Is there a relationship between the level of omega-3 fatty acids in the blood and death from any cause?

OmegaMatters: Episode 4

Hosts: Drs. Bill Harris & Kristina Harris Jackson

Guest: Nathan Tintle, PhD, Executive Director, Fatty Acid Research Institute (FARI)


Background & Key Takeaways:

A new research paper examining the relationship between the Omega-3 Index and risk for death from any and all causes was published in Nature Communications April 22, 2021. It showed that those people with higher omega-3 EPA and DHA blood levels (i.e., Omega-3 Index) lived longer than those with lower levels. In other words, those people who died with relatively low omega-3 levels died prematurely, i.e., all else being equal, they might have lived longer had their levels been higher.

Numerous studies have investigated the link between omega-3s and diseases affecting the heart, brain, eyes and joints, but few studies have examined their possible effects on lifespan.

In Japan, omega-3 intakes and blood levels are higher than most other countries in the world AND they happen to live longer than most. Coincidence? Possibly, or maybe a high Omega-3 Index is part of the explanation.

Studies reporting estimated dietary fish or omega-3 intake have reported benefits on risk for death from all causes, but “diet record” studies carry little weight because of the imprecision in getting at true EPA and DHA intakes. Studies using biomarkers – i.e., blood levels – of omega-3 are much more believable because the “exposure” variable is objective.

This new paper is from the FORCE – Fatty Acids & Outcomes Research – Consortium. FORCE is comprised of researchers around the world that have gathered data on blood fatty acid levels in large groups of study subjects (or cohorts) and have followed those individuals over many years to determine what diseases they develop. These data are then pooled to get a clearer picture of these relationships than a single cohort can provide. The current study focused on omega-3 levels and the risk for death during the follow-up period, and it is the largest study yet to do so.

Specifically, this report is a prospective analysis of pooled data from 17 separate cohorts from around the world, including 42,466 people followed for 16 years on average during which time 15,720 people died. When FORCE researchers examined the risk for death from any cause, the people who had the highest EPA+DHA levels (i.e., at the 90th percentile) had a statistically significant, 13% lower risk for death than people with EPA+DHA levels in the 10th percentile. When they looked at three major causes of death – cardiovascular disease, cancer and all other causes combined – they found statistically significant risk reductions (again comparing the 90th vs 10th percentile) of 15%, 11%, and 13%, respectively.

The range between the 10th and 90th percentile for EPA+DHA was (in terms of red blood cell membrane omega-3 levels, i.e., the Omega-3 Index) about 3.5% to 7.6%. From other research, an optimal Omega-3 Index is 8% or higher.

In the new paper, the authors noted that these findings suggest that omega-3 fatty acids may beneficially affect overall health and thus slow the aging process, and that they are not just good for heart disease.

“Since all of these analyses were statistically adjusted for multiple personal and medical factors (i.e., age, sex, weight, smoking, diabetes, blood pressure, etc., plus blood omega-6 fatty acid levels), we believe that these are the strongest data published to date supporting the view that over the long-term, having higher blood omega-3 levels can help maintain better overall health,” said Dr. Bill Harris, Founder of the Fatty Acid Research Institute (FARI), and lead author on this paper.

Dr. Harris co-developed the Omega-3 Index 17 years ago as an objective measure of the body’s omega-3 status. Measuring omega-3s in red blood cell membranes offers an accurate picture of one’s overall omega-3 intake during the last four to six months. To date, the Omega-3 Index has been featured in more than 200 research studies.

“This comprehensive look at observational studies of circulating omega-3 fatty acids indicates that the long chain omega-3s EPA, DPA, and DHA, usually obtained from seafood, are strongly associated with all-cause mortality, while levels of the plant omega-3 alpha-linolenic acid (ALA) are less so,” said Tom Brenna, PhD, Professor of Pediatrics, Human Nutrition, and Chemistry, Dell Medical School of the University of Texas at Austin. 


Guest Bios:

Dr. Nathan Tintle:

Dr Tintle holds a PhD in statistics from Stony Brook University. He has internationally recognized expertise in fatty acids, public health, genetics, and biomedical statistics via study design, survey instrument development, and standard and computationally intensive data analysis techniques. He has >100 peer-reviewed publications. Dr. Tintle also brings prior relevant experience as an executive director of a non-profit, research institute. As a researcher and research institute director he has led initiatives securing over $8 million of funding across 30+ major federally funded grant awards, in addition to securing substantial private and public charitable donations.



Kristina Harris Jackson: All right. Welcome to Omega Matters, our little show where my dad and I have casual conversations about health and nutrition, research, statistics on omega-3 fatty acids. I’m Kristina Harris Jackson. I’m the Director of Research at OmegaQuant Analytics. We specialize in fatty acid analysis. I am also a Nutritional Science Researcher and Registered Dietician.

Kristina Harris Jackson: My dad, Bill Harris, is a world renowned scientist in the field of nutrition and omega-3 fatty acids. Um, recently, I started a nonprofit research institute called the Fatty Acid Research Institute or FARI for short. Um, but he did start OmegaQuant over 10 years ago so we could offer omega-3 index testing, um, to clinicians and individuals.

Kristina Harris Jackson: So today, we are joined again by Dr. Nathan Tintle. And Nathan is now a, he’s Executive Director of FARI, I believe, but he’s also a, um, professor or expert in biostats. And so today, we’re going over an exciting new paper that my dad and Nathan wrote together along with the FORCE Consortium.

Kristina Harris Jackson: So first off, do you guys wanna talk about the paper?

Bill Harris: Yeah (laughs).

Kristina Harris Jackson: Start.

Bill Harris: Uh, [crosstalk] well, let’s talk about the … I’ll, I’ll talk about the FORCE Consortium-

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: … and, um, well, get, get right down to it. First of all, the paper was about, um, the relationship between omega-3 levels in the blood and risk for death, uh, death from any cause and risk for death from heart disease, cancer and everything else. And that was the general question. We did it within the context of a group called FORCE, which is the Fatty Acid Outcomes Research Coalition, which kind of spells FORCE. Don’t go too deeply into that. Um-

Kristina Harris Jackson: (laughs)

Bill Harris: Acronyms are pretty sloppy these day. Um, but this was started by Dr., uh, Dariush Mozaffarian, uh, who’s the Dean at, one of the deans at Tufts University. And Dari’s a Cardiologist and longterm a very productive omega-3 researcher. But he started this group several years ago to pull together, um, all the cohort studies around the world as much as possible that had fatty acid data at baseline and had followed different groups for different outcomes.

Bill Harris: And the idea was, “Let’s pull all these studies together.” Uh, and with the one we are, published yesterday in Nature Communications was one of those studies. Uh, and again, it was on omega-3 levels and its predictors of risk for total mortality. So that’s the, the, the overall introduction to it.

Kristina Harris Jackson: Yes. FORCE is a really, they have started to really put out a lot of interesting papers on fatty acids. So I can very much appreciate the work that FORCE does. Um, so with this study, you mentioned it’s somewhat of a meta-analysis. Um, can, Nathan, can you go ahead and talk about how this study might be a different kind of meta-analysis than what we’re used to?

Dr. Nathan Tintle: Yeah, so a lot of times, when you see meta-analysis published, uh, out there, what people have done, uh, is they’ve gone to already published studies in the peer reviewed literature and they try to kind of tell an overarching story from those individual papers. So you might have lots of small papers and some say there’s an association maybe between a blood biomarker and a disease, and some say there isn’t. And so meta-analysis tries to kind of pull all those results together and come with one overarching conclusion.

Dr. Nathan Tintle: And that’s a really laudable goal. There’s a lot of strengths to meta-analysis. You get lots of different cohorts represented, um, lots of, you know, usually you can repre- represent a larger population, uh, more diversity, things like this. But there’s some serious weaknesses to meta-analysis. And one of those is that all those individual analysis that you’ve pulled together have been done in a different way by different people.

Dr. Nathan Tintle: And what that means is that there’s a lot of stati- decisions that you’re making. A lot of them are statistical decisions about what co-variants to adjust for. How are we gonna account for this aspect of things? And so at the end of the day, sometimes the results of meta-analysis can be a little messy and hard to interpret, even though their goal is to try to tell this overarching story.

Dr. Nathan Tintle: So FORCE and this consortium that this paper is part of does have an advantage in the kind of meta-analysis that we do, because we all coordinate the analytic plan ahead of time. We all sit down and say, “How are we gonna decide what disease means in this context?” And so even though in those meta- typical meta-analysis there might be different definitions of disease, how are we gonna coordinate and harmonize that? And how are we gonna do the same on the blood biomarker? Um, and how are we gonna do the same on all the co-variants? How are we gonna handle Asia? How are we gonna decide which co-variants matter and, and all these things?

Dr. Nathan Tintle: And so at the end of the day, by working together and coordinating ahead of time, we have a streamlined har- harmonized analysis that we all agree upon, and so the story that we can tell is a much clearer one, uh, compared to a standard meta-analysis.

Kristina Harris Jackson: Yeah, that’s really well said. So now that we kind of know who did it and why it’s being done, uh, do you guys wanna go into some of the main findings?

Bill Harris: Yeah. Um, let me add one more thing to what Nathan said. Uh, another potential weakness of traditional meta-analysis is you only deal with published papers.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: So if there’s any data out there that’s not published, you don’t see it. And in the meta-analysis or in the, the paper we’re talking about today, over half of the … there were 17 cohorts, and well over half of those had never published, nev- never examined their own datasets for this question. So it’s all brand new data. Uh, and so you gets away from some of the publication bias-

Kristina Harris Jackson: Hm.

Bill Harris: that a, a standard meta-analysis could have. Uh, and, and it’s not that we’ve used every cohort possible on Earth. Uh, people have, you know, they volunteered to, to be part of this or, or not. And some have, some can, some can’t. But it’s certainly a step toward more transparency and more generalizability.

Kristina Harris Jackson: Mm-hmm (affirmative)

Bill Harris: Um, so I’ll tell you what, let me share my screen, if that’s okay.

Kristina Harris Jackson: Yeah.

Bill Harris: Um, and we’ll just pull up the paper. And, uh, if, s- s- just point out here that it’s published here in, in Nature Communications, which is one of the, uh, N- Nature family of journals. This is a open access, uh, uh, paper from Nature, meaning it’s, uh, it’s open to anybody. We can share it with anyone. And you can see, uh, as you mentioned, there are a lot of different authors. Nathan and I are the first two, because we kind of led the study. But, uh, all these other individuals are, are either PIs or, or the, the directors of a given cohort. Again, there are 17 studies here. Um, or there are the analysts, the bio statistical analysts who did the work. Uh, so there’s a lot of folks involved with these studies. Uh, there’s a lot of eyes looking at this data to make sure it makes sense.

Bill Harris: Um, if we go to the kind of quick look, uh, th- these are the cohorts. Each one of course has got an acronym, um, but you can see they’re from S- uh, 10 different countries without counting them here. Um, follow-up years of average, you know, something like 17 or 16 years on average of follow-up from between when the blood sample was taken and when they followed up to, to see who had died and who hadn’t is what it amounts to.

Bill Harris: Um, people generally in their 60s, uh, on average. Uh, typically, typically 50/50 each, male, female. Um, and then over here in the far-right corner is the lipid fraction in which the fatty acids were measured. And this is one of the challenges of fatty acid research, particularly epidemiology, is that different cohorts choose to measure fatty acid status in different parts of the blood. Because you can measure it in whole blood, you can measure it in red cells, you can measure it in plasma phospholipids, who plasma, et cetera.

Bill Harris: So the way that the FORCE Coalition gets around this problem of mixed exposures is they say, “Well, we don’t care what fraction of the blood you measure your omega-3 levels in. We’re just gonna look, we’re gonna, everybody’s just gonna divide their levels into quintiles, just in, in 20, you know, 20%, 20%, 20%, 20. And we’re gonna compare the highest and the lowest 20%, the, the extreme quintiles.”

Bill Harris: And we know from other studies that the omega-3 fatty acids particularly and, and uniquely, um, correlate very well regardless of which lipid pool you measure them in. So if it’s the high, if it’s high in red cells, it’s gonna be high in plasma, it’s gonna be high in plasma phospholipids. So our approach is to say, “We’re not gonna worry about the exact number, uh, the, the actual percent of EPA and BHA in red cells, for example. We’re just gonna look at the distribution within each of these cohorts of, of these, uh, by quintile.” And then we did our whole analysis by quintile.

Bill Harris: Um, so that’s the approach we took. Um, this I think is probably the most important figure in the report. And this is looking at, uh, hazard ratios, meaning risk for death between the, essentially the 10th percentile and the 90th percentile. So the 90th percentile, of course, is the highest omega-3 levels, 10th percentile is the lowest. So we’re looking at just at that spread, and so asking, “Is there a difference in risk for death, um, related to that difference in, uh, omega-3 levels in, in, uh, between 10th and 90th in each of these cohorts?”

Bill Harris: And, and this is broken down by lipid pool. The, so, these, these top, uh, half of … These, these studies on top all measured, uh, the omega-3s and phospholipids, whether it’s red cell or plasma. And as you can see over here, we’re looking again at the, the relative risk reduction in the 90th versus the 10th. So if the dot is on the left side of this line, it means there’s a reduced risk, lower risk for death in the people in the 90th percentile compared to the 10th.

Bill Harris: And interestingly, every one of these, even though they may not be statistically significant because the confidence bar, uh, runs, confidence interval crosses one, this is the beauty of meta-analysis, every one of them, is, the point estimate is below one, meaning there’s a significant ri- risk reduction.

Bill Harris: We then look at a couple studies that reported cholesterol esters, and the summary average, uh, here, one was right on the, on no effect and one was at big effect. Uh, some forced, four different cohorts use whole plasma, and again, the trend is certainly to the left. Uh, but when if you take, if you average all of these together, top quintile, the bottom quintile, you get to the bottom, this is the most important dot in the whole paper right there, and that is a overall hazard ratio of .87, meaning a 13% reduction risk for death in people in the 90% versus the 10% over that 16 years of follow-up. Of course, you, if you follow people long enough, everybody dies and their risk for death is 100%, you know, so we can’t do that.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: You have to look at a window of time. Uh, and so this is roughly between age 60 and mid-70s. Uh, that’s the window of time when people who, we’re looking at death. So that is the, I think, primary take-home message. Um, Nathan, you want to add anything to that?

Dr. Nathan Tintle: No. I, I think you made a good point. I’ll clarify one thing, you know, the beauty of this is, because you said, you know, it’s kind of an average across all those cohorts, it’s a weighted average across the cohorts. So it does allow, you know, certain cohorts that have more data, um, to sort of add a little bit more, um, you know, weight, uh, to the analysis.

Dr. Nathan Tintle: But part of what we also do then is look to make sure that there’s no single cohort or single, um, you know, for example, in this case, compartment, um, uh, that is driving, uh, the findings. And in this case, we’re able to say that these findings were robust, um, across those different, uh, considerations.

Bill Harris: Great. Yeah, and let me … the last thing I wanna, just wanna show here is this, uh, Table Two, which is, um, we, we not only focused on total mortality, so dead from any cause. We wanted to look, uh, at least roughly at the major bins of why people die. And, and typically it’s cardiovascular disease, CVD, cancer or everything else. So we, we split this up into these three subgroups, or we call, uh, cause specific, uh, uh, reasons for dying. And I, here we’re looking at each of the omega-3 fatty acids individually in the, uh, in the blood. And again, the 10th percentile versus 90th percentile versus 10th percentile, uh, the bottom one is EPA plus DHA, our favorite metric is what, that’s what we use, we call the Omega-3 Index, uh.

Bill Harris: And here is the, we look here at all cause mortality, .87 means a, uh, same pi- same thing we saw in the figure below. That’s a 13% reduction in risk for death, highest to the lowest. Um, but if we look in cardiovascular disease, and, uh, just to back up, most people think about omega-3s and heart disease, that that’s where their benefit is. And it’s a little bit fuzzy outside of heart disease, what, do, do they really have a role to play anywhere else.

Bill Harris: Well, this is an important finding here, because our risk, r- relative risk for death from heart disease, uh, was .85. That’s a 15% lower risk of death, highest versus lowest for heart disease. But if you look at cancer mortality, here we have a statistically significant 11% reduction in risk for death from cancer when people had the high omega-3. And then you go over to other mortality, which is everything, all, the entire kitchen sink, if everything else people die from. And we have a significant 12% reduction. So it’s about the same risk reduction regardless of cause of death. It kind of crosses the entire spectrum of, of, what you might call, non-health. Being dead is not being healthy.

Kristina Harris Jackson: (laughs)

Bill Harris: Um, so this is, I think, an important finding that the omega-3s predict risk for death regardless of the outcome, of, of the cause of death.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: So I’ll shut up and let you-

Kristina Harris Jackson: (laughs) Well, I guess back to kind of comparing to other meta-analysis, sometimes on omega-3s there seems like there’s tons of them, and sometimes they find no effect and sometimes they find an effect and sometime they’re talking about omega-3s from a dietary intake study. Sometimes they’re talking about … I mean, they’re, they’re pretty rarely talking about blood levels. Is that right? Is this one of the biggest, or one of the few that-

Bill Harris: That’s true.

Kristina Harris Jackson: blood levels to meta-analysis-

Bill Harris: Right.

Kristina Harris Jackson: And how is that better or worse than, uh, the dietary intake meta-analysis?

Bill Harris: Yeah, there’s many more dietary intake-based. And of course, uh, dietary intake is based on somebody writing down or reporting a guess as to how much of what kind of food they ate over the last week, month, year, um, and then linking that guess with a approximate amount of omega-3 in a certain kind of food. I mean, it’s a, it’s a very rough, uh, way to actually get, what we call, the exposure, you know, what, what are you being exposed to. You’re, we’re being exposed to omega-3. You can estimate it by these dietary questionnaires. They’re cheap and easy to do relative to actually a laboratory test, but the information is a lot, much more sloppy and less, necessarily, trustworthy.

Bill Harris: Um, what we did here is we, we certainly ranked it up to the next level and we said, “We’re gonna look at blood levels,” which is tissue levels essentially. Uh, and that’s an objective marker of your intake. And that is a, a much more trustworthy way of deciding or, or, or seeing the relationship between the omega-3 and the disease outcome than it, a diet questionnaire.

Kristina Harris Jackson: And sometimes people will take randomized control trials and put those together too. And these are all perspective cohort studies, large observational studies over time, so that-

Bill Harris: Yeah, yeah. Nathan, you wanna talk about the difference between those two study designs and-

Dr. Nathan Tintle: Yeah, sure. So, um, in these perspective cohort studies, um, they’re not being, people aren’t actively being, um, intervened with. So they’re not being told to change their behavior in some way. And so typically, um, you try to get a large group of people often representative of some population, and so, you know, the cohorts here, as Dr. Harris said, you know, representative of different countries or different parts of countries. And then you follow them forward for a long period of time.

Dr. Nathan Tintle: Um, compared to a randomized controlled trial, which often takes place over a much shorter time interval, um, not always but often that’ll be a much shorter time interval just because of logistics, because you’re intervening with people. And, and you have to make sure that they’re compliant with whatever your intervention is. So in an RCT based on omega-3, often then people would be given a supplement for a shorter period of time and then follow it.

Dr. Nathan Tintle: So I think one of the powerful aspects of this is, as Dr. Harris said, you know, we follow people for 16 years, um, and use this, uh, independent measure of, um, health, uh, being the omega-3, uh, levels in the blood. Um, and so I think those add some additional benefits over the randomized control trials in this case.

Kristina Harris Jackson: Yeah.

Bill Harris: But, but to be clear, one of the weaknesses, uh, the criticism of, of the observational study, like we do, is we measure their blood, omega-3 levels when they’re 60.

Dr. Nathan Tintle: Yeah.

Bill Harris: And then we assume that it’s gonna be the same over the next 16 years and we don’t measure. We can’t measure it.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: Uh, so that’s a, uh, an assumption that underlies the observational stuff. And that’s, you know, it’s fair. It, it, nothing’s perfect. There is no perfect study designs. So you have to look at the strengths of both of these randomized trials and observational, uh, biomarker-based epidemiology.

Kristina Harris Jackson:

Yeah. Um, we have seen some interesting things with the omega-6s in some of these FORCE papers. Did you guys look at the main omega-6s, linoleic, arachidonic acid in this paper? Or is that something coming up?

Bill Harris: We did not. We adjusted for them in the e- … Everybody, like Nathan said, everybody would read ahead time, “What is gonna, what’s the, uh, co-variants?” And the two co-variants that relative to that are omega-6, linoleic acid and arachidonic acid, in the blood.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: So these findings are the relationships between omega-3 and death outcomes, independent of any effect of omega-6.

Kristina Harris Jackson: Okay.

Bill Harris: Um, I don’t think any, we’re even talking about it, Nathan, doing an omega-6 focused trial?

Dr. Nathan Tintle: Yeah. I don’t think that’s come up yet. I mean, it’s true, you’re, you’re right Kristine. It, a lot times, FORCE had done both, some omega-6 things (laughs) and some omega-3 things. Um, just to follow-up on your point about adjusting for omega-6, and so, and back to our previous conversation just a few minutes ago about randomized control trials versus observational studies.

Dr. Nathan Tintle: So one of the ways that observational studies like this one try to get close to a randomized control trial is by statistically adjusting for these other factors. And so really the power of a randomized control trial is you say, “Okay, we’re able to say this intervention causes or doesn’t cause this change.” We can get closer to that in an analysis like this by controlling for age and sex and BMI and part of the country and lipid compartment, and as we just talked about, omega-6s, but we can’t rule out all of those other possible things. And so-

Bill Harris: Yeah.

Dr. Nathan Tintle: um, I think the power of FORCE is you get, you know, 30, 40, 50 experts in the field from all these different cohorts getting their heads together to say what really might matter or what really might impact this. And let’s account for that in our analysis so when we’re done, we feel really good about this finding probably, you know, holding up, um, against other people’s potential, “What if it was X?”. Um, we, we, we’ve accounted for a lot of those what if questions.

Bill Harris: Can you, can you quickly summarize some of the other things we accounted for in our analysis? I think we had using, uh, having high cholesterol, having high blood pressure, having diabetes, smoking, right?

Dr. Nathan Tintle: Yep. Um, alcohol consumption, um, a variety of demographics, um, including race and education, occupation, uh, marital status. Um, self-reported general health, um, which, uh, is kind of a catch-all, um, that can actually capture a lot of other variation in people’s health that wouldn’t be better c- categor- or classified by things like diabetes status or alcohol status. Um, I’m looking at the list. I think that covers, covers most of them, yeah.

Bill Harris: Great.

Kristina Harris Jackson: It’s a lot. Um, I guess my last question is, um, kind of focused on one of the compartments, the RBC, omega-3, [inaudible], Omega-3 Index. What are the levels that the 10th and the 90th percentile represented for, um, RBC phospholipids?


Bill Harris: Uh, the, yeah, we calculated that, um, and put it in the, um, supplementary material here.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: But roughly the, if, if you just look at the, the phospholipid category, the t- overall average of the 10th percentile was about 3.4% EPA plus DHA, which fits conveniently with our original proposal 17 years ago that under four percent was high-risk. And the upper end was, like, about 7.7%, uh, EPA/DHA, which is pretty close to the eight percent that we proposed, again, originally, uh-

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: 17 years ago when we set up the omega-3. So this is pretty strong confirmation that those numbers are generally, uh, reliable, I think.

Kristina Harris Jackson: Yeah. I, I think that’s, that’s really nice to be able to have some context. I think that’s some of the good part about, um, us being able to use Omega-3 Index and, um, have that as something that you can have, uh, have an idea of what ome- high omega-3 levels means, um, because there’s so many different ways to measure it. It’s not a standardized measure. So it’s good-

Bill Harris: Right.

Kristina Harris Jackson: to get a handle on this isn’t between people who are at three percent and five percent. This is-

Bill Harris: No.

Kristina Harris Jackson: about four and eight.

Bill Harris: No. And, but correct, that’s the 10th and 90th percentile. So that’s a-

Kristina Harris Jackson: That’s a big spread.

Bill Harris: We’re talking only 10% of the people in this cohort had a level that’s, you know, seven, s- seven or eight or nine percent.

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: Just … And if it was just the US, it would only be two or three percent, but this is worldwide. So-

Kristina Harris Jackson: Right.

Bill Harris: so we have some Japanese and some Icelandic people. And, um, you know-

Kristina Harris Jackson: Mm-hmm (affirmative). Yeah. [crosstalk] It looks like, um, are you guys able or trying to recruit more types of cohorts that are from more, like, different parts of the world? It looks like Asia, North America and Europe are pretty well, and Australia, are pretty well represented. Are there other cohorts that you’re trying to get after in other parts of the world?

Bill Harris: Well, I don’t, I don’t think we, Nathan, correct me if I’m wrong, but I don’t think we’ve made any, any intentional effort to say, you know, “We haven’t got anybody from Argentina here.”

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: “We, we really need an Argentinian.” And we go digging around the literature to see if anybody’s done a cohort study and if they’ve measured fatty acids. Um, this is a little bit more catch as catch can, and run into cohorts occasionally and say, “Oh … ” We just, we added one in China-

Kristina Harris Jackson: Mm-hmm (affirmative).

Bill Harris: that we didn’t know about. Um-

Kristina Harris Jackson: Yeah.

Bill Harris: And so-

Kristina Harris Jackson: Start the ability to start, um-

Bill Harris: Yeah.

Kristina Harris Jackson: getting-

Bill Harris: India would be a great one to add if there were something.

Kristina Harris Jackson: Yeah, yeah.

Bill Harris: Almost largest country in the world now population there, just about.

Kristina Harris Jackson: Crazy. All right. Well, this is a really cool paper. I understand it took about two years to get it from conception to-

Bill Harris: Conception to, to birth (laughs). Yeah.

Kristina Harris Jackson: It was-

Bill Harris: A long gestation, yeah.

Kristina Harris Jackson: a long time, but not out of the question for s- (laughs) a paper, especially with that many authors and trying to get it done. So congratulations-

Bill Harris: Thank you. Thank you.


Kristina Harris Jackson: And thanks for talking about it with us.

Bill Harris: You bet. Good talking to you.

Kristina Harris Jackson: Okay.

Dr. Nathan Tintle: Thank you.

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