are linked doesn't mean that one causes the other. 111 00:06:52,080 --> 00:06:55,440 Speaker 1: So in this world of diet and disease, there's countless 112 00:06:55,520 --> 00:07:00,000 Speaker 1: variables at play that could influence that both meat into 113 00:07:00,200 --> 00:07:05,080 Speaker 1: and diabetes risks. So things like socioeconomic status, access to healthcare, 114 00:07:05,480 --> 00:07:09,200 Speaker 1: other datary habits, lifestyle choices, they all play significant roles 115 00:07:09,200 --> 00:07:11,720 Speaker 1: whether or not you exercise or smoke. And we know 116 00:07:11,840 --> 00:07:16,240 Speaker 1: that people with higher process, especially meat intake, they are 117 00:07:16,280 --> 00:07:18,760 Speaker 1: often lower income because it's cheaper, so the elite that 118 00:07:18,840 --> 00:07:22,960 Speaker 1: stuff they often smoke more. They often had less access 119 00:07:23,080 --> 00:07:27,520 Speaker 1: to healthcare and less opportunity to engage in health promoting behaviors. 120 00:07:27,560 --> 00:07:30,600 Speaker 1: And we see this over and over again that lower 121 00:07:30,720 --> 00:07:36,400 Speaker 1: socioeconomic status people have got higher diseases across the board. Now, 122 00:07:36,440 --> 00:07:38,680 Speaker 1: this study did try to adjust for some of these, 123 00:07:38,720 --> 00:07:42,240 Speaker 1: but it is impossible to account for those things perfectly. 124 00:07:43,240 --> 00:07:46,080 Speaker 1: And if we dive in a little bit and look 125 00:07:46,080 --> 00:07:50,280 Speaker 1: at they adjusted for body mass index BMI in the study, 126 00:07:50,640 --> 00:07:54,360 Speaker 1: and when they included BMI in the statistical model, the 127 00:07:54,480 --> 00:07:58,480 Speaker 1: risk associated with meat consumption was significantly reduced by half 128 00:07:58,640 --> 00:08:02,280 Speaker 1: pretty much. So this on its own suggests that factors 129 00:08:02,320 --> 00:08:06,400 Speaker 1: that are related to general health rather than meat consumption 130 00:08:06,520 --> 00:08:10,400 Speaker 1: per se, might be driving the association with diabetes. I mean, 131 00:08:10,480 --> 00:08:12,440 Speaker 1: think about it makes sense if you've got a higher BMI, 132 00:08:12,760 --> 00:08:15,120 Speaker 1: that's a known risk factor for type two diabetes. 133 00:08:15,440 --> 00:08:17,760 Speaker 2: And if people who eat more meat also. 134 00:08:17,520 --> 00:08:20,720 Speaker 1: Tend to hire BMI, then it's not necessarily the meat 135 00:08:20,720 --> 00:08:22,880 Speaker 1: that's doing it, but it can be the BMI or 136 00:08:22,920 --> 00:08:27,400 Speaker 1: their overall health profile. So another point to note on 137 00:08:27,480 --> 00:08:31,760 Speaker 1: this is the inconsistency of findings across different populations. So 138 00:08:31,880 --> 00:08:35,000 Speaker 1: you dig into the paper. There was no significant association 139 00:08:35,080 --> 00:08:38,440 Speaker 1: between meat consumption and type two diabetes in the people 140 00:08:38,600 --> 00:08:42,520 Speaker 1: in the Eastern Mediterranean and people in Southeast Asia, and 141 00:08:42,559 --> 00:08:46,840 Speaker 1: the link between poultry intaken diabetes was only significant in 142 00:08:46,880 --> 00:08:49,920 Speaker 1: the European cohorts but not anywhere else. So why does 143 00:08:50,000 --> 00:08:53,800 Speaker 1: poultry cause increased diabetes in Europe but not anywhere else? 144 00:08:54,120 --> 00:08:57,880 Speaker 1: And why does red meat and particularly processed meat cause 145 00:08:58,480 --> 00:09:01,320 Speaker 1: increased risk of diabetes in some places, but not an 146 00:09:01,360 --> 00:09:05,920 Speaker 1: Eastern Mediterranea and not in Usia. So here we go again. 147 00:09:06,000 --> 00:09:09,080 Speaker 1: This is this observational study and a wave of media hype. 148 00:09:09,200 --> 00:09:14,280 Speaker 2: Now let's then follow this and think through it logically. 149 00:09:14,760 --> 00:09:19,880 Speaker 1: So what I did is I kind of tested the 150 00:09:20,000 --> 00:09:24,440 Speaker 1: kind of assumptions here, right, So if this observational study 151 00:09:24,600 --> 00:09:29,040 Speaker 1: is true and red meat does cause diabetes, then what 152 00:09:29,080 --> 00:09:31,679 Speaker 1: we should see, and this is the way that science 153 00:09:31,720 --> 00:09:34,840 Speaker 1: should work, is that is a hypothesis that we then 154 00:09:34,880 --> 00:09:37,200 Speaker 1: go and test. And the easy way to test that 155 00:09:37,280 --> 00:09:40,960 Speaker 1: hypothesis is to get a bunch of people and get 156 00:09:41,240 --> 00:09:44,000 Speaker 1: some of them to reduce their risk of red meat 157 00:09:44,120 --> 00:09:48,400 Speaker 1: consumption and process meat and then look and see if 158 00:09:48,440 --> 00:09:52,199 Speaker 1: they have less diabetes, then the similar amount of. 159 00:09:52,120 --> 00:09:53,840 Speaker 2: People who don't reduce theirs. 160 00:09:54,240 --> 00:09:57,560 Speaker 1: So what I did was I jumped onto illicit dot com. 161 00:09:57,559 --> 00:10:00,320 Speaker 1: So this is a research to use by researchers, and 162 00:10:00,360 --> 00:10:04,120 Speaker 1: you type in a research question, right, and I typed 163 00:10:04,160 --> 00:10:07,440 Speaker 1: into question what is the evidence that reducing red meat 164 00:10:07,440 --> 00:10:09,479 Speaker 1: consumption can manage diabetes? 165 00:10:09,559 --> 00:10:12,840 Speaker 2: Please find intervention studies. And what the illicit. 166 00:10:12,440 --> 00:10:16,600 Speaker 1: Does is then will find the top eight papers in 167 00:10:16,679 --> 00:10:19,680 Speaker 1: the field, and so I looked at these top eight 168 00:10:19,720 --> 00:10:22,840 Speaker 1: papers and I'll actually put links in them. Well, particularly 169 00:10:23,120 --> 00:10:25,559 Speaker 1: I'll put links to the ones that were in intervention 170 00:10:25,720 --> 00:10:28,160 Speaker 1: study to say if reducing it, because some of them 171 00:10:28,160 --> 00:10:31,000 Speaker 1: were observational studies. And let's talk about the first one, 172 00:10:31,040 --> 00:10:34,520 Speaker 1: potential effects of red meat. Reduced red meat compared with 173 00:10:34,600 --> 00:10:37,840 Speaker 1: increased fiber intake on glucose metabolism and liver fat content 174 00:10:38,240 --> 00:10:41,319 Speaker 1: a randomized and controlled atary intervention studies. So this is 175 00:10:41,360 --> 00:10:45,040 Speaker 1: the sort of study we're after. And it found caloric restriction, 176 00:10:45,520 --> 00:10:49,200 Speaker 1: not reduced red meat or increased fiber led to improved 177 00:10:49,200 --> 00:10:52,400 Speaker 1: glucose metabolism and reduce liver fat in subjects at risk 178 00:10:52,480 --> 00:10:55,560 Speaker 1: of type two diabetes. So reducing red meat did nothing. 179 00:10:56,080 --> 00:10:58,400 Speaker 1: And then the next one, modern consumption of red meat 180 00:10:58,440 --> 00:11:01,360 Speaker 1: compared to soy or non soi leg gloom has no 181 00:11:01,520 --> 00:11:05,360 Speaker 1: adverse effect on cardio metabolic factors in patients with TAPE 182 00:11:05,360 --> 00:11:08,000 Speaker 1: two diabetes. They found moderate consumption of red meat has 183 00:11:08,080 --> 00:11:11,199 Speaker 1: no adverse effect on cardio metabolic factors compared to soy 184 00:11:11,679 --> 00:11:14,600 Speaker 1: or non soi legooms in patients with type two diabetes. 185 00:11:14,600 --> 00:11:18,680 Speaker 1: So they were comparing an intervention. Then they looked here 186 00:11:18,840 --> 00:11:23,480 Speaker 1: and another one faculty opinions recommended of effect of lower 187 00:11:23,559 --> 00:11:27,199 Speaker 1: versus higher red meat intake on cardio metabolic and cancer outcomes. 188 00:11:27,200 --> 00:11:31,239 Speaker 1: A systematic review of randomized trials. Remember cardio metabolic includes diabetes. 189 00:11:31,960 --> 00:11:34,160 Speaker 1: They found load of very low certainty evidence suggests that 190 00:11:34,200 --> 00:11:37,160 Speaker 1: reducing red meat intake may have little or no effect 191 00:11:37,200 --> 00:11:41,719 Speaker 1: on cardio metabolic and cancer outcomes. And then there's another one, 192 00:11:42,360 --> 00:11:46,720 Speaker 1: red meat, dirty and insulin sensitivity or randomized crossover intervention study. 193 00:11:46,760 --> 00:11:49,280 Speaker 1: This is the really good study of randomized one. We 194 00:11:49,440 --> 00:11:53,080 Speaker 1: then cross people over to the different arms. They find 195 00:11:53,160 --> 00:11:57,360 Speaker 1: a diet high in lean red meat improved insulin sensitivity 196 00:11:57,720 --> 00:12:02,360 Speaker 1: compared to high dirty diet in overweight and obese subjects. 197 00:12:02,640 --> 00:12:05,920 Speaker 1: And then another one substituting lin beef for carbohydrate in 198 00:12:05,960 --> 00:12:09,600 Speaker 1: a healthy dietary pattern does not adversely affect the cardio 199 00:12:09,640 --> 00:12:13,000 Speaker 1: metabolic risk factor of profile of men and women at 200 00:12:13,080 --> 00:12:17,200 Speaker 1: risk for tapto biobetes. They found that actually taking out 201 00:12:17,240 --> 00:12:21,600 Speaker 1: carbohydrate and putting in beef actually has no adverse effect 202 00:12:21,920 --> 00:12:25,760 Speaker 1: on cardio metabolic risk factors and the risk of developing 203 00:12:25,760 --> 00:12:28,200 Speaker 1: type two diabetes. And then the last one, effects of 204 00:12:28,240 --> 00:12:31,920 Speaker 1: total red meat intake on glycemic control and inflammatory biomarkers, 205 00:12:31,960 --> 00:12:36,760 Speaker 1: and meta analysis of randomized control trials. Total red meat 206 00:12:36,760 --> 00:12:40,559 Speaker 1: consumption for up to sixteen weeks does not affect biomarkers 207 00:12:40,559 --> 00:12:44,800 Speaker 1: of glycemic control or inflammation in adults at risk of 208 00:12:44,880 --> 00:12:50,880 Speaker 1: cardio metabolic disease. So all of this taken together, suggests 209 00:12:51,000 --> 00:12:55,240 Speaker 1: that John Ionides is absolutely right, and we need to 210 00:12:55,640 --> 00:13:01,280 Speaker 1: realize that observational nutritional studies or a dead horse. 211 00:13:01,080 --> 00:13:02,880 Speaker 2: And we need to bury the corpse. Now. 212 00:13:02,920 --> 00:13:05,240 Speaker 1: I do just want to call it one little caveat 213 00:13:05,320 --> 00:13:08,800 Speaker 1: on that, because I have reported on observational studies, particularly 214 00:13:08,800 --> 00:13:11,560 Speaker 1: stuff from the UK Biobank. I've done a number of 215 00:13:11,559 --> 00:13:14,679 Speaker 1: things looking at risks of devention and stuff like that, 216 00:13:14,760 --> 00:13:18,840 Speaker 1: and exercise and strength. When we see observational studies that 217 00:13:19,040 --> 00:13:25,240 Speaker 1: are consistent that consistently so the same thing in different populations, 218 00:13:25,720 --> 00:13:30,640 Speaker 1: and there is a plausible biological mechanism, then you can 219 00:13:30,679 --> 00:13:33,240 Speaker 1: start to say, okay, well this is actually given us 220 00:13:33,280 --> 00:13:35,680 Speaker 1: some reasonable evidence that we then need to go and 221 00:13:35,760 --> 00:13:38,520 Speaker 1: test further with the randomized control trial. 222 00:13:38,559 --> 00:13:39,160 Speaker 2: And it's not. 223 00:13:39,120 --> 00:13:43,719 Speaker 1: Always possible to do a randomized control trial, but we 224 00:13:43,800 --> 00:13:47,640 Speaker 1: need to realize that you can't just take one study 225 00:13:48,240 --> 00:13:50,640 Speaker 1: and then have all of these headlines around it, and 226 00:13:50,920 --> 00:13:56,880 Speaker 1: especially have people influence or change their diets based on 227 00:13:56,880 --> 00:14:00,360 Speaker 1: one or a couple of pretty poor observational stuf allies. 228 00:14:00,800 --> 00:14:03,040 Speaker 2: That's it for this week, folks, Catch you next time.