podcast Peter Attia 2022-02-28 topics

#197 - The science of obesity & how to improve nutritional epidemiology | David Allison, Ph.D.

(Oct 17, 2021) Ten errors in randomized experiments (Feb 26, 2022) Nutritional epidemiology: abolition vs defending the status quo (Feb 28, 2022) The science of obesity & how to improve nutritional epidemiology David Allison is an award-winning scientific writer who has been at t

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Show notes

(Oct 17, 2021) Ten errors in randomized experiments
(Feb 26, 2022) Nutritional epidemiology: abolition vs defending the status quo
(Feb 28, 2022) The science of obesity & how to improve nutritional epidemiology

David Allison is an award-winning scientific writer who has been at the forefront of obesity research for the last 20 years. Currently the Dean of the Indiana University School of Public Health, he has also authored many publications on statistical and research methodology and how to improve research rigor and integrity. David’s focus on evidence and data brings forth an interesting discussion of what we know (and don’t know) about the science of obesity. He provides an insightful and unemotional explanation of the potential impact of nutritional epidemiology in public health while also explaining its many pitfalls and limitations. He offers his take on the path forward in addressing the obesity epidemic, and he closes with a lucid explanation for the evident lack of credibility in science and the steps we can take to change that.

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We discuss:

David’s background, interest in obesity, and focus on evidence [5:00];
The moment when the obesity crisis was recognized, and the sloppy science that ensued [13:00];
What twins studies tell us about the genetics of obesity [20:30];
How doctors and scientists have historically approached obesity treatment [23:45];
Do surgical procedures for obesity prolong life? [32:00];
The ‘Obesity Paradox’ [36:00];
Interpreting BMI and mortality data and considering confounders [43:15];
How body composition and ethnicity factor into consideration of BMI data [50:30];
Superior tools for measuring obesity at the individual level [57:15];
Using BMI data for actionable steps to combat obesity [1:02:00];
Why maintaining weight loss is more challenging than losing weight [1:06:00];
Differing perspectives on the utility of nutritional epidemiology [1:16:30];
A mouse study illustrating the impossibility of fully controlling for confounds in observational studies [1:22:15];
Limitations of nutritional epidemiology and how it can improve [1:26:30];
Addressing the obesity epidemic—the path forward and obstacles to overcome [1:37:15];
What David believes to be the most promising interventions we could take to address obesity and improve public health [1:47:30];
Reproducibility in science, normative and non-normative errors explained [1:51:30];
Rebuilding trust in science and differentiating between science and advocacy [1:59:00];
More.

Show Notes

*Notes from intro:

David Allison received his PhD from Hofstra University in 1990
He went on to complete his post-doctoral fellowship at the Johns Hopkins University School of Medicine
And a second post-doctoral fellowship at the New York Obesity Research Center at St. Luke’s Roosevelt Hospital Center
He’s currently the Dean and Provost Professor at the Indiana University Bloomington School of Public Health
Prior to that, he was an endowed professor and a director of an NIH-funded nutrition organization research center at the University of Alabama in Birmingham
He’s authored over 500 scientific publications and received many awards, including: The 2002 Lilly Scientific Achievement Award from the Obesity Society The 2002 Andre Mayor Award from the International Association for the Study of Obesity The National Science Foundation Administered 2006 Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring
In 2012, he was elected to the National Academy of Medicine and the National Academies
He serves on or has served on many of the editorial boards and currently serves on: As an Associate Editor or Statistical Editor for The International Journal of Obesity Nutrition Today , Obesity Reviews , Public Library of Science (PLOS Genetics) , Surgery for Obesity and Related Diseases , and The American Journal of Clinical Nutrition He is also the founding Field Chief Editor of Frontiers in Genetics
David’s research interests include obesity and nutrition, quantitative genetics, clinical trials, statistical and research methodology, and research rigor and integrity
Peter has known David Allison for probably about 7-8 years now
He has always found him to be one of the most insightful and thoughtful people on virtually any topic
In this episode we talk about obesity We spend a lot of time getting into what is known and what is not known about obesity and also the science of obesity In particular we focus on the science of nutrition and nutritional epidemiology We talk about all these pitfalls, which for many of my listeners, will be familiar
David brings a very unemotional and a very insightful, logical, and thoughtful approach to how he thinks about the pitfalls in this field
There are parts of this discussion that are actually quite frustrating in the sense that David acknowledges that most of the measures that we have in place from a public health perspective are probably not founded in any scientific basis
We then talk a little bit about the reproducibility of science and we close with a very clear elucidation of the challenges that science seems to be facing This kind of existential threat where science and scientists are often confounded Where science and advocacy is often confounded There seems to be a bit of a crisis around this David offers his thoughts on that and whether or not there is a crisis or not For Peter, this is one of the most interesting parts of the discussion, and it’s something that he’s been trying to wrap his head around for some time without much success That is the seeming lack of credibility that science has today David is quick to point out that it’s probably not science that is being doubted Certainly the scientific method is not in doubt, as it is a means by which knowledge can be reliably and reproducibly gained But rather it might be the confounding of science and advocacy Peter would encourage you to listen all the way through, even if at the outset, you find the topic of obesity not particularly to your interest to hear what David has to say on this topic
The 2002 Lilly Scientific Achievement Award from the Obesity Society
The 2002 Andre Mayor Award from the International Association for the Study of Obesity
The National Science Foundation Administered 2006 Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring
As an Associate Editor or Statistical Editor for The International Journal of Obesity
Nutrition Today , Obesity Reviews , Public Library of Science (PLOS Genetics) , Surgery for Obesity and Related Diseases , and The American Journal of Clinical Nutrition
He is also the founding Field Chief Editor of Frontiers in Genetics
We spend a lot of time getting into what is known and what is not known about obesity and also the science of obesity
In particular we focus on the science of nutrition and nutritional epidemiology
We talk about all these pitfalls, which for many of my listeners, will be familiar
This kind of existential threat where science and scientists are often confounded
Where science and advocacy is often confounded
There seems to be a bit of a crisis around this
David offers his thoughts on that and whether or not there is a crisis or not
For Peter, this is one of the most interesting parts of the discussion, and it’s something that he’s been trying to wrap his head around for some time without much success That is the seeming lack of credibility that science has today
David is quick to point out that it’s probably not science that is being doubted Certainly the scientific method is not in doubt, as it is a means by which knowledge can be reliably and reproducibly gained But rather it might be the confounding of science and advocacy
Peter would encourage you to listen all the way through, even if at the outset, you find the topic of obesity not particularly to your interest to hear what David has to say on this topic
That is the seeming lack of credibility that science has today
Certainly the scientific method is not in doubt, as it is a means by which knowledge can be reliably and reproducibly gained
But rather it might be the confounding of science and advocacy

David’s background, interest in obesity, and focus on evidence [5:00]

Even as an undergraduate David was focused on evidence, data

Peter admires the intellectual approach David has to obesity research, his lack of emotional thinking
For many people, the field of obesity is a loaded field, scientifically and politically
David doesn’t really know why he turned out the way he did To quote his friend Don Ruben , “ we may be able to figure out what the causal effect of X is, but we may not be able to assess whether X cause Y ”
When David went to college he wanted to be a psychologist What this meant to him at the time was Hitchcock films He was going to interpret people’s dreams and figure out the meaning
When he got to college he started to think about the evidence for these things That opened up this whole can of worms
He became more and more cognitive behaviorally-oriented
He remembers in graduate school the professor explaining IQ tests and different theories of intelligence The professor noted that some people think there is 1 factor in intelligence, some people think 3 and one person thinks its 144 David asked who was right The professor said, “ Well, they bring their different evidence to bear, and they argue ” David asked about the evidence The professor replied “ these factor analyses…you have to go study multivariate statistics if you want understand that ”
To quote his friend Don Ruben , “ we may be able to figure out what the causal effect of X is, but we may not be able to assess whether X cause Y ”
What this meant to him at the time was Hitchcock films
He was going to interpret people’s dreams and figure out the meaning
That opened up this whole can of worms
The professor noted that some people think there is 1 factor in intelligence, some people think 3 and one person thinks its 144
David asked who was right
The professor said, “ Well, they bring their different evidence to bear, and they argue ”
David asked about the evidence
The professor replied “ these factor analyses…you have to go study multivariate statistics if you want understand that ”

“S o I don’t like to take anybody’s word for anything ” – David Allison

So David went and studied multi-varied statistics
He became more and more involved with statistical analysis to the point where eventually people started thinking he was a statistician
He sort of became, by evolution, a statistician, having been trained as a psychologist
He thinks all of that comes down to evidence Body fat is no different than any other variable
People are another variable; they still have to obey the same laws of probability and physics and mathematics and so on that we apply to anything else People talk and so folks who study people think about the words that people say, whereas if you’re studying atoms and molecules, you don’t think about the words they say, you just apply scientific methods For example the same person who would never question a diabetol ogist on what the beta cell of a pancreas is doing, would say to an obesity research, “ Well, this is how obesity works and it’s this aspect of food or that aspect of culture or that aspect of child rearing ” Based only on the fact that they were children or had children and had some experience David takes a step back and says, “ whether it’s pigs today and pigs tomorrow, whether it’s Xs and Ys, they’re just variables and applying the same laws of thinking to all those systems ”
Body fat is no different than any other variable
People talk and so folks who study people think about the words that people say, whereas if you’re studying atoms and molecules, you don’t think about the words they say, you just apply scientific methods
For example the same person who would never question a diabetol ogist on what the beta cell of a pancreas is doing, would say to an obesity research, “ Well, this is how obesity works and it’s this aspect of food or that aspect of culture or that aspect of child rearing ” Based only on the fact that they were children or had children and had some experience
David takes a step back and says, “ whether it’s pigs today and pigs tomorrow, whether it’s Xs and Ys, they’re just variables and applying the same laws of thinking to all those systems ”
Based only on the fact that they were children or had children and had some experience

David’s interest in the field of obesity

As an undergraduate, a sophomore at Vassar College in New York, he took a class on human emotion and motivation.
He studied the theories of Stanley Schacter , who at the time was a professor of psychology at Columbia University; he is since deceased
Stanley was an amazing, brilliant man who wrote a book called Emotion, Obesity, and Crime He talked about the connection among these and how the distinction between our cognitive state and our physiologic arousal state might lead us to certain kinds of behaviors, including in the case of some people, eating more calories than they might otherwise eat
His experiments were so creative; David just loved it He would put a clock on the wall and he would have the clock move a little faster, but not perceptively faster Then he would bring some students in and give them some work to do under some ruse Then the clock would say for some of the students at 11:00 AM, that it was noon, and he’d say, “ By the way, I have a big tray of roast beef sandwiches out here. So whenever you’re hungry for lunch, just let me know and you can have some sandwiches .” For some people, the clock wouldn’t say it was noon until 1:00 PM And for some people, it would say it was noon at noon He’d say, “ Who would be following the clock and who would be following the actual time? ” Obese or overweight persons were more likely to follow the clock; this became the external theory This didn’t always work out; another experiment would show that it only holds up under this circumstance
He had to write lots and lots of papers at Vassar College He got a great education in writing and thinking there There were not so many tests but lots of papers When he took physiologic psychology, he would write about the physiologic psychology of obesity When he took behavioral psych, he wrote about the behavioral obesity When he took developmental, he wrote about the developmental aspects of obesity He loved being able to look at obesity from so many different angles No one researcher does this; everybody’s got their pet thing— this nutrient is toxic, the problem is food marking practices, the problem is cultural, it’s exercise There are so many factors involved and he enjoyed studying it from many angles (and he still does)
He finished his PhD in the mid to late ‘80’s
Obesity rates then were not as high as they are now There have been steady increases
He talked about the connection among these and how the distinction between our cognitive state and our physiologic arousal state might lead us to certain kinds of behaviors, including in the case of some people, eating more calories than they might otherwise eat
He would put a clock on the wall and he would have the clock move a little faster, but not perceptively faster Then he would bring some students in and give them some work to do under some ruse Then the clock would say for some of the students at 11:00 AM, that it was noon, and he’d say, “ By the way, I have a big tray of roast beef sandwiches out here. So whenever you’re hungry for lunch, just let me know and you can have some sandwiches .” For some people, the clock wouldn’t say it was noon until 1:00 PM And for some people, it would say it was noon at noon He’d say, “ Who would be following the clock and who would be following the actual time? ”
Obese or overweight persons were more likely to follow the clock; this became the external theory
This didn’t always work out; another experiment would show that it only holds up under this circumstance
Then he would bring some students in and give them some work to do under some ruse
Then the clock would say for some of the students at 11:00 AM, that it was noon, and he’d say, “ By the way, I have a big tray of roast beef sandwiches out here. So whenever you’re hungry for lunch, just let me know and you can have some sandwiches .”
For some people, the clock wouldn’t say it was noon until 1:00 PM
And for some people, it would say it was noon at noon
He’d say, “ Who would be following the clock and who would be following the actual time? ”
He got a great education in writing and thinking there
There were not so many tests but lots of papers
When he took physiologic psychology, he would write about the physiologic psychology of obesity
When he took behavioral psych, he wrote about the behavioral obesity
When he took developmental, he wrote about the developmental aspects of obesity
He loved being able to look at obesity from so many different angles No one researcher does this; everybody’s got their pet thing— this nutrient is toxic, the problem is food marking practices, the problem is cultural, it’s exercise There are so many factors involved and he enjoyed studying it from many angles (and he still does)
No one researcher does this; everybody’s got their pet thing— this nutrient is toxic, the problem is food marking practices, the problem is cultural, it’s exercise
There are so many factors involved and he enjoyed studying it from many angles (and he still does)
There have been steady increases

The moment when the obesity crisis was recognized, and the sloppy science that ensued [13:00]

Looking at the data from the 1700s forward, there have been relatively steady increases in obesity rates in westernized industrialized countries since then
A wake-up moment occurred in the early ‘90’s with the NHANES III study This is the National Health and Nutrition Examination Survey It’s an annual study performed today, a survey of a representative sample of Americans with measured heights and weights This is how obesity levels are tracked In the early ‘90’s it was only done every few years Prior to this obesity was an issue, but it wasn’t on top of everyone minds, especially for kids
Pharmaceuticals were still seen as the realm of charlatans at that point
Doc’s that proposed the use of obesity medications were called diet docs, and that was a very bad stigma
There weren’t many good medications available
Surgery was still looked at as a very peculiar thing for very extreme cases, and many medical professionals disdained it
In the early ‘90’s when the NHANES III data came out, it showed this big jump in obesity levels This got everyone’s attention Words like epidemic started to be used, especially for childhood obesity
The public health policy and environmental perspective started to shift in the mid-90’s
People like Kelly Brownell suddenly started to say, “ Maybe we’ve got it wrong. Maybe it’s this environment .” He was probably one of the most forceful voices at the time He was a colleague of Tom Wadden (University of Pennsylvania) And a student of Mickey Stunkard of the cognitive behavioral individual clinical treatment approach to obesity He popularized the term “toxic environment”
It was at this point that people began to think about prevention and children and the overall environment, the political, economic, social, food marketing environment we live in
The same public health people who had battled cigarette companies and tobacco for decades, came with their tools and said, “ We know how to deal with things that are environmental, social, political problems ”
It began to be seen as an environmental, social, political problem
In some ways, a lot was gained, because obesity research got a lot more funding, more attention, more efforts, more research But in some ways a lot was lost
This is the National Health and Nutrition Examination Survey
It’s an annual study performed today, a survey of a representative sample of Americans with measured heights and weights
This is how obesity levels are tracked
In the early ‘90’s it was only done every few years
Prior to this obesity was an issue, but it wasn’t on top of everyone minds, especially for kids
This got everyone’s attention
Words like epidemic started to be used, especially for childhood obesity
He was probably one of the most forceful voices at the time
He was a colleague of Tom Wadden (University of Pennsylvania)
And a student of Mickey Stunkard of the cognitive behavioral individual clinical treatment approach to obesity
He popularized the term “toxic environment”
But in some ways a lot was lost

As interest in obesity research grew, the science became sloppy

David grew up in the field in the early-90’s in the first federally-funded obesity research center, which is the New York Obesity Research Center
As a young postdoc, if he were to say something that didn’t quite jive with physiology or genetics or anatomy or clinical medicine, there was a physiologist and a geneticist and an atomist and a medical doctor with whom he could consult They all knew each other, they knew the arguments, they knew the literature for the last 20 years
Then the public health people came in fresh without kind of knowing so much It was great to have more interest in obesity But it brought about a dilution of the rigor of the field intellectually It became a lot more of opinion, a lot more of advocacy In the absence of rigorous evidence showing what worked, people are saying, “ This seems like it ought to work ”
They all knew each other, they knew the arguments, they knew the literature for the last 20 years
It was great to have more interest in obesity
But it brought about a dilution of the rigor of the field intellectually It became a lot more of opinion, a lot more of advocacy In the absence of rigorous evidence showing what worked, people are saying, “ This seems like it ought to work ”
It became a lot more of opinion, a lot more of advocacy
In the absence of rigorous evidence showing what worked, people are saying, “ This seems like it ought to work ”

Peter asks what scientists believed to be the “cause” of obesity (prior to the NHANES III study) [17:15]

There wasn’t a single cause
What some people today call the energy balance model was accepted as valid Maybe not as a model but as a description of what occurs Peter notes, this sort of tautology doesn’t really tell us anything; it’s implied and obvious but not explanatory David agrees that “ not explanatory is maybe the best way of describing it ” He likes the term energy balance “ statement” because it doesn’t imply causality
Maybe not as a model but as a description of what occurs
Peter notes, this sort of tautology doesn’t really tell us anything; it’s implied and obvious but not explanatory
David agrees that “ not explanatory is maybe the best way of describing it ”
He likes the term energy balance “ statement” because it doesn’t imply causality

Peter asks if prior to NHANES III the belief was that obese people ate more calories than they were expending by choice (i.e., it was behavioral)?

David notes this is a hard question to answer because people’s thinking was so sloppy and they didn’t distinguish among things well This is still true today People talk about the influence of biology versus behavior as though there can be behavior without biology
But if you really drill down, smart people understood there is a genetic component to obesity Any rancher could have told you a hundred or more years ago that there’s a genetic component We can selectively breed animals for being thinner or fatter It’s prima facie evidence
This is still true today
People talk about the influence of biology versus behavior as though there can be behavior without biology
Any rancher could have told you a hundred or more years ago that there’s a genetic component
We can selectively breed animals for being thinner or fatter
It’s prima facie evidence

What twin studies tell us about the genetics of obesity [20:30]

Peter asks, what is the concordance of obesity in identical twins separated at birth?

For monozygotic (or identical twins) separated at or nearly after birth, it’s nearly the same magnitude as it is for twins reared together, which is around 0.8 He misspoke in the podcast when he said the concordance is 0.9 and asked us to correct this number to 0.8 Published in the International Journal of Obesity and Related Metabolic Disorders in 1996, The heritability of body mass index among an international sample of monozygotic twins reared apart Of course you can argue, well, that also takes into account the intrauterine environment, maybe some epigenetic things, but bottom line is whatever those things are, they’re not just child rearing of the home Rearing of the home does have an influence, but it’s not huge Peter notes, this is “ an incredible degree of concordance”
Peter asks when this degree of concordance was realized; when were these studies done?
There were many hints for quite some period of time Lots of people observed this in ranching data, mouse data, and family data
But there was this moment where a key figure came in to both see it and say it with a degree of crispness that wasn’t there before
In 1923, Davenport published under the Carnegie Foundation, these studies of concordance of families; his 1923 data showed this genetic component He is probably looked at now as a racist from the past
But it was Albert J. (Mickey) Stunkard who did the first major high quality twin and adoption studies David knew Mickey; he was a wonderful man He got Torkel Sorenson and other people to start working on twin studies with the great Nordic data, Sweden, Denmark, and so on, and adoption studies It was the twin and adoption studies coming out of Sweden and Denmark that really nailed it Finally in The New England Journal of Medicine with Mickey Stunkard behind it with clear writing, with high quality data, people said, “ We got it. There’s a big genetic component. ” Published in 1986, An Adoption Study of Human Obesity Published in 1990, The Body-Mass Index of Twins Who Have Been Reared Apart
He misspoke in the podcast when he said the concordance is 0.9 and asked us to correct this number to 0.8
Published in the International Journal of Obesity and Related Metabolic Disorders in 1996, The heritability of body mass index among an international sample of monozygotic twins reared apart
Of course you can argue, well, that also takes into account the intrauterine environment, maybe some epigenetic things, but bottom line is whatever those things are, they’re not just child rearing of the home
Rearing of the home does have an influence, but it’s not huge
Peter notes, this is “ an incredible degree of concordance”
Lots of people observed this in ranching data, mouse data, and family data
He is probably looked at now as a racist from the past
David knew Mickey; he was a wonderful man
He got Torkel Sorenson and other people to start working on twin studies with the great Nordic data, Sweden, Denmark, and so on, and adoption studies
It was the twin and adoption studies coming out of Sweden and Denmark that really nailed it
Finally in The New England Journal of Medicine with Mickey Stunkard behind it with clear writing, with high quality data, people said, “ We got it. There’s a big genetic component. ” Published in 1986, An Adoption Study of Human Obesity Published in 1990, The Body-Mass Index of Twins Who Have Been Reared Apart
Published in 1986, An Adoption Study of Human Obesity
Published in 1990, The Body-Mass Index of Twins Who Have Been Reared Apart

How doctors and scientists have historically approached obesity treatment [23:45]

Peter notes when genetics play a role in disease, pharmacologic therapy makes sense For example, if somebody is genetically predisposed to hypothyroidism, a doctor wouldn’t think twice about replacing thyroid hormone as necessary The endocrine system is relatively straightforward to understand
Why was there this disconnect in the early ‘80’s when it was understood that genetics plays a role in obesity but medical tools were not being used What was being done? Were people simply counseled to eat less and exercise more?
For example, if somebody is genetically predisposed to hypothyroidism, a doctor wouldn’t think twice about replacing thyroid hormone as necessary The endocrine system is relatively straightforward to understand
The endocrine system is relatively straightforward to understand
What was being done? Were people simply counseled to eat less and exercise more?

A focus on reducing energy intake

Most of the focus was on developing tools to help people reduce energy intake This is still the case today Surgery and drugs mostly help people reduce calorie intake
This is still the case today
Surgery and drugs mostly help people reduce calorie intake

“ We know that reducing energy intake works. It’s just really hard to do, and telling people to do it and saying, ‘I’ll try to do it,’ is not all that effective .” – David Allison

Behavioral therapy began to be used in the ‘60’s Stewart began thinking about using behavioral therapy to treat obesity It has continued to get better and better since then
David’s sense is that we have been asymptoting for a long time We’re getting incrementally better but not meaningfully better with many of the behavioral/cognitive things
Stewart began thinking about using behavioral therapy to treat obesity
It has continued to get better and better since then
We’re getting incrementally better but not meaningfully better with many of the behavioral/cognitive things

Early pharmaceuticals

In the early 90’s he was a postdoc at the New York Obesity Research Center At this time a few people started using pharmaceuticals to treat obesity Fen-phen is a drug that came up and caught people’s attention We now know it’s dangerous and it’s gone
Fen-phen is a nickname for two drugs used in combination, phentermine and fenfluramine
Phentermine is a drug that was and still is approved by the FDA for the treatment of obesity Though it’s never been approved for long-term This goes back a long way, it’s a catecholaminergic agonist It’s a relatively safe drug; no drug is perfectly safe It’s modestly effective
Fenfluramine is a selective serotonergic reuptake inhibitor, which originally was used for depression and people realized sometimes those drugs ( SSRIs ) cause weight loss
Somebody realized you could put those two together and it seemed to provide better results So that became a big craze There were many unscrupulous medical providers who did provided it in ways they shouldn’t have But there were many scrupulous medical providers who used it carefully and thoughtfully, and it did seem to have much better benefit than other people had predicted before
So suddenly, pharmaceutical treatment was starting to be credible
People like George Bray , who’s still around today and working on obesity, jumped on board and started to really think through all the cornucopia of pharmaceuticals we knew about and which ones might be useful
Then a very young, smart pathologist at the Mayo Clinic (not an obesity researcher; David doesn’t remember her name) began noticing peculiar valvulopathy on autopsies This was not a common thing What they shared in common was the patients had been on fen-phen This began the investigation into fen-phen
People quickly realized that fen-phen did produce a certain valvulopathy and further investigation made it clear it was the fenfluramine component, not the phentermine component that did that So fenfluramine was withdrawn
Many drugs in the history of obesity hurt people; but what was good about this is prompted people to think more about obesity as a serious medical disorder Obesity began to receive serious attention from credible physicians And incredible scientists began working at the molecular pharmaceutical and physiologic level
Peter asks, “ how much of Fen Phen’s mechanism was understood? ” Was it simply that one component was increasing energy expenditure while the other was reducing appetite?
David doesn’t think with any of these things we ever fully know the components, but it wasn’t that simple
Compare it to statins, which are thought of so highly It’s unclear whether they really have their beneficial effects by reducing LDL cholesterol (which is sort of the initial thought) or through other mechanisms (that are being debated now)
Fen-phen was thought to reduce appetite through 2, slightly different mechanisms, and therefore help people control their food intake better One was serotonergic and the other was more adrenergic Phentermine more than the fenfluramine may have had modest effects on energy expenditure
David doesn’t know the mechanism for the valvulopathy they cause
Fen-phen was pulled in the late ‘90’s, maybe ‘97
At this time a few people started using pharmaceuticals to treat obesity
Fen-phen is a drug that came up and caught people’s attention We now know it’s dangerous and it’s gone
We now know it’s dangerous and it’s gone
Though it’s never been approved for long-term
This goes back a long way, it’s a catecholaminergic agonist
It’s a relatively safe drug; no drug is perfectly safe
It’s modestly effective
So that became a big craze
There were many unscrupulous medical providers who did provided it in ways they shouldn’t have
But there were many scrupulous medical providers who used it carefully and thoughtfully, and it did seem to have much better benefit than other people had predicted before
This was not a common thing
What they shared in common was the patients had been on fen-phen
This began the investigation into fen-phen
So fenfluramine was withdrawn
Obesity began to receive serious attention from credible physicians
And incredible scientists began working at the molecular pharmaceutical and physiologic level
Was it simply that one component was increasing energy expenditure while the other was reducing appetite?
It’s unclear whether they really have their beneficial effects by reducing LDL cholesterol (which is sort of the initial thought) or through other mechanisms (that are being debated now)
One was serotonergic and the other was more adrenergic
Phentermine more than the fenfluramine may have had modest effects on energy expenditure

Surgical options

When did gastric bypass and other surgical approaches begin to be used?

David doesn’t know if there was a singular moment, rather it’s been sort of a steady march
There was 1 key step in the credibility of the surgical approach The Swedish obesity study from Lars Sjostrom in Sweden Published in the New England Journal of Medicine in 2004, Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery
The Swedish obesity study from Lars Sjostrom in Sweden
Published in the New England Journal of Medicine in 2004, Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery

“ Surgery had been around for a while. Interestingly, even among physicians and scientists, it was very controversial and still is .” – David Allison

Some people think surgery is abhorrent, but he thinks you just have to take the data as it is Would the world be better if no one needed surgery, yea; but that’s not the world we live in
Surgery is the most effective life-saving, life-changing treatment we have, and it’s a good one
Many physicians had vitriolic battles on this topic David remembers John Carl (who was a very good surgeon) being chastised by a physician colleague over dinner at a conference The physician told him, “ When you are done with a patient Dr. Carl, they will never eat normally again ” Dr. Carl replied, “ No, when I’m done, they will never eat abnormally again ”
As more and more surgeries were performed, people got better at doing them, mortality rates went down and efficacy went up
Would the world be better if no one needed surgery, yea; but that’s not the world we live in
David remembers John Carl (who was a very good surgeon) being chastised by a physician colleague over dinner at a conference
The physician told him, “ When you are done with a patient Dr. Carl, they will never eat normally again ”
Dr. Carl replied, “ No, when I’m done, they will never eat abnormally again ”

Do surgical procedures for obesity prolong life? [32:00]

Lars Sjostrom asked if these surgeries prolonged life
David remembers Lars telling him about his senior mentor (Pierre Bjorn Thorpe) Pierre Bjorn Thorpe was known for fat cell theories and the apple versus pear idea [body shape] Jean Vogg proposed the idea of apple versus pear in France in the ‘50’s But this idea really took hold in the ‘70’s and ‘80’s Bjorn Thorpe was one of the big people that picked it up Pierre laughed at him and said, “ Lars, everybody knows this. Everybody knows that surgery will cause weight loss and help people live longer. There’s no point in doing this study .” Lars replied, “ You may be right, that it does, but we have to do this study because everybody doesn’t accept and believe that and it hasn’t been shown ”
Pierre Bjorn Thorpe was known for fat cell theories and the apple versus pear idea [body shape] Jean Vogg proposed the idea of apple versus pear in France in the ‘50’s But this idea really took hold in the ‘70’s and ‘80’s Bjorn Thorpe was one of the big people that picked it up
Pierre laughed at him and said, “ Lars, everybody knows this. Everybody knows that surgery will cause weight loss and help people live longer. There’s no point in doing this study .”
Lars replied, “ You may be right, that it does, but we have to do this study because everybody doesn’t accept and believe that and it hasn’t been shown ”
Jean Vogg proposed the idea of apple versus pear in France in the ‘50’s
But this idea really took hold in the ‘70’s and ‘80’s
Bjorn Thorpe was one of the big people that picked it up

“ We know over and over again, you’ve got to do the experiment ” – David Allison

As John Hunter famously said to Edward Jenner , when Jenner says, “ I think ,” (and he’s thinking about the first vaccine), Hunter comes back and says, “ Why think? Do the experiment. Got to do the experiment and show it. ”
Sjostrom didn’t do a pure experiment, not a randomized trial, but it’s a controlled trial The IRB , at the time, didn’t think it was ethical to randomly assign people to either surgery or not So if they were willing to get surgery, Sjostrom would find a closely matched control and give them usual care He showed more than a decade later in the New England Journal of Medicine that surgery reduced the mortality rate Surgery had very powerful effects on obesity It was clearly a life-saving and a beneficially, life-changing treatment This was probably a big jump Since then, many other trials, some randomized, have been done showing positive benefits on many things, including longevity
Peter asks what the risk reduction was in all-cause mortality David doesn’t recall from that study, but looking across studies (as it varies a bit), it’s on the order of a 50% reduction, sometimes a little more
How does this change in patients with and without type 2 diabetes ? David doesn’t know off the top of his head, but he shares the intuition that it is probably more beneficial for people with type 2 diabetes Many factors are involved
One of the surprising things in the Swedish Obesity Study was the effect on hypertension Diabetes really came down and stayed down very well, even if weight came back up a little (which it did, on average) Hypertension came down as well, but did not stay down; it would come back up Why was this? Is it damage to the endothelial elasticity that’s not really repairable, and so you get a short-term effect of negative energy balance that’s not sustained? It goes back to the need to do the experiment You can’t make priority assumptions about the effects of treatments You’ve got to do the experiment and look at the effects of treatments
Peter notes, “ it’s interesting that hypertension would return and yet mortality would still improve ” It’s surprising because of how causally related hypertension is to atherosclerosis This suggests perhaps that the benefits of improved insulin sensitivity preserve and play a greater role in mortality than body weight David notes that hypertension may be an additional role and if it too could be reduced over the long term, there would be an even bigger reduction in mortality
The IRB , at the time, didn’t think it was ethical to randomly assign people to either surgery or not
So if they were willing to get surgery, Sjostrom would find a closely matched control and give them usual care
He showed more than a decade later in the New England Journal of Medicine that surgery reduced the mortality rate Surgery had very powerful effects on obesity It was clearly a life-saving and a beneficially, life-changing treatment This was probably a big jump Since then, many other trials, some randomized, have been done showing positive benefits on many things, including longevity
Surgery had very powerful effects on obesity
It was clearly a life-saving and a beneficially, life-changing treatment
This was probably a big jump
Since then, many other trials, some randomized, have been done showing positive benefits on many things, including longevity
David doesn’t recall from that study, but looking across studies (as it varies a bit), it’s on the order of a 50% reduction, sometimes a little more
David doesn’t know off the top of his head, but he shares the intuition that it is probably more beneficial for people with type 2 diabetes
Many factors are involved
Diabetes really came down and stayed down very well, even if weight came back up a little (which it did, on average)
Hypertension came down as well, but did not stay down; it would come back up Why was this? Is it damage to the endothelial elasticity that’s not really repairable, and so you get a short-term effect of negative energy balance that’s not sustained? It goes back to the need to do the experiment You can’t make priority assumptions about the effects of treatments You’ve got to do the experiment and look at the effects of treatments
Why was this?
Is it damage to the endothelial elasticity that’s not really repairable, and so you get a short-term effect of negative energy balance that’s not sustained? It goes back to the need to do the experiment You can’t make priority assumptions about the effects of treatments You’ve got to do the experiment and look at the effects of treatments
It goes back to the need to do the experiment
You can’t make priority assumptions about the effects of treatments
You’ve got to do the experiment and look at the effects of treatments
It’s surprising because of how causally related hypertension is to atherosclerosis
This suggests perhaps that the benefits of improved insulin sensitivity preserve and play a greater role in mortality than body weight
David notes that hypertension may be an additional role and if it too could be reduced over the long term, there would be an even bigger reduction in mortality

The ‘Obesity Paradox’ [36:00]

When did the idea of the ‘Obesity Paradox’ start to be observed?

That phrase ‘Obesity Paradox’ has never been really crisply defined And whether it really is something that’s a paradox is not clear
People use it to mean at least 2 different things There’s this so-called U-shaped curve, more accurately concave upward, it’s a bathtub shaped curve (see the figure below)
And whether it really is something that’s a paradox is not clear
There’s this so-called U-shaped curve, more accurately concave upward, it’s a bathtub shaped curve (see the figure below)

Figure 1. The relation between Longevity and obesity in humans Image credit: PNAS 1958

So people at the very thin end also die earlier than people in the middle, just as people at the very heavy end die earlier
We can argue whether it’s causal
There are 2 observations here: 1) It is clear that people thinner than those with an intermediate BMI also die earlier 2) When people are sick or injured, obese people often live the longest This is true even though obesity is associated with increased mortality rate or decreased longevity
1) It is clear that people thinner than those with an intermediate BMI also die earlier
2) When people are sick or injured, obese people often live the longest This is true even though obesity is associated with increased mortality rate or decreased longevity
This is true even though obesity is associated with increased mortality rate or decreased longevity
So if somebody comes in with kidney failure or someone comes in after a major injury or a major infection, they’re in the hospital, it’s often the heaviest people that live longer This started to be talked about maybe 10, 15 years ago
This started to be talked about maybe 10, 15 years ago

“ It’s very difficult to disentangle cause and effect. We can observe lots of associations, but it’s just hard to know what to make of all of these associations, and what’s causal .” – David Allison

There are multiple hypotheses that are consistent with the data That’s why the randomized experiment allows us to do things that otherwise we can’t do, sort of eliminates more competing hypotheses We don’t know what’s causal yet
We have thrown out 1 model
David and his postdoc (Doug Childers, a good mathematician) asked 2 questions: 1) What if obesity makes it more likely that you get a major illness or injury Could this be why obesity is associated with a risk of early mortality? 2) Once you get a major illness or injury, does being heavier (more obese) reduce your risk of dying from it? Compare to this analogy— suppose we are going on a hike in the Grand Canyon We go to an outfitter and he says, “ you’re about 10 years younger than me; you have a choice. I can give you this fat suit you can wear, it has lots of padding on it. If you fall off the cliff, it makes it much more likely you’ll survive, but it makes you a little clumsy. So it makes you more likely to fall off the cliff ” You might think that you have good balance and eyesight, you’re young and strong; so you say no to the fat suit Somebody 10 years older may be struggling with eyesight, balance, or strength; and they may say yes, “ I’ll take the fat suit ” And so whether the fat suit is good for you may depend upon the probability of falling, to begin with Under that mathematical model, David can show, in fact, that the point of BMI, the nadir of that bathtub shape concave upward curve, should keep moving to the right as you age, which is exactly what it does They have a model that’s consistent with the data, but the data don’t prove their model There are other models that would be consistent with it
That’s why the randomized experiment allows us to do things that otherwise we can’t do, sort of eliminates more competing hypotheses
We don’t know what’s causal yet
1) What if obesity makes it more likely that you get a major illness or injury Could this be why obesity is associated with a risk of early mortality?
2) Once you get a major illness or injury, does being heavier (more obese) reduce your risk of dying from it?
Compare to this analogy— suppose we are going on a hike in the Grand Canyon We go to an outfitter and he says, “ you’re about 10 years younger than me; you have a choice. I can give you this fat suit you can wear, it has lots of padding on it. If you fall off the cliff, it makes it much more likely you’ll survive, but it makes you a little clumsy. So it makes you more likely to fall off the cliff ” You might think that you have good balance and eyesight, you’re young and strong; so you say no to the fat suit Somebody 10 years older may be struggling with eyesight, balance, or strength; and they may say yes, “ I’ll take the fat suit ” And so whether the fat suit is good for you may depend upon the probability of falling, to begin with
Under that mathematical model, David can show, in fact, that the point of BMI, the nadir of that bathtub shape concave upward curve, should keep moving to the right as you age, which is exactly what it does They have a model that’s consistent with the data, but the data don’t prove their model There are other models that would be consistent with it
Could this be why obesity is associated with a risk of early mortality?
We go to an outfitter and he says, “ you’re about 10 years younger than me; you have a choice. I can give you this fat suit you can wear, it has lots of padding on it. If you fall off the cliff, it makes it much more likely you’ll survive, but it makes you a little clumsy. So it makes you more likely to fall off the cliff ”
You might think that you have good balance and eyesight, you’re young and strong; so you say no to the fat suit
Somebody 10 years older may be struggling with eyesight, balance, or strength; and they may say yes, “ I’ll take the fat suit ”
And so whether the fat suit is good for you may depend upon the probability of falling, to begin with
They have a model that’s consistent with the data, but the data don’t prove their model
There are other models that would be consistent with it

Putting some numbers to it

Peter notes that this U-shaped curve gives an optimal BMI, a BMI associated with the lowest mortality (see the figure below) Is David suggesting that instead of using 1 plot for everybody, graph it by decade? What does this U-shape cure look like for people in their 20s, 30s, 30s…up to 90s?
Is David suggesting that instead of using 1 plot for everybody, graph it by decade?
What does this U-shape cure look like for people in their 20s, 30s, 30s…up to 90s?

Figure 2. Mortality rates versus BMI at age 20 (red), 30 (green), 40 (yellow), 50 (purple), 60 (magenta), and 70 (blue) Image Credit: International Journal of Obesity 2010

Figure 3. BMI for a range of heights and weights, colors indicate World Health Organization BMI categories: underweight, normal weight, overweight, moderately obese, severely obese, and very severely obese Image Credit: Wikipedia

David tells a story that’s not perfectly true; it’s roughly true; it conveys the nice element of this The average American might gain about a pound a year For an average height, about 6 or so pounds might be a BMI unit And so that might mean that over 6 years, you’d be about one BMI unit heavier And that’s not too far off from how the nadir moves It’s almost as though your weight is increasing to keep you at the nadir, which is an interesting speculation And if you looked at people who are maybe 20 years old, that nadir might not be too far from 20, in some populations
We can come back and make distinctions by age, race, and sex
But putting that aside for the moment, very loosely speaking, you might say, that nadir might be far down near [a BMI of] 20 when you’re 20 And by the time you’re 80, it’s not to 80, but by the time you’re 80, it might be well above [a BMI of] 30, maybe even in the low 30s We generally say, “ 30 is the beginning of obesity ”
For those who are not used to BMI’s, here are some touchstones (see also the previous figure) The supermodel Kate Moss (at least a decades ago) had a BMI in 16 to 17 range We say that about 18.5 is sort of the beginning of normal weight; less is underweight David’s BMI right now is probably 21-ish Bill Clinton’s BMI at the height of his presidency was probably 27, 28 (he’s since lost weight) Obesity begins around a BMI of 30 A top class Sumo wrestler has a BMI of about 43, 44 So it’s really 30, 32, where you see people 70, 80, and above, having that lowest mortality rate
The average American might gain about a pound a year
For an average height, about 6 or so pounds might be a BMI unit
And so that might mean that over 6 years, you’d be about one BMI unit heavier
And that’s not too far off from how the nadir moves
It’s almost as though your weight is increasing to keep you at the nadir, which is an interesting speculation
And if you looked at people who are maybe 20 years old, that nadir might not be too far from 20, in some populations
And by the time you’re 80, it’s not to 80, but by the time you’re 80, it might be well above [a BMI of] 30, maybe even in the low 30s We generally say, “ 30 is the beginning of obesity ”
We generally say, “ 30 is the beginning of obesity ”
The supermodel Kate Moss (at least a decades ago) had a BMI in 16 to 17 range
We say that about 18.5 is sort of the beginning of normal weight; less is underweight
David’s BMI right now is probably 21-ish
Bill Clinton’s BMI at the height of his presidency was probably 27, 28 (he’s since lost weight)
Obesity begins around a BMI of 30
A top class Sumo wrestler has a BMI of about 43, 44
So it’s really 30, 32, where you see people 70, 80, and above, having that lowest mortality rate

Interpreting BMI and mortality data and considering confounders [43:15]

Peter wonders if there is a risk that we are looking at confounders here? Could affluence be a confounder? When body composition is taken into account, do you see the same thing? Some people have a BMI of 30 and fall into the obese category even though they only have 15% body fat; instead they are incredibly muscular How do we reconcile, one, the potential confounders of that type of an analysis with this layer of granularity in the data that looks at adiposity versus lean mass?
Could affluence be a confounder?
When body composition is taken into account, do you see the same thing? Some people have a BMI of 30 and fall into the obese category even though they only have 15% body fat; instead they are incredibly muscular
How do we reconcile, one, the potential confounders of that type of an analysis with this layer of granularity in the data that looks at adiposity versus lean mass?
Some people have a BMI of 30 and fall into the obese category even though they only have 15% body fat; instead they are incredibly muscular

“ The confounding question is a nightmare ” – David Allison

David notes this is the challenge of observational research in general
There are no simple solutions to it, other than trying to triangulate on the answer with multiple studies
What we really want are pure, randomized experiments in humans With large samples and perfect compliance for many years And we want to randomly assign people to be obese or not obese Obviously, we can’t do that
What we have is observational epidemiology There are randomized trials where people lose weight There are non-randomized trials, like Sjostrom’s with surgery There are mouse studies
With large samples and perfect compliance for many years
And we want to randomly assign people to be obese or not obese
Obviously, we can’t do that
There are randomized trials where people lose weight
There are non-randomized trials, like Sjostrom’s with surgery
There are mouse studies

“ We look at all these different things, and we try to just put the puzzle together as best we can ” – David Allison

Possibilities for confounding of the BMI, mortality data

There are a lot of possibilities for confounding, cigarette smoking was one of the early ones Avery famous paper by JoAnn Manson and colleagues, published in JAMA , pointing out that the “ right way ,” to analyze BMI and mortality data was to exclude smokers; otherwise you may have confounding by smoking Published in 1987, Body Weight and Longevity: A Reassessment Smoking makes you thinner; smoking kills you earlier You’ve got to throw out the subjects who die early, because subjects who die early may have been sick And sickness makes you thinner and makes you die earlier, that is a confounder
It has since been proved mathematically, that throwing out these confounders is not a good thing to do But for a long time, it was believed
Peter asks about the low end of the BMI chart One of the most obvious explanations for the uptick in mortality at very low BMIs, is all of liver disease, the kidney disease, the types of chronic diseases that actually do lead to muscle wasting and things like that
David includes them in his analysis What they’ve shown is that throwing out subjects who die early in the analysis doesn’t help, or it doesn’t reliably help What they showed is not that that confounding doesn’t occur Confounding absolutely can occur and they think it’s likely
Avery famous paper by JoAnn Manson and colleagues, published in JAMA , pointing out that the “ right way ,” to analyze BMI and mortality data was to exclude smokers; otherwise you may have confounding by smoking Published in 1987, Body Weight and Longevity: A Reassessment
Smoking makes you thinner; smoking kills you earlier
You’ve got to throw out the subjects who die early, because subjects who die early may have been sick
And sickness makes you thinner and makes you die earlier, that is a confounder
Published in 1987, Body Weight and Longevity: A Reassessment
But for a long time, it was believed
One of the most obvious explanations for the uptick in mortality at very low BMIs, is all of liver disease, the kidney disease, the types of chronic diseases that actually do lead to muscle wasting and things like that
What they’ve shown is that throwing out subjects who die early in the analysis doesn’t help, or it doesn’t reliably help
What they showed is not that that confounding doesn’t occur Confounding absolutely can occur and they think it’s likely
Confounding absolutely can occur and they think it’s likely

David’s early work analyzing BMI data [46:15]

When David went to analyze his first BMI mortality data set, he had no training in this So he called up his friends to ask about it and ask for references to explain this The epidemiologists would say “ No, it’s obvious that it works ” David replied, “ Well, it’s not obvious to me ” And they said, “ Well, maybe you’re not smart enough to be an epidemiologist ” When he asked the statisticians about a paper that says you have to eliminate early death in the analysis, they would laugh and they replied, “ That’s the most ridiculous thing I’ve ever heard. We don’t just throw out data and think it makes things better. You’ve got to have a model that you fit things to .”
David got a small grant from the CDC and looked at mathematical proofs, computer simulations, and meta-analysis
The mathematical proof showed that not only did removing early deaths help reduce the confounding, it could make it worse
Simulation showed the same thing in realistic data scenarios
Then the meta-analysis showed that on average it didn’t make much difference at all
So he called up his friends to ask about it and ask for references to explain this
The epidemiologists would say “ No, it’s obvious that it works ” David replied, “ Well, it’s not obvious to me ” And they said, “ Well, maybe you’re not smart enough to be an epidemiologist ”
When he asked the statisticians about a paper that says you have to eliminate early death in the analysis, they would laugh and they replied, “ That’s the most ridiculous thing I’ve ever heard. We don’t just throw out data and think it makes things better. You’ve got to have a model that you fit things to .”
David replied, “ Well, it’s not obvious to me ”
And they said, “ Well, maybe you’re not smart enough to be an epidemiologist ”

“ So throwing out the subjects who die early, basically, just reduces your power in most practical situations ” – David Allison

Confounding factors

People suggested throwing other people out of the analysis, to control for intermediary variables Diabetes and hypertension Cutting people with these conditions out of the analysis wasn’t enough to flatten out that left end of the U-shaped curve So he also cut out people with a lot of weight fluctuation This got rid of most of it, but it didn’t completely get rid of it This was one of the bigger variables, but what it means is unclear
Katherine Flegal has written very well on this, and talked about how much you’re throwing away She points out that we do observe these patterns, but what they mean causally is unclear
Diabetes and hypertension Cutting people with these conditions out of the analysis wasn’t enough to flatten out that left end of the U-shaped curve
So he also cut out people with a lot of weight fluctuation This got rid of most of it, but it didn’t completely get rid of it This was one of the bigger variables, but what it means is unclear
Cutting people with these conditions out of the analysis wasn’t enough to flatten out that left end of the U-shaped curve
This got rid of most of it, but it didn’t completely get rid of it
This was one of the bigger variables, but what it means is unclear
She points out that we do observe these patterns, but what they mean causally is unclear

Stigma from being overweight may have an effect

The bottom line is, it’s likely that there’s confounding by cigarette smoking and socioeconomic status and stigma

“ How much does obesity kill you because it stigmatizes you and it creates some stress?” – David Allison

Stigma may be why the BMI associated with the lowest mortality has been increasing over calendar time It’s not just with age of individuals If you compare data collected in the 1970s to data collected in the 1990s, obesity doesn’t look quite as bad in the 1990s as it did in the 1970s At least from an association point of view This is true in Denmark, in the US, in meta-analyses But it’s not true for every age, race, sex group Why is that? Maybe it’s stigma
If you’ve ever watched that old TV show, The Three Stooges , the character Curly was often mocked as the fat guy By today’s standards, he’s not that big So as different BMIs become normative, stigma too changes over time Maybe this accounts for part of it
There’s lots of potential confounding going on there, but there’s lots of other possible explanations
It’s not just with age of individuals
If you compare data collected in the 1970s to data collected in the 1990s, obesity doesn’t look quite as bad in the 1990s as it did in the 1970s At least from an association point of view This is true in Denmark, in the US, in meta-analyses But it’s not true for every age, race, sex group Why is that? Maybe it’s stigma
At least from an association point of view
This is true in Denmark, in the US, in meta-analyses
But it’s not true for every age, race, sex group Why is that? Maybe it’s stigma
Why is that?
Maybe it’s stigma
By today’s standards, he’s not that big
So as different BMIs become normative, stigma too changes over time
Maybe this accounts for part of it

Important questions

The bottom line, we don’t know; and the real important question then is, what’s the effect of intervention?
One of the clearest thinkers David knows is Don Rubin , a statistician at Harvard He developed the Rubin Causal Model He is always asking, “ What’s the intervention? If you say, does this cause that? What do you mean? Compared to what? ” It’s always got to be compared to what?
So if you say weight loss is going to increase longevity (that’s the question) well, how are you going to achieve that weight? What are you going to do to get that? If it’s surgery, then what’s the effect of surgery? If it’s a GLP-1 agonist, what’s the effect of a GLP-1 agonist, et cetera?
David thinks this is the key question
We are starting to see that some of these things do prolong life: surgery, SGLT-2 inhibitors, GLP-1 agonists, and so forth
He developed the Rubin Causal Model
He is always asking, “ What’s the intervention? If you say, does this cause that? What do you mean? Compared to what? ”
It’s always got to be compared to what?
What are you going to do to get that?
If it’s surgery, then what’s the effect of surgery?
If it’s a GLP-1 agonist, what’s the effect of a GLP-1 agonist, et cetera?

How body composition and ethnicity factor into consideration of BMI data [50:30]

BMI is a measure of mass divided by stature
It was developed back in the 19th century by Adolph Quetelet , who was a Belgian astronomer, epidemiologist, statistician, mathematician, a brilliant guy
One would think that the mass of a three dimensional object ought to increase in proportion to the cube of a linear dimension If we were spheres of uniform density, but we’re not Empirically, BMI works closer to the square for adult humans
Quetelet said, “ Take mass or weight over stature squared, the square of stature ” Then it was called Quetelet’s Index Now we call it BMI It was rediscovered in the ‘60s or ‘70s by Ancel Keys , and termed BMI, body mass index And every few years, some smart person likes to come along, says, “ It should be cubed ”
BMI doesn’t really take into account body composition The NBA center would have a BMI greater than 30 and yet look how strong and fit that person is What physician in their right mind would diagnose them as obese?
If we were spheres of uniform density, but we’re not
Empirically, BMI works closer to the square for adult humans
Then it was called Quetelet’s Index
Now we call it BMI
It was rediscovered in the ‘60s or ‘70s by Ancel Keys , and termed BMI, body mass index
And every few years, some smart person likes to come along, says, “ It should be cubed ”
The NBA center would have a BMI greater than 30 and yet look how strong and fit that person is What physician in their right mind would diagnose them as obese?
What physician in their right mind would diagnose them as obese?

“ BMI is a useful tool for epidemiologic research and some simple physiologic research and some simple clinical trials, it’s not a perfect clinical tool ” – David Allison

For the average person, BMI works okay

Do conclusions about BMI hold up in different ethnicities?

Peter asks about different ethnicities, Asians, East Asians Some people are skinny fat , they have a BMI of 26 but have metabolic syndrome, tons of visceral fat, very little muscle mass ( see Ethnic Differences in BMI and Disease Risk ) This is a different phenotype than perhaps what the model was built on
How much is the metric that we use for BMI validated in other ethnicities? Where a BMI of 20 to 25 is about perfect 25 to 30 is overweight 30 to 40 is obese Then morbidly obese kicks in at some point
With a few exceptions, the idea that there’s a curve and that it’s a generally concave up curve
Yes, there are exceptions
The shape of that curve is not the same in every age, race, and sex group
It does seem that the right side (the part where you’re getting too high in BMI and risk is going up) seems to occur a lot earlier among people of Middle Eastern and East Asian descent
So this is very simple model to use just 1 curve for everybody
A slight more complicated models takes into account some of the other factors How much of your fat is subcutaneous versus how much is visceral. Some groups have more visceral fat than the others for any given body mass index; and therefore it adjusts the curve
Some people are skinny fat , they have a BMI of 26 but have metabolic syndrome, tons of visceral fat, very little muscle mass ( see Ethnic Differences in BMI and Disease Risk )
This is a different phenotype than perhaps what the model was built on
Where a BMI of 20 to 25 is about perfect
25 to 30 is overweight
30 to 40 is obese
Then morbidly obese kicks in at some point
How much of your fat is subcutaneous versus how much is visceral. Some groups have more visceral fat than the others for any given body mass index; and therefore it adjusts the curve
Some groups have more visceral fat than the others for any given body mass index; and therefore it adjusts the curve

“ The narratives we have about obesity, including about ethnicity and obesity, are grossly oversimplified ” – David Allison

So we often hear, “ Obesity’s selectively a disease of the poor and uneducated ”
In this country, it’s often stated, “ Minority status leads to less income, less education, which in turn, leads to poorer access to healthcare, poorer habits, poorer living environments, which leads to poor health and reduced longevity ” And there’s probably some truth to that, but it’s not 1 to 1; it’s not simple
For example, when we hear that there’s this inverse relationship between socioeconomic status and obesity, this varies depending on ethnicity We hear this over and over again It was first shown by Mickey Stunkard , again, in the 1950s, in the Midtown Manhattan Project It’s reliably true in adult white women When you go outside the group of adult white women, it’s not always true If you go to African American women, there is virtually no association between socioeconomic status and obesity When you go to African American men and look at their obesity levels, they’re very similar to the obesity levels of European American men, white American men But if you look at African American women’s obesity levels, and you compare it to European or white American women, it’s much higher If you bring Hispanic Americans in, both men and women have higher levels of obesity, than do European American men and women So in Hispanic Americans, there is an ethnicity difference (but not by gender) In African Americans, there is a gender by ethnicity difference When you look at mortality, the African American curves follow similarly, but not identically, to the European American curves
But in Hispanic Americans, David’s research can’t find an association between BMI and longevity in this group This is true across all BMIs The data sets they have are not perfect; the follow-ups may not be long enough, the sample sizes may not be big enough He’s not saying it’s causal, he’s only explaining what they observed in publicly available datasets of Hispanic Americans Analysis of BMI and longevity could not show an association between elevated BMI and mortality in Hispanic Americans
And there’s probably some truth to that, but it’s not 1 to 1; it’s not simple
We hear this over and over again
It was first shown by Mickey Stunkard , again, in the 1950s, in the Midtown Manhattan Project
It’s reliably true in adult white women
When you go outside the group of adult white women, it’s not always true
If you go to African American women, there is virtually no association between socioeconomic status and obesity
When you go to African American men and look at their obesity levels, they’re very similar to the obesity levels of European American men, white American men
But if you look at African American women’s obesity levels, and you compare it to European or white American women, it’s much higher
If you bring Hispanic Americans in, both men and women have higher levels of obesity, than do European American men and women
So in Hispanic Americans, there is an ethnicity difference (but not by gender)
In African Americans, there is a gender by ethnicity difference
When you look at mortality, the African American curves follow similarly, but not identically, to the European American curves
This is true across all BMIs
The data sets they have are not perfect; the follow-ups may not be long enough, the sample sizes may not be big enough
He’s not saying it’s causal, he’s only explaining what they observed in publicly available datasets of Hispanic Americans
Analysis of BMI and longevity could not show an association between elevated BMI and mortality in Hispanic Americans

Superior tools for measuring obesity at the individual level [57:15]

Peter is at the other end of the spectrum in terms of concerns at the public health level; he has the luxury of looking at 1 person at at time and trying to come up with the best course of action
His view of BMI is quite negative Maybe it’s the least bad tool available to get massive data sets and broad assessments on, for understanding what’s going on at the population level
But BMI offers little insight, relative to other tools
Peter uses other tools to measure obesity ; DEXA scans provide 4 points of information: 1) % body fat 2) Visceral fat (VAT, visceral adipose tissue) 3) Bone mineral density 4) Appendicular Lean Mass Index, a measure of muscle mass It also provides information about subcutaneous fat, but that doesn’t seem to matter because it is incredibly genetic and relatively uncoupled from metabolic health VAT, the visceral adipose tissue seems to be much more tightly correlated to what we see when we look at more sophisticated biomarkers of insulin sensitivity and metabolic health, and any evidence of liver fat
So Peter is glad he gets to look at these other metrics It’s a luxury that a statistician or an epidemiologist doesn’t have At the individual level, there is much more data and you can be more nuanced in your appreciation for things
Peter wonders if at the population level, something better than BMI will come alone one day This example with the Hispanic subset is mind boggling and speaks to the futility of BMI measurement in some populations
David acknowledges this is one plausible interpretation
He doesn’t think we’re far away from better tools
He published some work years ago on the idea of using 3D photography, take a picture of somebody from a couple of angles This came out of work experience way back at the New York Obesity Research Center, when Steve Heymsfield (David’s mentor) would study professional basketball players He was the king of body composition, and he would study them Technicians who measured people’s body composition every day would say, “ I can look at a person and tell you how much fat they have. And I’ll be very accurate .” David thought if they could do this with their eye, then he could do it with a camera He got a NIH grant with Olivia Affuso and Steve Heymsfield to look at this; they published a paper on it, and since then many others have done it as well He thinks Amazon may be working on this or already have something out on this; we’ll get to the point where we have 3D photography
If you can measure something’s weight and volume, you know it’s density If you know a little bit about human anatomy, you can figure out from density, body fat He can do this with a camera
To measure mass there is: DEXA, plethysmography, isotope dilution techniques, etc.
There’s this idea of fit for purpose If you were to say, “ Is my vehicle that I drive, is this precision enough for the Indy 500? ’ The answer is no; you need a better vehicle But I’m not in the Indy 500, I’m just driving 5 miles to and from work every day; it’s fine Similarly, if you were to say, “ What proportion of that country has obesity? ” BMI probably provides a reasonable estimate But if you want to say, “ I want to help this individual patient ,” especially at the sort of the kind of artisan level that Peter goes at Then you need better tools
Maybe it’s the least bad tool available to get massive data sets and broad assessments on, for understanding what’s going on at the population level
1) % body fat
2) Visceral fat (VAT, visceral adipose tissue)
3) Bone mineral density
4) Appendicular Lean Mass Index, a measure of muscle mass
It also provides information about subcutaneous fat, but that doesn’t seem to matter because it is incredibly genetic and relatively uncoupled from metabolic health
VAT, the visceral adipose tissue seems to be much more tightly correlated to what we see when we look at more sophisticated biomarkers of insulin sensitivity and metabolic health, and any evidence of liver fat
It’s a luxury that a statistician or an epidemiologist doesn’t have
At the individual level, there is much more data and you can be more nuanced in your appreciation for things
This example with the Hispanic subset is mind boggling and speaks to the futility of BMI measurement in some populations
This came out of work experience way back at the New York Obesity Research Center, when Steve Heymsfield (David’s mentor) would study professional basketball players
He was the king of body composition, and he would study them
Technicians who measured people’s body composition every day would say, “ I can look at a person and tell you how much fat they have. And I’ll be very accurate .”
David thought if they could do this with their eye, then he could do it with a camera
He got a NIH grant with Olivia Affuso and Steve Heymsfield to look at this; they published a paper on it, and since then many others have done it as well
He thinks Amazon may be working on this or already have something out on this; we’ll get to the point where we have 3D photography
If you know a little bit about human anatomy, you can figure out from density, body fat
He can do this with a camera
If you were to say, “ Is my vehicle that I drive, is this precision enough for the Indy 500? ’ The answer is no; you need a better vehicle But I’m not in the Indy 500, I’m just driving 5 miles to and from work every day; it’s fine
Similarly, if you were to say, “ What proportion of that country has obesity? ” BMI probably provides a reasonable estimate
But if you want to say, “ I want to help this individual patient ,” especially at the sort of the kind of artisan level that Peter goes at Then you need better tools
But I’m not in the Indy 500, I’m just driving 5 miles to and from work every day; it’s fine
BMI probably provides a reasonable estimate
Then you need better tools

Using BMI data for actionable steps to combat obesity [1:02:00]

Important questions

With BMI we can accurately plot out the histogram of exactly what the BMI is by age and by demographic and all those things

Questions: Are people in Indiana more or less healthy than people in Kentucky? And are they more or less healthy than the average American?’ What can we do to improve their health? Could everybody become healthier? Could we extend the life of the average person in the state of Indiana by three years? What would the intervention need to be? These questions lead to more complicated problems
David notes when he talks to people, even physicians, even highly educated scholars, there’s this bifurcation There’s the data and those who look at the data, and if they’re really honest, they say, “ We agree. Surgery works, pharmaceuticals work, individualized or group-based clinical treatment with behavioral cognitive techniques work somewhat for some period of time, meal replacement formulas work, somewhat for some period of time .” But if you’re honest, all the public health stuff we’ve tried for obesity doesn’t work
He gets asked a lot, “ What is your goal? ” Is it to expose people to ideas so the next really smart kid can figure it out This goal of raising consciousness is fine Is the goal to tell communities, “ We know you’re suffering and we know this is concerning, and we want you to know we care, and we’re trying. We’re not really going to necessarily reduce obesity levels. We want you to know we care, and you want farmers markets in the school parking lot. You want vending machines changed. You want running tracks built in your neighborhood. We’ll build a running track and so on. And we’ll feel better about we’re caring for each other, but it’s probably not going to affect obesity, given what we know right now ” Or is the goal to actually have less people suffer from obesity; to reduce the obesity levels and improve public health? This won’t win any feel-good awards
Successful approaches include: surgery, pharmaceuticals, and to some extent, individualized treatment, cognitive behavioral group-based treatment, including things like meal replacements and so on
If the state of Indiana handed me $10 million and said, “ Make a difference ” he: Would NOT build farmers markets in school yards He would give a small number of people bariatric surgery And a subset of those would likely live longer, on average
Are people in Indiana more or less healthy than people in Kentucky?
And are they more or less healthy than the average American?’
What can we do to improve their health?
Could everybody become healthier?
Could we extend the life of the average person in the state of Indiana by three years? What would the intervention need to be? These questions lead to more complicated problems
What would the intervention need to be?
These questions lead to more complicated problems
There’s the data and those who look at the data, and if they’re really honest, they say, “ We agree. Surgery works, pharmaceuticals work, individualized or group-based clinical treatment with behavioral cognitive techniques work somewhat for some period of time, meal replacement formulas work, somewhat for some period of time .”
But if you’re honest, all the public health stuff we’ve tried for obesity doesn’t work
Is it to expose people to ideas so the next really smart kid can figure it out This goal of raising consciousness is fine
Is the goal to tell communities, “ We know you’re suffering and we know this is concerning, and we want you to know we care, and we’re trying. We’re not really going to necessarily reduce obesity levels. We want you to know we care, and you want farmers markets in the school parking lot. You want vending machines changed. You want running tracks built in your neighborhood. We’ll build a running track and so on. And we’ll feel better about we’re caring for each other, but it’s probably not going to affect obesity, given what we know right now ”
Or is the goal to actually have less people suffer from obesity; to reduce the obesity levels and improve public health? This won’t win any feel-good awards
This goal of raising consciousness is fine
This won’t win any feel-good awards
Would NOT build farmers markets in school yards
He would give a small number of people bariatric surgery And a subset of those would likely live longer, on average
And a subset of those would likely live longer, on average

Why maintaining weight loss is more challenging than losing weight [1:06:00]

This is a tough one; there is probably no single explanation
You can approach this from an evolutionary perspective, biochemical perspective; you can think about mechanisms David doesn’t know all the answers
From the evolutionary point of view, for a long time, the meme was it’s the thrifty gene hypothesis from James Neel The idea is that animals/ humans throughout evolutionary history have been on the brink of starvation They did anything they could to preserve energy When given the opportunity to get more energy, they ate as much as they could, while they could Now in the modern environment, most of use over consume
David think’s this is simplistic for many reasons 1) As the lawyers say, “Objection, it assumes facts, not in evidence ” It’s not at all clear that humans have been on the brink of starvation throughout history Robert Fogel , who won the Nobel prize for looking at these old data, going back to at least the 1700s, of British naval recruits and other places, saw that BMI (on average) went up over the centuries There’s a little fluctuation as things get better and worse in places 2) How does this account for pregnancy The latest data from John Speakman and colleagues in Science suggests that women’s energy intake doesn’t need to go up that much during pregnancy, but they still go up Published in August 2021, Daily energy expenditure through the human life course So, if humans have been reproducing for millennia, where did all that extra energy come from if we were all on the brink of starvation all the time? 3) Anybody whoever goes fishing knows that the idea that every animal is hungry all the time and is going to grab every bite of food you throw in front of it, is not true 4) Some animals do get obese when given unlimited food, some don’t, both within and across species there’s lots of differences
This is where John Speakman came in and questioned this idea
Speakman thinks its freedom from predation Back in history we were prey; then there was a certain point where we learned to use tools and hunt together, and we stopped being prey, and we started being predators When we switched from being prey to predators, we didn’t need to hide in our boroughs and eat the least we could because every time we came out we were potentially exposed to a predator As a predator we could sort of walk around and eat kind of ad-lib In this situation, the genes that were being selected for that gave us satiety mechanisms that kept our weight down were no longer under selection It wasn’t that nature was selecting for genes that made us fatter; instead nature was not selecting for genes that keep us thin Drift mutations allow this to happen There’s not just 1 factor
David doesn’t know all the answers
The idea is that animals/ humans throughout evolutionary history have been on the brink of starvation
They did anything they could to preserve energy When given the opportunity to get more energy, they ate as much as they could, while they could
Now in the modern environment, most of use over consume
When given the opportunity to get more energy, they ate as much as they could, while they could
1) As the lawyers say, “Objection, it assumes facts, not in evidence ” It’s not at all clear that humans have been on the brink of starvation throughout history Robert Fogel , who won the Nobel prize for looking at these old data, going back to at least the 1700s, of British naval recruits and other places, saw that BMI (on average) went up over the centuries There’s a little fluctuation as things get better and worse in places
2) How does this account for pregnancy The latest data from John Speakman and colleagues in Science suggests that women’s energy intake doesn’t need to go up that much during pregnancy, but they still go up Published in August 2021, Daily energy expenditure through the human life course So, if humans have been reproducing for millennia, where did all that extra energy come from if we were all on the brink of starvation all the time?
3) Anybody whoever goes fishing knows that the idea that every animal is hungry all the time and is going to grab every bite of food you throw in front of it, is not true
4) Some animals do get obese when given unlimited food, some don’t, both within and across species there’s lots of differences
It’s not at all clear that humans have been on the brink of starvation throughout history
Robert Fogel , who won the Nobel prize for looking at these old data, going back to at least the 1700s, of British naval recruits and other places, saw that BMI (on average) went up over the centuries There’s a little fluctuation as things get better and worse in places
There’s a little fluctuation as things get better and worse in places
The latest data from John Speakman and colleagues in Science suggests that women’s energy intake doesn’t need to go up that much during pregnancy, but they still go up Published in August 2021, Daily energy expenditure through the human life course So, if humans have been reproducing for millennia, where did all that extra energy come from if we were all on the brink of starvation all the time?
Published in August 2021, Daily energy expenditure through the human life course
So, if humans have been reproducing for millennia, where did all that extra energy come from if we were all on the brink of starvation all the time?
Back in history we were prey; then there was a certain point where we learned to use tools and hunt together, and we stopped being prey, and we started being predators
When we switched from being prey to predators, we didn’t need to hide in our boroughs and eat the least we could because every time we came out we were potentially exposed to a predator
As a predator we could sort of walk around and eat kind of ad-lib
In this situation, the genes that were being selected for that gave us satiety mechanisms that kept our weight down were no longer under selection
It wasn’t that nature was selecting for genes that made us fatter; instead nature was not selecting for genes that keep us thin Drift mutations allow this to happen
There’s not just 1 factor
Drift mutations allow this to happen

Compare to sexual reproduction to understand fitness

Why is maintaining weightloss difficult?
David compares this question to the evolution of sexual reproduction, “ the queen of questions in biology ” Nobody can really figure out why do we have sexual reproduction when asexual seems so much more efficient from a genetic fitness point of view People have proposed different hypotheses for it and no one seems to work mathematically Maybe it only works mathematically when you put all these hypothesis together Maybe it’s just an inelegant solution
For example, Daph ( Daphnia ) is a species that can reproduce both sexually and asexually (see the figure below) There are many species that can do this In asexual reproduction an organism makes a copy of itself; it reproduces all of its genes From the Richard Dawkins point of view, The Selfish Gene , those genes all got their way Those genes all won; they got copied And genes that are good at getting copied will get copied again in the future, so you have more of those That’s how evolution works
Nobody can really figure out why do we have sexual reproduction when asexual seems so much more efficient from a genetic fitness point of view
People have proposed different hypotheses for it and no one seems to work mathematically
Maybe it only works mathematically when you put all these hypothesis together
Maybe it’s just an inelegant solution
There are many species that can do this
In asexual reproduction an organism makes a copy of itself; it reproduces all of its genes
From the Richard Dawkins point of view, The Selfish Gene , those genes all got their way Those genes all won; they got copied And genes that are good at getting copied will get copied again in the future, so you have more of those That’s how evolution works
Those genes all won; they got copied
And genes that are good at getting copied will get copied again in the future, so you have more of those
That’s how evolution works

Figure 4. The life cycle of Daphnia species alternates between asexual (parthenogenetic) and sexual reproduction Image credit: Wikipedia

Sexual reproduction requires a partner This invites questions like why are there only 2 sexes? Why Have sexes at all? DNA could be exchanged without sexes; bacteria do it through conjugation Say there are two sexes male and female, they come together and the offspring has roughly 50% of the genetic material of one parent and 50% of the other The organism only copied half of itself so it didn’t win as much as if it copied itself entirely Why would an organism switch to sexual reproduction? It’s very inefficient from a genetic fitness point of view
The most compelling hypothesis David has heard is the so-called red queen hypothesis This is from Alice in Wonderland and Through the Looking Glass where the red queen is running with Alice Alice at one point says, “ We don’t seem to be getting anywhere. ” And the red queen says, “ Oh, in this world you have to run as fast as you can just to stay in place .” Alice says, “ Oh, in my world we run and we actually get somewhere .” The red queen hypothesis is the idea that you keep running as fast as you can just to stay steady This means, as humans live for a long time, there are these microbes in a human and they’re evolving much more rapidly because they have a much more shorter generation time As these microbes evolve, they start to get good at getting past human defenses and locks They start developing keys to the locks and the human wants to reset the locks The way you reset the locks is by getting a partner and mixing up your DNA with them The idea is that sexual reproduction is a way to keep up with the Jones’s And the Jones’s are all the microbes in your body This is the red queen hypothesis
Peter notes that if humans used asexual reproduction, we would have a population of identical people There might only be a few hundred thousand gene pools David agrees, there would be much less diversity
From a species point of view, if you believed in group selection, then you’d say, “ this is good for the species ”
A smart evolutionary biologist would come along and say that group selection doesn’t make sense Selection occurs at the individual or gene level It has to make sense for that individual; it has to enhance their fitness or their gene’s fitness One can argue that if only half the genes get reproduced, then the fitness level has to double to break even; this doesn’t really hold up
Muller and others have argued that if you consider a handful of things, put them together, that maybe the math works; but it’s very inelegant It’s probably the same with people and evolution
Neel had his thrifty gene hypothesis ; which argues you need to be selected to get food when you can Maybe not everybody was dying of starvation, but if you’re not getting enough food you may not be big enough to win the battle for mates in a polygyny physical combat mating system That may select for wanting to eat more If women get too thin, they stop menstruating They may not die of starvation, but their reproductive fitness goes down
Another idea centers around predation; freedom from predation is an idea John Speakman supports
Food safety is another idea; this is supported by Gary Beauchamp , from Monell Chemical Census Center Back in time before refrigeration and a modern, safe food supply, every time you ate something you were potentially exposed to microbes and toxins (not just predators) Eating less meant less exposure But now with a safer food supply, this pressure is less
Cooperative living is another angle; as a group it’s a bad situation if the members are so hungry all the time they are willing to kill each other for the last bite It would be good to have some satiety mechanisms to preserve social order Then everyone gets to eat a little and can work together to build tools and so on
This invites questions like why are there only 2 sexes? Why Have sexes at all? DNA could be exchanged without sexes; bacteria do it through conjugation
Say there are two sexes male and female, they come together and the offspring has roughly 50% of the genetic material of one parent and 50% of the other The organism only copied half of itself so it didn’t win as much as if it copied itself entirely Why would an organism switch to sexual reproduction? It’s very inefficient from a genetic fitness point of view
Why Have sexes at all?
DNA could be exchanged without sexes; bacteria do it through conjugation
The organism only copied half of itself so it didn’t win as much as if it copied itself entirely
Why would an organism switch to sexual reproduction?
It’s very inefficient from a genetic fitness point of view
This is from Alice in Wonderland and Through the Looking Glass where the red queen is running with Alice
Alice at one point says, “ We don’t seem to be getting anywhere. ” And the red queen says, “ Oh, in this world you have to run as fast as you can just to stay in place .” Alice says, “ Oh, in my world we run and we actually get somewhere .”
The red queen hypothesis is the idea that you keep running as fast as you can just to stay steady This means, as humans live for a long time, there are these microbes in a human and they’re evolving much more rapidly because they have a much more shorter generation time As these microbes evolve, they start to get good at getting past human defenses and locks They start developing keys to the locks and the human wants to reset the locks The way you reset the locks is by getting a partner and mixing up your DNA with them
The idea is that sexual reproduction is a way to keep up with the Jones’s And the Jones’s are all the microbes in your body This is the red queen hypothesis
This means, as humans live for a long time, there are these microbes in a human and they’re evolving much more rapidly because they have a much more shorter generation time
As these microbes evolve, they start to get good at getting past human defenses and locks
They start developing keys to the locks and the human wants to reset the locks
The way you reset the locks is by getting a partner and mixing up your DNA with them
And the Jones’s are all the microbes in your body
This is the red queen hypothesis
There might only be a few hundred thousand gene pools
David agrees, there would be much less diversity
Selection occurs at the individual or gene level
It has to make sense for that individual; it has to enhance their fitness or their gene’s fitness
One can argue that if only half the genes get reproduced, then the fitness level has to double to break even; this doesn’t really hold up
It’s probably the same with people and evolution
Maybe not everybody was dying of starvation, but if you’re not getting enough food you may not be big enough to win the battle for mates in a polygyny physical combat mating system That may select for wanting to eat more
If women get too thin, they stop menstruating They may not die of starvation, but their reproductive fitness goes down
That may select for wanting to eat more
They may not die of starvation, but their reproductive fitness goes down
Back in time before refrigeration and a modern, safe food supply, every time you ate something you were potentially exposed to microbes and toxins (not just predators) Eating less meant less exposure
But now with a safer food supply, this pressure is less
Eating less meant less exposure
It would be good to have some satiety mechanisms to preserve social order
Then everyone gets to eat a little and can work together to build tools and so on

Differing perspectives on the utility of nutritional epidemiology [1:16:30]

Epidemiology is married very closely with statistics Without statistics you can’t really do epidemiology
Most people understand this field has its limitations
There are 2 camps, 2 ends of the spectrum of views on nutritional epidemiology 1) There’s a camp of people that would say there is absolutely nothing wrong with epidemiology, nutritional epidemiology It is a masterful tool that provides exceptional insights without which we would be lost 2) There are people who say this is a tool that has probably reached its peak of utility The epidemiologists should probably focus on other problems outside of nutrition now Peter is a little closer to this end of the spectrum
Without statistics you can’t really do epidemiology
1) There’s a camp of people that would say there is absolutely nothing wrong with epidemiology, nutritional epidemiology It is a masterful tool that provides exceptional insights without which we would be lost
2) There are people who say this is a tool that has probably reached its peak of utility The epidemiologists should probably focus on other problems outside of nutrition now Peter is a little closer to this end of the spectrum
It is a masterful tool that provides exceptional insights without which we would be lost
The epidemiologists should probably focus on other problems outside of nutrition now
Peter is a little closer to this end of the spectrum

David’s perspective on nutritional epidemiology

David feels this is a topic that needs more discussion
In group 2 are the abolitionists: John Ioannidis said nutrition epidemiology is a dead science and it’s time to bury the corpse Gary Taubes has been very critical Nina Teicholz and many others have pointed out that perhaps this is just a worthless waste of time and misleading
Group 1 is the other end of the spectrum They are defenders of the status quo that say nutrition epidemiology is imperfect, as all tools are, but it is still a very valuable tool They claim there’s nothing seriously wrong with it and those who criticize it are naive and ignorant David doesn’t think that Gary Taubes, John, and Nina are naive and ignorant
John Ioannidis said nutrition epidemiology is a dead science and it’s time to bury the corpse
Gary Taubes has been very critical
Nina Teicholz and many others have pointed out that perhaps this is just a worthless waste of time and misleading
They are defenders of the status quo that say nutrition epidemiology is imperfect, as all tools are, but it is still a very valuable tool
They claim there’s nothing seriously wrong with it and those who criticize it are naive and ignorant
David doesn’t think that Gary Taubes, John, and Nina are naive and ignorant

“ We know that there’s something wrong there. When we look at the evidence, it’s very clear that many findings from nutrition epidemiology have not held up once we’ve done randomized controlled trials .” – David Allison

What is going on? Why don’t the findings of these studies hold up?

People will argue that there is nothing wrong with the evidence That meta-analysis on intervention and non-randomized studies give very similar findings to randomized studies But they’re often citing a non-randomized intervention study or a non-randomized observational study of pharmaceutical or other medical treatment They’re usually not citing nutritional studies These are very different situations
David argues that findings of nutritional epidemiology often don’t hold up very well
When you really look, you see a lot of things that look like obfuscation, exaggeration, sweeping under the rug of measurement error, and so on
There are huge issues with confounding
There are huge measurement problems
Many people say the status quo is not okay More change is needed than some minor fine-tuning
That meta-analysis on intervention and non-randomized studies give very similar findings to randomized studies But they’re often citing a non-randomized intervention study or a non-randomized observational study of pharmaceutical or other medical treatment They’re usually not citing nutritional studies These are very different situations
But they’re often citing a non-randomized intervention study or a non-randomized observational study of pharmaceutical or other medical treatment
They’re usually not citing nutritional studies
These are very different situations
More change is needed than some minor fine-tuning

“ We need reformation but we also need to use these tools well. This field is not going to go away whether you want it to or not .” – David Allison

Reform is needed

David believes reformation is essential; the status quo is completely unacceptable But abolition is neither realistic nor desirable
In one observational epidemiology nutrition study, the author correctly and honestly points out that it’s an observational study It reports an association, it doesn’t necessarily show causation Then says, “ but how could I be wrong? ” It could be that a measurement error creates this problem The authors reply, “ I used a validated food frequency questionnaire so it’s really okay .” It could be confounding due to socioeconomic status Does the nurse who works in a poor school in rural Indiana has the same socioeconomic status as the nurse who is married to a billionaire? They dismiss the idea that it’s not really causation
It would be okay measured and controlled for all these things: food intake, diet composition, housing and socioeconomic status, genetic background But you could never do this in humans
But abolition is neither realistic nor desirable
It reports an association, it doesn’t necessarily show causation
Then says, “ but how could I be wrong? ” It could be that a measurement error creates this problem The authors reply, “ I used a validated food frequency questionnaire so it’s really okay .” It could be confounding due to socioeconomic status Does the nurse who works in a poor school in rural Indiana has the same socioeconomic status as the nurse who is married to a billionaire?
They dismiss the idea that it’s not really causation
It could be that a measurement error creates this problem
The authors reply, “ I used a validated food frequency questionnaire so it’s really okay .”
It could be confounding due to socioeconomic status
Does the nurse who works in a poor school in rural Indiana has the same socioeconomic status as the nurse who is married to a billionaire?
But you could never do this in humans

A mouse study illustrating the impossibility of fully controlling for confounds in observational studies [1:22:15]

These controlled studies have been done in mice
David ran a mouse study where he randomly assigned mice to eat different amounts of calories, but all on the same diet Published in the European Journal of Clinical Investigation in 2016, Observational Research Rigor Alone Does Not Justify Causal Inference The mice were all given the same food They were all genetically identical because they were an inbred, isogenic strain ( C57BL/6 mice ) They’re all in the same housing conditions There’s no smoking. He had 4 groups of mice, randomly assigned to 1 of the following groups: 1) Low calorie 2) Medium calorie 3) High calorie effectively 4) Ad libitum
What he found was the more calories he assigned the mice to eat, the shorter they lived No surprise; this has been shown a thousand times in the literature by Roy Wallford , Rick Weindruch , and others over the decades
The interesting finding was with the ad libitum group Within that group, some chose to eat more than others Further, in this group they now have an observational epidemiologic study and can correlate amount chosen to be eaten with longevity
Published in the European Journal of Clinical Investigation in 2016, Observational Research Rigor Alone Does Not Justify Causal Inference
The mice were all given the same food
They were all genetically identical because they were an inbred, isogenic strain ( C57BL/6 mice )
They’re all in the same housing conditions
There’s no smoking.
He had 4 groups of mice, randomly assigned to 1 of the following groups: 1) Low calorie 2) Medium calorie 3) High calorie effectively 4) Ad libitum
1) Low calorie
2) Medium calorie
3) High calorie effectively
4) Ad libitum
No surprise; this has been shown a thousand times in the literature by Roy Wallford , Rick Weindruch , and others over the decades
Within that group, some chose to eat more than others
Further, in this group they now have an observational epidemiologic study and can correlate amount chosen to be eaten with longevity

“ Those mice that choose to eat more live longer. The association in the observational component is exactly opposite to the causal effect in the experimental component .” – David Allison

People argue that this observation is confounding They argue that the mice that are the strongest and healthiest have the biggest appetites and eat more This observation is confounding by general health
David agrees, and this is the point In an observational study that is more pristine than anybody will ever be able to do in humans, they can’t reproduce the cause of effect This suggests to David that reform is needed
They argue that the mice that are the strongest and healthiest have the biggest appetites and eat more
This observation is confounding by general health
In an observational study that is more pristine than anybody will ever be able to do in humans, they can’t reproduce the cause of effect
This suggests to David that reform is needed

Observational studies can be improved

David would love it if he never heard the plural analogy— there are no randomized controlled trials of parachute jumping There’s a wonderful book called, Randomistas (like fashionistas) by Andrew Leigh He says actually there are randomized controlled trials of parachute jumping It’s just not true Peter asks how the IRB for that was ever approved Participants have to be in the army This is used often as an excuse to argue, “ I can’t do the pure perfect pristine randomized control trial so therefore you have to accept any old observational study ” David doesn’t agree
David acknowledges that we may have to accept that we’re going to draw some inferences from something other than the pure classic pristine randomized control trial But in between that and any old observational epidemiologic study, there’s a lot of space
There are better studies Co-twin controls (hinted at that earlier) use identical twins and we randomly assign each to a different group For example, randomly assign 1 twin to exercise a lot; their twin brother doesn’t exercise, but has the same genotype That’s a tight control How about observing interventions, even if they are not assigned at random For example, build a restaurant in 1 town but not another This is the realm of Bethany Bell , she looks at food deserts and things Built a grocery store where there was a food desert and we’re told that food deserts are a problem, but it doesn’t look like things got better when we built the grocery store That’s a much stronger design than just asking people how far away do you live from a grocery store?
There’s a wonderful book called, Randomistas (like fashionistas) by Andrew Leigh
He says actually there are randomized controlled trials of parachute jumping
It’s just not true Peter asks how the IRB for that was ever approved Participants have to be in the army
This is used often as an excuse to argue, “ I can’t do the pure perfect pristine randomized control trial so therefore you have to accept any old observational study ”
David doesn’t agree
Peter asks how the IRB for that was ever approved
Participants have to be in the army
But in between that and any old observational epidemiologic study, there’s a lot of space
Co-twin controls (hinted at that earlier) use identical twins and we randomly assign each to a different group
For example, randomly assign 1 twin to exercise a lot; their twin brother doesn’t exercise, but has the same genotype That’s a tight control
How about observing interventions, even if they are not assigned at random For example, build a restaurant in 1 town but not another This is the realm of Bethany Bell , she looks at food deserts and things Built a grocery store where there was a food desert and we’re told that food deserts are a problem, but it doesn’t look like things got better when we built the grocery store That’s a much stronger design than just asking people how far away do you live from a grocery store?
That’s a tight control
For example, build a restaurant in 1 town but not another
This is the realm of Bethany Bell , she looks at food deserts and things
Built a grocery store where there was a food desert and we’re told that food deserts are a problem, but it doesn’t look like things got better when we built the grocery store That’s a much stronger design than just asking people how far away do you live from a grocery store?
That’s a much stronger design than just asking people how far away do you live from a grocery store?

Limitations of nutritional epidemiology and how it can improve [1:26:30]

Peter’s take away from this

Peter remarks that the mouse study is remarkable
One reason why Peter struggles so much with the legitimacy of epidemiology has to do with food-frequency questionnaires He simply can’t take seriously anything that relies on these questionnaires For every patient he’s ever come in contact with, to try to accurately assess what they eat based on a food frequency questionnaire is a fool’s errand These questionnaires are simply unrelated to what they eat, full stop
The second issue he has with nutritional epidemiology comes down to the hazard ratios that very commonly show up and lead to grand statements For example, a hazard ratio on the order of 1.16 being used to support a causal relationship between bacon and cancer is weak
He simply can’t take seriously anything that relies on these questionnaires
For every patient he’s ever come in contact with, to try to accurately assess what they eat based on a food frequency questionnaire is a fool’s errand These questionnaires are simply unrelated to what they eat, full stop
These questionnaires are simply unrelated to what they eat, full stop
For example, a hazard ratio on the order of 1.16 being used to support a causal relationship between bacon and cancer is weak

“ What would the actual fathers of epidemiology be saying in their graves if they were looking at these strengths of association? ” – Peter Attia

Peter’s not saying there should be no epidemiology
But there needs to be a referendum on how the media is taught how to interact with such studies and on how we scrutinize some of the methodologies behind these things For example, checking a food frequency questionnaire once in an 8-year study just doesn’t mean anything Amazingly though, this is the basis of an observation This is a problem
For example, checking a food frequency questionnaire once in an 8-year study just doesn’t mean anything
Amazingly though, this is the basis of an observation
This is a problem

David’s discussion of reforms needed

David notes that many people incorrectly perceive the problem to be a measurement issue They agree that measurement of food intakes is a big problem but think everything else is fine David’s mouse study show that when the measurement is near perfect, everything is not fine
We don’t have to go back to the fathers of epidemiology
They agree that measurement of food intakes is a big problem but think everything else is fine
David’s mouse study show that when the measurement is near perfect, everything is not fine
We can go back to at least Confucius who says, “ To know what you know and to know what you do not know, that is true knowledge ”

“ This idea that we have to be honest with ourselves and each other about what we know and don’t know and how we know it and don’t know it is clear. I think that’s part of that reform. ” – David Allison

We need a greater level of honesty
Simine Vazire just had a paper in one of the peer review journals, looking at or writing about epistemic humility and saying when you get to the discussion section of a paper and you consider that the hypothesis that you made, which now seems to be supported by your data, and you say, “ but I might be wrong ” Published in Nature Human Behavior in October 2021, Aspiring to greater intellectual humility in science It’s not honest for the discussion to systematically go through with the greatest effort and art to show how the findings are not wrong, and how all the competing explanations can be dismissed This is not an honest epistemic An honest epistemic humility would say, “ I really might be wrong, and here’s all the ways I might be wrong that I and others should test going forward ”
Michael Strevens in his book, The Knowledge Machine , does a beautiful composition, decomposition, construction, deconstruction of this, and talks about the idea of communities doing this The battle shouldn’t be ad hominem The battle shouldn’t be undercutting each other by who you are, and who you work for, and what your beliefs are He calls that the iron rule of evidence
Published in Nature Human Behavior in October 2021, Aspiring to greater intellectual humility in science
It’s not honest for the discussion to systematically go through with the greatest effort and art to show how the findings are not wrong, and how all the competing explanations can be dismissed This is not an honest epistemic
An honest epistemic humility would say, “ I really might be wrong, and here’s all the ways I might be wrong that I and others should test going forward ”
This is not an honest epistemic
The battle shouldn’t be ad hominem
The battle shouldn’t be undercutting each other by who you are, and who you work for, and what your beliefs are
He calls that the iron rule of evidence

“ It needs to be a battle about the data ” – David Allison

David doesn’t think the nutrition epidemiology field has been quite honest about the limits of its measurement Neither has its attackers
David has been careful about saying he thinks measurements of energy intake and expenditure from self-report methods are so bad that they shouldn’t even be used To say that it’s so bad, one can’t even be guaranteed to get the directional effect; so don’t even use it
But on the other hand, if the question is, do people eat vegetarian or not, or eat kosher or not, or eat after midnight or not He doesn’t know; maybe people do report this type of information accurately Maybe they don’t; he honestly doesn’t know He thinks it’s important to look at the purpose of the self-reporting questionnaire
Katherine Flegal wrote a very famous paper about the obesity wars Published in Progress in Cardiovascular Disease in 2021, The obesity wars and the education of a researcher: A personal account
David notes that her meta-analysis published in 2005 really got people’s attention Published in JAMA , Excess deaths associated with underweight, overweight, and obesity This analysis found that BMIs in the overweight range were actually not strongly associated and consistently associated with increased mortality rate In some cases were associated with lower mortality rate The media went crazy, responding as if this were a new finding The new finding that there’s a genetic component to obesity This was known decades ago The people that are the defenders of you can never be too rich or too thin went crazy and attacked her But this wasn’t new data, it was a meta-analysis In the 1950’s Linus Pauling (the double Nobel Laureate) has a paper on BMI and life expectancy; it’s got a bathtub shape curve This report was not new at all, but somehow it was seen as new People started attacking her very vociferously One investigator called it a worthless pile of rubbish David thinks these are very inappropriate statements The data are the data whether the person on the paper has a MD or not
Neither has its attackers
To say that it’s so bad, one can’t even be guaranteed to get the directional effect; so don’t even use it
He doesn’t know; maybe people do report this type of information accurately Maybe they don’t; he honestly doesn’t know
He thinks it’s important to look at the purpose of the self-reporting questionnaire
Maybe they don’t; he honestly doesn’t know
Published in Progress in Cardiovascular Disease in 2021, The obesity wars and the education of a researcher: A personal account
Published in JAMA , Excess deaths associated with underweight, overweight, and obesity
This analysis found that BMIs in the overweight range were actually not strongly associated and consistently associated with increased mortality rate In some cases were associated with lower mortality rate The media went crazy, responding as if this were a new finding
The new finding that there’s a genetic component to obesity This was known decades ago
The people that are the defenders of you can never be too rich or too thin went crazy and attacked her But this wasn’t new data, it was a meta-analysis In the 1950’s Linus Pauling (the double Nobel Laureate) has a paper on BMI and life expectancy; it’s got a bathtub shape curve
This report was not new at all, but somehow it was seen as new
People started attacking her very vociferously One investigator called it a worthless pile of rubbish David thinks these are very inappropriate statements
The data are the data whether the person on the paper has a MD or not
In some cases were associated with lower mortality rate
The media went crazy, responding as if this were a new finding
This was known decades ago
But this wasn’t new data, it was a meta-analysis
In the 1950’s Linus Pauling (the double Nobel Laureate) has a paper on BMI and life expectancy; it’s got a bathtub shape curve
One investigator called it a worthless pile of rubbish
David thinks these are very inappropriate statements

“ In science, three things matter: the data, the methods used to collect the data (which give them their probative value), and the logic which connects the data and the methods to conclusions. Everything else is not science .” – David Allison

It may be pragmatic to say, “ Oh, I trust Peter and he’s a smart guy. I know he studies a lot and he tells me I should eat this ”, but it’s not science
The science is the data, the methods, and the logic connecting the data to conclusions; not whether I trust you or not
All these Ad hominem things were said, they way they attacked her; it was very vociferous and very inappropriate But there are many other people who’ve been attacked David has been attacked
When Nina Teicholz had an editorial in Lancet, talking about some elements of nutrition, and fat, and carbohydrate, and many people wrote in trying to get it retracted This is a sort of regular occurrence now
When Brad Johnston published on red meat roughly 2 years ago, he was vigorously attacked It was a big meta-analysis showing that the association between red meat consumption and negative health outcomes was not strong and compelling Published in Annals of Internal Medicine in 2019, Red and Processed Meat Consumption and Risk for All-Cause Mortality and Cardiometabolic Outcomes: A Systematic Review and Meta-analysis of Cohort Studies People tried to get it retracted before it was published instead of just engaging with the data, the methods, and the logic Thankfully it wasn’t retracted
This sort of thing happens a lot in obesity and nutrition It happens elsewhere too; it’s terrible David thinks this is because nutrition has to do with the everyday experience All of us eat every day, almost all of us eat almost every day Food is culture; it’s family; it’s love; it’s economy; it’s commerce; it’s political beliefs; it’s philosophical beliefs It’s so connected to so many emotional things We all have that everyday experience and have to make decisions every day We make these decisions and then we may want to justify them; we may need to believe they’re good
But there are many other people who’ve been attacked
David has been attacked
This is a sort of regular occurrence now
It was a big meta-analysis showing that the association between red meat consumption and negative health outcomes was not strong and compelling
Published in Annals of Internal Medicine in 2019, Red and Processed Meat Consumption and Risk for All-Cause Mortality and Cardiometabolic Outcomes: A Systematic Review and Meta-analysis of Cohort Studies
People tried to get it retracted before it was published instead of just engaging with the data, the methods, and the logic Thankfully it wasn’t retracted
Thankfully it wasn’t retracted
It happens elsewhere too; it’s terrible
David thinks this is because nutrition has to do with the everyday experience
All of us eat every day, almost all of us eat almost every day Food is culture; it’s family; it’s love; it’s economy; it’s commerce; it’s political beliefs; it’s philosophical beliefs It’s so connected to so many emotional things We all have that everyday experience and have to make decisions every day We make these decisions and then we may want to justify them; we may need to believe they’re good
Food is culture; it’s family; it’s love; it’s economy; it’s commerce; it’s political beliefs; it’s philosophical beliefs
It’s so connected to so many emotional things
We all have that everyday experience and have to make decisions every day
We make these decisions and then we may want to justify them; we may need to believe they’re good

“ We may mistake our experience for expertise ” – David Allison

David thinks when you get into any field where people have everyday experience, people have very strong feelings and often will opine quite aggressively in the absence of data

Addressing the obesity epidemic—the path forward and obstacles to overcome [1:37:15]

Some pretty exciting pharmacologic things have come along Semaglutide (a glucagon-like peptide-1 receptor agonist) is a remarkable drug
Semaglutide (a glucagon-like peptide-1 receptor agonist) is a remarkable drug

“ It’s certainly the most impressive thing that I’ve seen clinically for obesity ” – Peter Attia

25 years ago when he was in medical school, Peter remembers the first gastric bypass he ever saw in a surgical rotation This was before they were done laparoscopically; it was done as an open roux-en-Y gastric on a 400-pound man who would die 40 days later in the hospital of sepsis He never got out of the hospital; he had an anastomotic leak That was a very dangerous operation 25 years ago
Today, that operation is done laparoscopically; it is an incredibly safe procedure, and it has also remarkable efficacy
Amazing progress has been made on the surgical front and pharmacological front
It’s not clear why progress hasn’t been made on the nutritional front
David notes that letters between President Taft (who was very obese) and his physician about diet were found recently These could have easily been letters written today A diet has not been found that reliably causes sustained weight loss
This was before they were done laparoscopically; it was done as an open roux-en-Y gastric on a 400-pound man who would die 40 days later in the hospital of sepsis
He never got out of the hospital; he had an anastomotic leak
That was a very dangerous operation 25 years ago
These could have easily been letters written today
A diet has not been found that reliably causes sustained weight loss

The big question— what diet results in sustained weight loss?

David questions the underlying premise Why should there be one diet that causes sustained weight loss? This is important to think about
There is a misperception in the field around nutrition and weight loss or food intake and weight loss That there is a good diet with respect to weight loss, such that for most people, if they just ate the right way, they wouldn’t have to count calories They wouldn’t have to be uncomfortable and hungry They wouldn’t have to feel deprived and yet would maintain a good, healthy weight David has no reason to believe that’s true
Lots of people argue it is diet A or diet B This one thinks it’s low carb and that one thinks it’s high or low fat This one thinks it’s don’t eat at night This one thinks it’s whatever it is, eat paleo, et cetera
Why should there be one diet that causes sustained weight loss?
This is important to think about
That there is a good diet with respect to weight loss, such that for most people, if they just ate the right way, they wouldn’t have to count calories
They wouldn’t have to be uncomfortable and hungry
They wouldn’t have to feel deprived and yet would maintain a good, healthy weight
David has no reason to believe that’s true
This one thinks it’s low carb and that one thinks it’s high or low fat
This one thinks it’s don’t eat at night
This one thinks it’s whatever it is, eat paleo, et cetera

“ Maybe the null hypothesis is, it doesn’t matter that much ” – David Allison

There isn’t such a diet for many people
Now, for some people, they do maintain a normal, healthy, desirable weight without trying to restrict their energy, but maybe for others, it’s just not the case
David thinks the paths forward are manifold

“ I think in some cases we are on the good path and in some cases, we are wandering in the drunkards walk ” – David Allison

Where we are making good progress

We’re on the good path I think on surgery and pharmaceuticals There is clearly a long way to go, but they’ve gotten much better David would love to see more funding for good research
We need to get on a much better path as a society making obesity treatments available to people If you have cancer, we’re willing to treat you If you have obesity, maybe not If you’re rich, you can pay for that If you’re not rich, what do you do?
We’re on a good path on stigma, but there’s a long way to go As a society, we’ve woken up to say stigmatizing obese people is not okay Shaming people about their body habit is not okay
Sometimes the counterargument is, “ But it’s good for them because it’ll help them want to lose weight .”
And sometimes the argument made against the shaming is empirical The evidence shows that people who experienced a lot of weight shaming gain more weight Then the causal thing is thrown in, so therefore, you shouldn’t do it It’s a moral issue; it’s not an empirical issue
We know so much more about genes, and physiology, and metabolism, and cells with respect to obesity and nutrition than we knew 20, 30, 40 years ago
There is clearly a long way to go, but they’ve gotten much better
David would love to see more funding for good research
If you have cancer, we’re willing to treat you
If you have obesity, maybe not If you’re rich, you can pay for that If you’re not rich, what do you do?
If you’re rich, you can pay for that
If you’re not rich, what do you do?
As a society, we’ve woken up to say stigmatizing obese people is not okay
Shaming people about their body habit is not okay
The evidence shows that people who experienced a lot of weight shaming gain more weight
Then the causal thing is thrown in, so therefore, you shouldn’t do it
It’s a moral issue; it’s not an empirical issue

Where we are not making progress

The one area where we are not making progress, and we aren’t yet on a good path, is with this public health community, school based, community based, policy based approach

“ I think we are continuing to look for our keys under the lampposts because that’s where the light is as opposed to where the keys might be ” – David Allison

We continue to ignore the data
We keep saying the same old suggestions that people have been trying for decades And that when you really look at the data, these have at best not been shown to work, and at worst been shown to not work There are some people who have patently obfuscating those data
The cluster randomized trials we see in the childhood obesity literature bring to mind the phrase that rhymes with cluster muck This is distorted evidence, this is science gone wrong in the worst sens
We’ve got to clean up the quality of the science we do
We’ve got to start treating this like science Just as much as the science of quirks, or tires on automobiles, or beta cells of pancreases Treat it like real science and take it just as seriously
And that when you really look at the data, these have at best not been shown to work, and at worst been shown to not work
There are some people who have patently obfuscating those data
This is distorted evidence, this is science gone wrong in the worst sens
Just as much as the science of quirks, or tires on automobiles, or beta cells of pancreases
Treat it like real science and take it just as seriously

The cluster randomization problem

A cluster randomized trial is a trial which instead of randomizing the individual unit of observation (one person), entire intact units are assigned to one treatment or another An individual might be a child in a school who you either assigned to the treatment group, maybe it’s exercise, or the control group, no special exercise An entire intact unit might be a classroom, or a school, or a neighborhood, or a family
There’s nothing wrong with randomizing a unit of people as long as there are at least 2 clusters assigned to each condition This allows some ability to observe variants Although frankly, with only 2 there is so little power and robustness; for practical purposes, that would be invalid, but theoretically it’s valid
Then one must analyze the data to take into account both what’s called the clustering and the nesting The clustering is that you have people grouped and that grouping leads to more similar individuals So imagine that we did a trial and the trial was you and your brother randomly assigned to eat low carb, and me and my brother randomly assigned to eat high carb; and at the end we see a difference by an ordinary t-test One question that arises— was that the effect of diet or is it that the Attia brothers are different from the Allison brothers? This has to be taken into account, so you need more than 1 cluster So if you get the Attia brothers, and the Jones brothers, and the Allison brothers, and the Smith brothers, now, in theory, you can do it But now you can’t treat us like we’re 8 different people; what you really have is 4 different clusters, 4 different sets of brothers This must be taken into account and it results in less degrees of freedom People don’t do that reliably and they don’t do it correctly often, and that leads to many papers being wrong David has written countless letters to editors about this
There have probably been at least 3 or 4 cluster randomized trials retracted as a result of letters he’s written People have had to come back and just say, “ The results don’t hold up ”
But until this has changed, we have people out there who understandably say, “ But I read these papers suggesting that this works. Gardening in schools makes kids thinner .”
An individual might be a child in a school who you either assigned to the treatment group, maybe it’s exercise, or the control group, no special exercise
An entire intact unit might be a classroom, or a school, or a neighborhood, or a family
This allows some ability to observe variants
Although frankly, with only 2 there is so little power and robustness; for practical purposes, that would be invalid, but theoretically it’s valid
The clustering is that you have people grouped and that grouping leads to more similar individuals So imagine that we did a trial and the trial was you and your brother randomly assigned to eat low carb, and me and my brother randomly assigned to eat high carb; and at the end we see a difference by an ordinary t-test One question that arises— was that the effect of diet or is it that the Attia brothers are different from the Allison brothers? This has to be taken into account, so you need more than 1 cluster So if you get the Attia brothers, and the Jones brothers, and the Allison brothers, and the Smith brothers, now, in theory, you can do it
But now you can’t treat us like we’re 8 different people; what you really have is 4 different clusters, 4 different sets of brothers
This must be taken into account and it results in less degrees of freedom People don’t do that reliably and they don’t do it correctly often, and that leads to many papers being wrong David has written countless letters to editors about this
So imagine that we did a trial and the trial was you and your brother randomly assigned to eat low carb, and me and my brother randomly assigned to eat high carb; and at the end we see a difference by an ordinary t-test
One question that arises— was that the effect of diet or is it that the Attia brothers are different from the Allison brothers?
This has to be taken into account, so you need more than 1 cluster
So if you get the Attia brothers, and the Jones brothers, and the Allison brothers, and the Smith brothers, now, in theory, you can do it
People don’t do that reliably and they don’t do it correctly often, and that leads to many papers being wrong
David has written countless letters to editors about this
People have had to come back and just say, “ The results don’t hold up ”

“ That’s not what the results showed, but that’s what the paper says ” – David Allison

And until we become more rigorous and more honest, we’re not on the right path

What David believes to be the most promising interventions we could take to address obesity and improve public health [1:47:30]

Peter asks David what intervention (or set of interventions) could improve public health outcomes

What would he test first? ⇒ General education , not nutrition education, general education There are provocative data strongly suggesting that general education, especially for girls and women, leads to lower BMIs, lesser rates of obesity, and lesser diabetes than less education Some studies in Europe of policies where someone puts in a policy and it effectively gives a cohort of people more education show this results in that cohort, less obesity, especially among women There’s a famous study by the Ramey’s, who are a husband and wife investigative team ( Craig Ramey and Sharon Landesman Ramey ) They worked at UAB when David first got there, They started a study decades ago at UNC , it was head start on steroids They called it the Abecedarian study They gave these kids the super head start program; it was mostly just general education, there may have been a little nutrition education It wasn’t a weight loss study 30 years later they followed-up on the participants There’s a paper in Science on this; the women have less obesity Published in 2014, Early Childhood Investments Substantially Boost Adult Health The Moving to Opportunity Study funded by The Department of Housing and Urban Development took families who lived in so-called poor neighborhoods, and they randomly assigned them either 1) To a control group, where they basically got nothing 2) Or to a group where they received housing vouchers; but the housing vouchers required that they moved to less poor neighborhoods What they found years later in follow up is that there was less obesity and diabetes in those assigned to move to the less poor neighborhoods and given the financial wherewithal to do so Published in the New England Journal of Medicine in 2011, Neighborhoods, Obesity, and Diabetes — A Randomized Social Experiment Published in Science in 2012, Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults These studies suggest that general education may help
This speaks to this whole socioeconomic thing we started about way earlier— what is it about higher socioeconomic status that at least in some groups (not all, but at least in white women) seems to be associated with less obesity? David doesn’t know what the causal mechanisms are
So if somebody said to him, “ You’re going to be the king for a year, and you’ve got the federal budget, and you can take this big chunk of money, and you can make an impact on obesity and diabetes .”
He would choose to divide it into 4 pots 1) One pot is going to be surgery, and it’s going to be both providing it and continuing to study it 2) The next one’s going to be pharmaceuticals, both providing it and continuing to study it 3) The third pot is going to be some general education, maybe general wellbeing, safety, security, starting in early childhood to see whether that alone is enough Reducing disparities back to Confucius ; Confucius said, “ We are not so concerned with an absence of wealth, we are concerned with a disparity of wealth .” It may be that reducing disparities is really important 4) And then the fourth pot would be basic research, basic science questions Look at senolytics , and look at microchimerism , and all the things that you talk about so often in your podcast, but against both metabolism, and obesity, and nutrition, but also the fundamentalist in essence David wonders if we use microchimerism (or sanalytics) to restore people to younger metabolic states?
There are provocative data strongly suggesting that general education, especially for girls and women, leads to lower BMIs, lesser rates of obesity, and lesser diabetes than less education
Some studies in Europe of policies where someone puts in a policy and it effectively gives a cohort of people more education show this results in that cohort, less obesity, especially among women
There’s a famous study by the Ramey’s, who are a husband and wife investigative team ( Craig Ramey and Sharon Landesman Ramey ) They worked at UAB when David first got there, They started a study decades ago at UNC , it was head start on steroids They called it the Abecedarian study They gave these kids the super head start program; it was mostly just general education, there may have been a little nutrition education It wasn’t a weight loss study 30 years later they followed-up on the participants There’s a paper in Science on this; the women have less obesity Published in 2014, Early Childhood Investments Substantially Boost Adult Health
The Moving to Opportunity Study funded by The Department of Housing and Urban Development took families who lived in so-called poor neighborhoods, and they randomly assigned them either 1) To a control group, where they basically got nothing 2) Or to a group where they received housing vouchers; but the housing vouchers required that they moved to less poor neighborhoods What they found years later in follow up is that there was less obesity and diabetes in those assigned to move to the less poor neighborhoods and given the financial wherewithal to do so Published in the New England Journal of Medicine in 2011, Neighborhoods, Obesity, and Diabetes — A Randomized Social Experiment Published in Science in 2012, Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults These studies suggest that general education may help
They worked at UAB when David first got there,
They started a study decades ago at UNC , it was head start on steroids
They called it the Abecedarian study
They gave these kids the super head start program; it was mostly just general education, there may have been a little nutrition education
It wasn’t a weight loss study
30 years later they followed-up on the participants
There’s a paper in Science on this; the women have less obesity
Published in 2014, Early Childhood Investments Substantially Boost Adult Health
1) To a control group, where they basically got nothing
2) Or to a group where they received housing vouchers; but the housing vouchers required that they moved to less poor neighborhoods
What they found years later in follow up is that there was less obesity and diabetes in those assigned to move to the less poor neighborhoods and given the financial wherewithal to do so
Published in the New England Journal of Medicine in 2011, Neighborhoods, Obesity, and Diabetes — A Randomized Social Experiment
Published in Science in 2012, Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults
These studies suggest that general education may help
David doesn’t know what the causal mechanisms are
1) One pot is going to be surgery, and it’s going to be both providing it and continuing to study it
2) The next one’s going to be pharmaceuticals, both providing it and continuing to study it
3) The third pot is going to be some general education, maybe general wellbeing, safety, security, starting in early childhood to see whether that alone is enough Reducing disparities back to Confucius ; Confucius said, “ We are not so concerned with an absence of wealth, we are concerned with a disparity of wealth .” It may be that reducing disparities is really important
4) And then the fourth pot would be basic research, basic science questions Look at senolytics , and look at microchimerism , and all the things that you talk about so often in your podcast, but against both metabolism, and obesity, and nutrition, but also the fundamentalist in essence David wonders if we use microchimerism (or sanalytics) to restore people to younger metabolic states?
Reducing disparities back to Confucius ; Confucius said, “ We are not so concerned with an absence of wealth, we are concerned with a disparity of wealth .”
It may be that reducing disparities is really important
Look at senolytics , and look at microchimerism , and all the things that you talk about so often in your podcast, but against both metabolism, and obesity, and nutrition, but also the fundamentalist in essence
David wonders if we use microchimerism (or sanalytics) to restore people to younger metabolic states?

Reproducibility in science, normative and non-normative errors explained [1:51:30]

David was on a panel set up by the National Academy of Science, Engineering, and Medicine; they looked at the question of reproducibility in science Reproducibility and Replicability in Science
The phrase that Harvey Feinberg (who was the chair of the panel) started using is— “ no crisis but no cause for complacency ” The idea is that we must make things better
There might be some things that are getting worse, but on average, there’s a lot of evidence that things are getting better
David finds that science is better and more rigorous than it’s ever been in history
But we also see all the flaws and science must get better This is why Marcia McNutt (the President of the National Academy of Sciences) instantiated this new strategic council on trust and integrity and rigor in science and very generously appointed me as one of the 3 co-chairs. Many other organizations are also trying to help on this too
Peter asks how much of this situation is intrinsic to science itself and how much is a result of the media’s interface with science
David thinks both are important Michael Strevens book, mentioned earlier, ( The Knowledge Machine ) does a wonderful job explaining how hard science is
We have to make the distinction between normative errors and non-normative errors
Reproducibility and Replicability in Science
The idea is that we must make things better
This is why Marcia McNutt (the President of the National Academy of Sciences) instantiated this new strategic council on trust and integrity and rigor in science and very generously appointed me as one of the 3 co-chairs.
Many other organizations are also trying to help on this too
Michael Strevens book, mentioned earlier, ( The Knowledge Machine ) does a wonderful job explaining how hard science is

Normative errors

Normative errors occur because of limitations in instruments/ technology used to study a phenomenon
Consider 2 examples: 1) A few hundred years ago Galileo was under house arrest, and from his house Galileo directs a study He has two colleagues go out to 2 tops of mounds, or hills, or mountains far apart, each holding a lantern with shutters and a synchronized watch or timepiece He direct them at a predetermined moment to open their shutters and record when they see the other guy’s light He wants to figure out whether light travels instantaneously or not They conclude that light travels instantaneously because they can’t discern any time delay Today we know that’s wrong But with their instrumentation they couldn’t have done better; this is a normative error Galileo didn’t do anything wrong; it’s great question and great way of working on it 2) Similarly, when Linus Pauling says DNA is a triple helix before Watson and Crick show it’s a double hex Pauling didn’t have good x-ray crystallography data, he’s working at the edge; this is a normative error
1) A few hundred years ago Galileo was under house arrest, and from his house Galileo directs a study
He has two colleagues go out to 2 tops of mounds, or hills, or mountains far apart, each holding a lantern with shutters and a synchronized watch or timepiece
He direct them at a predetermined moment to open their shutters and record when they see the other guy’s light He wants to figure out whether light travels instantaneously or not
They conclude that light travels instantaneously because they can’t discern any time delay Today we know that’s wrong But with their instrumentation they couldn’t have done better; this is a normative error Galileo didn’t do anything wrong; it’s great question and great way of working on it
2) Similarly, when Linus Pauling says DNA is a triple helix before Watson and Crick show it’s a double hex
Pauling didn’t have good x-ray crystallography data, he’s working at the edge; this is a normative error
He wants to figure out whether light travels instantaneously or not
Today we know that’s wrong
But with their instrumentation they couldn’t have done better; this is a normative error
Galileo didn’t do anything wrong; it’s great question and great way of working on it

Non-normative errors

A very famous non-normative error is people working to determine the size of the thymus gland in children They used cadavers in the early 20th century Poor people tend to become cadavers, poor children tend to be undernourished Undernourished children tend to have smaller thymus glands
So when physicians started seeing richer children dying of sudden infant death syndrome, and they examined them, they thought, “ That’s a big thymus gland ” Well, it was actually a normal thymus gland because their norms were determined from undernourished kids The doctors then proceeded to irradiate these kids with big thymus glands to prevent sudden infant death syndrome This probably caused lots of cases of thyroid cancer because the thyroid and the thymus us are very close to each other This is an example of a non-normative error because even 100 years ago, any epidemiologist or statistician could have told you that is bad sampling and bad inference from bad sampling
They used cadavers in the early 20th century Poor people tend to become cadavers, poor children tend to be undernourished Undernourished children tend to have smaller thymus glands
Poor people tend to become cadavers, poor children tend to be undernourished
Undernourished children tend to have smaller thymus glands
Well, it was actually a normal thymus gland because their norms were determined from undernourished kids
The doctors then proceeded to irradiate these kids with big thymus glands to prevent sudden infant death syndrome This probably caused lots of cases of thyroid cancer because the thyroid and the thymus us are very close to each other
This is an example of a non-normative error because even 100 years ago, any epidemiologist or statistician could have told you that is bad sampling and bad inference from bad sampling
This probably caused lots of cases of thyroid cancer because the thyroid and the thymus us are very close to each other

Current examples of non-normative errors

The distinction between normative and non-normative errors needs to be made
A lot of the errors in nutrition epidemiology today cannot be called normative errors anymore, these are non-normative
The misanalysis of the cluster randomized trials, these are not normative Any statistician knows how to do it People are either obfuscating or they’re just woefully ignorant and not using professional statisticians when they need to
People are using food frequency questionnaires to draw causal inference about some of these things we have discussed, these are not normative errors, people should know better
Then there’s the stuff about the more general public about believing things and how we promote our ideas This is where the scientific community needs to take responsibility
Any statistician knows how to do it
People are either obfuscating or they’re just woefully ignorant and not using professional statisticians when they need to
This is where the scientific community needs to take responsibility

Rebuilding trust in science and differentiating between science and advocacy [1:59:00]

“ I think we need to be prepared to lose some battles in order to win the intellectual war ” – David Allison

This means we need to be prepared to not use all the rhetorical tools at our disposal at any one point in time to convince somebody that X is true Even when we’re really worked up and think it’s important we believe X is true Even when we think it’s important that others believe X is true because we want them to eat what we think is good Or we want them to eat more broccoli and less ice cream, we want them to take their vaccine, wear their mask, wear their seatbelt, stop smoking We may be right about all those things, but if we use rhetorical devices, the we may win that battle may lose the war in helping people think though what good evidence is and elevating our level of dialogue Rhetorical devices such as if you and I are debating and I attack you on that homonym grounds, or I exaggerate the strength of my evidence, or I don’t honestly say that I’ve shown an association and not causation Compare this to what a late night comedian would’ve said 30 years ago in making jokes about wives, and husbands, and race, and sex That would never be considered acceptable today We are able to change societal norms about dialogue
There is a need to elevate our societal norms of dialogue on epistemological and empirical issues So that ordinary people can say, “ Oh, you’re telling me you have a treatment for X. Was there a study? Was the study in humans? Was it a randomized study? Was it a study of the actual outcome you’re making a claim about? Was it a study that was long enough for this to be a meaningful outcome? Was there a statistically significant result? Was the result big enough to matter? Was the dose a dose I might realistically take? ” Those are not all that difficult questions to train ourselves and each other to reliably ask And if we just reliably ask those and reliably and honestly answer them, this can take us a long way
Peter agrees and thinks of discussions about COVID COVID has been such a polarizing scientific phenomenon in a way that he’s become quite frustrated in watching it COVID has accelerated the loss of the public’s faith in science Well-meaning public health officials have simply failed to communicate the nuance of science and lost so much credibility
Even when we’re really worked up and think it’s important we believe X is true
Even when we think it’s important that others believe X is true because we want them to eat what we think is good Or we want them to eat more broccoli and less ice cream, we want them to take their vaccine, wear their mask, wear their seatbelt, stop smoking
We may be right about all those things, but if we use rhetorical devices, the we may win that battle may lose the war in helping people think though what good evidence is and elevating our level of dialogue Rhetorical devices such as if you and I are debating and I attack you on that homonym grounds, or I exaggerate the strength of my evidence, or I don’t honestly say that I’ve shown an association and not causation
Compare this to what a late night comedian would’ve said 30 years ago in making jokes about wives, and husbands, and race, and sex That would never be considered acceptable today
We are able to change societal norms about dialogue
Or we want them to eat more broccoli and less ice cream, we want them to take their vaccine, wear their mask, wear their seatbelt, stop smoking
Rhetorical devices such as if you and I are debating and I attack you on that homonym grounds, or I exaggerate the strength of my evidence, or I don’t honestly say that I’ve shown an association and not causation
That would never be considered acceptable today
So that ordinary people can say, “ Oh, you’re telling me you have a treatment for X. Was there a study? Was the study in humans? Was it a randomized study? Was it a study of the actual outcome you’re making a claim about? Was it a study that was long enough for this to be a meaningful outcome? Was there a statistically significant result? Was the result big enough to matter? Was the dose a dose I might realistically take? ” Those are not all that difficult questions to train ourselves and each other to reliably ask And if we just reliably ask those and reliably and honestly answer them, this can take us a long way
Those are not all that difficult questions to train ourselves and each other to reliably ask
And if we just reliably ask those and reliably and honestly answer them, this can take us a long way
COVID has been such a polarizing scientific phenomenon in a way that he’s become quite frustrated in watching it
COVID has accelerated the loss of the public’s faith in science
Well-meaning public health officials have simply failed to communicate the nuance of science and lost so much credibility

The difference between science and advocacy

David reflects that part of the problem is the lack of clarity on the identity of whose speaking
We need to be clear when we are speaking as scientists versus advocates Scientists must not compromise the truth The standard is not so high for an advocate
Scientists can advocate but need to make it clear by saying “ I’m not being a scientist right now, I’m just telling you what I want you to do. And I’m going to say whatever I need to say to convince you ”
Scientists must not compromise the truth
The standard is not so high for an advocate

Trust

Another important component is trust
David hears a lot that trust in science has been really weighed down in the last few years He doesn’t think it is true It depends what you mean by science If what you mean is science as a process of developing and finding knowledge, he knows of no evidence that it’s down If what you mean by science is trust in individual elements of the scientific community then he’s not sure it’s down either, but it’s spread around Some people think Fauci is trustworthy and some people think Gwyneth Paltro is trustworthy Some people think David Allison is and some people think Peter Attia is; and some people think we’re corrupt, and ignorant, and confused, and terrible
The challenge is that there are people who cannot distinguish between the statements of a Tony Fauci and the extent to which they are or are not backed by evidence , and the statements of a John Ioannidis and the extent to which they are or not backed, versus the statements of a Gweneth Paltro or somebody else That’s the challenge
He doesn’t think it is true
It depends what you mean by science
If what you mean is science as a process of developing and finding knowledge, he knows of no evidence that it’s down
If what you mean by science is trust in individual elements of the scientific community then he’s not sure it’s down either, but it’s spread around Some people think Fauci is trustworthy and some people think Gwyneth Paltro is trustworthy Some people think David Allison is and some people think Peter Attia is; and some people think we’re corrupt, and ignorant, and confused, and terrible
Some people think Fauci is trustworthy and some people think Gwyneth Paltro is trustworthy
Some people think David Allison is and some people think Peter Attia is; and some people think we’re corrupt, and ignorant, and confused, and terrible
That’s the challenge

“ It’s not that people don’t trust science, it’s that people don’t know which voice to trust as a communicator of the science and therefore they don’t trust individual elements of the canon of science. ” – David Allison

This can be seen in nutrition There’s a nice summary on the Pew Charitable Trust website now indicating that trust in science is high, trust in dieticians is high, trust in medical doctors who talk about nutrition in treating their patients is high But trust in nutrition scientists is low compared to dieticians and medical doctors who talk about nutrition, and compared to other scientists
So in nutrition we have met the enemy and it is us We have shot ourselves in the credibility foot with our obfuscation, and our exaggeration, and our hype David thinks that pocket of trust is gone even though trust in science overall has not down
Peter really likes this point; the difference between science and advocacy can’t be overstated It would be amazing if people, himself included, had the self-awareness to speak and know which hat we were wearing Think about the problems that could be solved if people always had to have a hat on; they couldn’t blind the listener to which hat they were wearing The scientist hat — focused on the nuanced hard truth, as messy as it might be, as unclear as it might be, with no regard for how a person feels when they hear it and what action they may or may not take as a result of it This is different from the advocacy hat — saying, “I want to change your behavior because I think it’s in your best interest .” We can come up with a two hat system and everybody gets to own two hats
There’s a nice summary on the Pew Charitable Trust website now indicating that trust in science is high, trust in dieticians is high, trust in medical doctors who talk about nutrition in treating their patients is high
But trust in nutrition scientists is low compared to dieticians and medical doctors who talk about nutrition, and compared to other scientists
We have shot ourselves in the credibility foot with our obfuscation, and our exaggeration, and our hype
David thinks that pocket of trust is gone even though trust in science overall has not down
It would be amazing if people, himself included, had the self-awareness to speak and know which hat we were wearing
Think about the problems that could be solved if people always had to have a hat on; they couldn’t blind the listener to which hat they were wearing
The scientist hat — focused on the nuanced hard truth, as messy as it might be, as unclear as it might be, with no regard for how a person feels when they hear it and what action they may or may not take as a result of it
This is different from the advocacy hat — saying, “I want to change your behavior because I think it’s in your best interest .”
We can come up with a two hat system and everybody gets to own two hats

Selected Links / Related Material

Concordance of BMI in monozygotic twins : The heritability of body mass index among an international sample of monozygotic twins reared apart | International Journal of Obesity and Related Metabolic Disorders (D B Alison et al. 1996) | [20:30]

Swedish obesity study from Lars Sjostrom in Sweden : Lifestyle, Diabetes, and Cardiovascular Risk Factors 10 Years after Bariatric Surgery | New England Journal of Medicine (L Sjöström et al. 2004) | [20:45]

Stunkard’s key publications on the genetics of obesity :

Published in 1986, An Adoption Study of Human Obesity | The New England Journal of Medicine (AJ Stunkard et al . 1986) | [22:45]
Published in 1990, The Body-Mass Index of Twins Who Have Been Reared Apart | | The New England Journal of Medicine (AJ Stunkard et al. 1990) | [22:45]

Doug Childers’ and David Allison’s publication on the ‘Obesity Paradox’ : The ‘Obesity Paradox:’ a parsimonious explanation for relations among obesity, mortality rate, and aging? | International Journal of Obesity (DK Childers and DB Allison 2010) | [38:15]

JoAnn Manson’s paper on excluding smokers from BMI mortality analysis : Body Weight and Longevity: A Reassessment | JAMA (JE Manson et al. 1987) | [45:00]

Women’s energy needs during pregnancy : Daily energy expenditure through the human life course | Science (H Pontzer et al. 2021) | [1:07:45]

Book claiming randomized controlled trials of parachute jumping : Randomistas: How Radical Researchers Are Changing Our World by Andrew Leigh (2018) | [1:24:45]

Mouse study found mice who chose to eat more lived longer : Observational Research Rigor Alone Does Not Justify Causal Inference | European Journal of Clinical Investigation (K Ejima et al. 2016) | [1:22:15]

Simine Vazire calls for epistemic humility in the discussion section of papers : Aspiring to greater intellectual humility in science | Nature Human Behavior (R Hoekstra and S Vazire 2021) | [1:29:00]

Strevens book calls for epistemic humility and a focus on data : The Knowledge Machine: How Irrationality Created Modern Science by Michael Strevens (2020) | [1:29:45]

Katherine Flegal’s papers about the obesity wars :

The obesity wars and the education of a researcher: A personal account | Progress in Cardiovascular Disease (KM Flegal 2021) | [1:31:15]
Excess deaths associated with underweight, overweight, and obesity | JAMA (KM Flegal et al. 2005) | [1:31:30]

Nina Teicholz’s editorial in Lancet : Response to critique of review of The Big Fat Surprise | Lancet (N Teicholz 2019) | [1:34:45]

Brad Johnston’s meta-analysis challenges the association between red meat consumption and negative health outcomes : Red and Processed Meat Consumption and Risk for All-Cause Mortality and Cardiometabolic Outcomes: A Systematic Review and Meta-analysis of Cohort Studies | Annals of Internal Medicine (D Zeraatkar et al. 2019) | [1:35:00]

Children who completed the early education (Abecedarian program) had better health outcomes 30 years later : Early Childhood Investments Substantially Boost Adult Health | Science (F Campbell et al. 2014) | [1:49:00]

The Moving to Opportunity Study showed moving to a less poor neighborhood was associated with improved health outcomes :

Neighborhoods, Obesity, and Diabetes — A Randomized Social Experiment | New England Journal of Medicine (J Ludwig et al. 2011) | [1:49:00]
Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults | Science (J Ludwig et al 2012) | [1:49:00]

Findings by the Pew Charitable Trust, trust in dieticians and doctors is high but trust in nutrition scientists is low : Findings at a glance: Nutrition research scientists | Pew Research Center (August 2, 2019) | [2:08:30]

A few of David’s publications on how to improve research :

Reproducibility: A tragedy of errors | Nature (DB Allison et al. 2016)
Childhood Obesity Intervention Studies: A Narrative Review and Guide for Investigators, Authors, Editors, Reviewers, Journalists, and Readers to Guard Against Exaggerated Effectiveness Claims | Obesity Reviews (AW Brown et al. 2019)
Toward more rigorous and informative nutritional epidemiology: The rational space between dismissal and defense of the status quo | Critical Reviews in Food Science and Nutrition (AW Brown et al. 2021)

People Mentioned

Donald Rubin (friend and Emeritus Professor of Statistics at Harvard University) [6:45]
Stanley Schacter () [10:30]
Kelly Brownell (Duke University clinical psychologist who studies obesity) [15:00]
Thomas (Tom) Wadden (University of Pennsylvania psychologist who studies obesity) [15:00]
Albert (Mickey) Stunkard (University of Pennsylvania psychiatrist who described binge eating) [15:00, 22:45, 55:15]
Charles Davenport (biologist and eugenist in the early 12900’s) [22:30]
William Stewart Agras (Stanford psychiatrist who studied binge eating and behavioral therapy) [25:15]
George Bray (Louisiana State professor who studies obesity and metabolism) [27:30]
Lars Sjostrom (Swedish doctor who studied bariatric surgery) [30:45]
Pierre Bjorn Thorpe (senior mentor of Lars Sjostrom) [31:30]
John Hunter (distinguished Scottish surgeon in the late 1700’s) [33:00]
Edward Jenner (British physician and scientist who developed the smallpox vaccine) [33:00]
Joann Manson (Harvard physician best known for work on preventing chronic disease in women) [45:00]
Katherine Flegal (CDC epidemiologist who studies obesity) [18:15, 1:31:00]
Donald (Don) Rubin (Harvard statistician who developed the Rubin Causal Model ) [49:45]
Adolph Quetelet (developed BMI) [50:45]
Ancel Keys (physiologist who studied influence of diet on health) [51:45]
Steven Heymsfield (David’s mentor at the New York Obesity Research Center) [59:45]
Olivia Affuso (obesity and nutrition scientist who worked with David at the New York Obesity Research Center) [1:00:15]
James Neel (geneticist known for the thrifty gene hypothesis ) [1:06:30]
Robert Fogel (Nobel Prize winning economic historian and scientist) [1:07:15]
John Speakman (British biologist working at the University of Aberdeen studies energy expenditure in animals) [1:07:45, 1:15:00]
Richard Dawkins (evolutionary biologist, Professor at New College, Oxford) [1:11:00]
Hermann Joseph Muller (geneticist) [1:14:00]
James V. Neel (geneticist, developed the thrifty gene hypothesis) [1:14:15]
Gary Beauchamp (expert in chemosensory science and former director of the Monell Chemical Census Center ) [1:15:00]
John Ioannidis (Stanford professor of epidemiology, proponent of evidence-based research) [1:18:00, 2:08:00]
Gary Taubes (science writer and author of many books on nutrition) [1:18:15]
Nina Teicholz (journalist and author who has focused on nutrition) [1:18:15]
Roy Wallford (UCLA pathologist, a proponent of calorie restriction) [01:23:00]
Richard Weindruch (University of Wisconsin-Madison professor of medicine, a a proponent of calorie restriction) [01:23:00]
Andrew Leigh (former professor of economics, Australian politician, author) [1:24:45]
Bethany Bell (Studies food deserts, Professor of Social Work at the University of South Carolina) [1:26:00]
Confucius (Chinese philosopher from the late 16th century) [1:28:30, 1:50:45, 2:11:15]
Simine Vazire Professor of Psychology Ethics and Wellbeing at the University of Melbourne [1:29:00]
Michael Strevens (author of The Knowledge Machine: How Irrationality Created Modern Science ) [1:29:30, 1:55:00]
Katherine Flegal (epidemiologist at the CDC who studies obesity) [1:31:00]
Linus Pauling (biochemist in the early-mid 1900’s, double Nobel Laureate) [1:32:30]
Nina Teicholz (journalist and author of The Big Fat Surprise ) [1:34:45]
Bradley Johnston (Professor of Nutrition at Texas A&M University) [1:35:00]
Craig and Sharon Landesman Ramey (husband-wife investigative team at UNC then UAB who studied early education) [1:48:30]
Harvey Feinberg (Chair of the National Academy panel on reproducibility and replicability in science) [1:52:00]
Marcia McNutt (the President of the National Academy of Sciences) [1:54:15]
Galileo Galilei (16th-17th century astronomer) [1:55:30]
Linus Pauling (20th century biochemist) [1:56:45]
Watson and Crick (20th century molecular biologists) [1:56:45]
Anthony Fauci (director of NIAD and chief medical advisor to the president) [2:07:45]
Gwyneth Paltro (actress) [2:07:45]
David Allison (obesity researcher and Dean of The Indiana University School of Public Health-Bloomington) [2:07:45]
Peter Attia (physician focused on applying science to longevity) [2:07:45]

David B. Allison received his Ph.D. from Hofstra University in 1990. He then completed a post-doctoral fellowship at the Johns Hopkins University School of Medicine and a second post-doctoral fellowship at the NIH-funded New York Obesity Research Center at St. Luke’s/Roosevelt Hospital Center. He was a research scientist at the NY Obesity Research Center and Associate Professor of Medical Psychology in Psychiatry at Columbia University College of Physicians & Surgeons until 2001. He became Dean and Provost Professor at the Indiana University School of Public Health-Bloomington in 2017. Prior he was Distinguished Professor, Quetelet Endowed Professor, and Director of the NIH-funded Nutrition Obesity Research Center (NORC) at the University of Alabama at Birmingham.

He has authored more than 600 scientific publications and received many awards, including the 2002 Lilly Scientific Achievement Award from The Obesity Society (TOS); the 2002 Andre Mayer Award from the International Association for the Study of Obesity (IASO); the National Science Foundation–administered 2006 Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM); and the 2018 Harry V. Roberts Statistical Advocate of the Year Award from the American Statistical Association. In 2009, he was awarded the Centrum Award from the American Society of Nutrition (ASN) and the TOPS research achievement award from the Obesity Society. In 2013, he was awarded the Alabama Academy of Science’s Wright A. Gardner award and the American Society of Nutrition’s (ASN) Dannon Institute Mentorship award. He was elected as a Fellow of the American Statistical Association (ASA) in 2007, the American Psychological Association (APA) in 2008, the American Association for the Advancement of Science (AAAS) in 2009, the NY Academy of Medicine in 2014, the Gerontological Society of America in 2014, the Academy of Behavioral Medicine Research in 2017, and inducted into the Johns Hopkins Society of Scholars in 2013. In 2012, he received an NIH Director’s Transformative Research Award entitled “Energetics, Disparities, & Lifespan: A unified hypothesis.” In 2020, he was awarded the American Statistical Association’s San Antonio Chapter 2020 Don Owen Award in recognition of excellence in research, statistical consultation, and service to the statistical community. In 2021, he received the Obesity Society’s Friends of Albert (Mickey) Stunkard Lifetime Achievement Award.

In 2012 he was elected to the National Academy of Medicine of the National Academies. In addition to co-chairing their Strategic Council for Research Excellence, Integrity, and Trust (with Marcia McNutt and France Córdova), he was selected for their ad hoc committee to develop methods for assessing misinformation about biological threats. He has also served on the Scientific Advisory Board for the Nutrition Science Initiative (NuSI) and served on the board-appointed Committee on Science and Technology Engagement with the Public (CoSTEP) for the American Association for the Advancement of Science (AAAS), 2014–2020.

He has contributed to many editorial boards and is currently an associate editor or statistical editor for Obesity ; International Journal of Obesity ; Nutrition Today ; Obesity Reviews ; Public Library of Science (PLOS) Genetics ; Surgery for Obesity and Related Diseases (SOARD) , and American Journal of Clinical Nutrition. Dr. Allison is also proud to be the founding Field Chief Editor of Frontiers in Genetics . His research interests include obesity and nutrition, quantitative genetics, clinical trials, statistical and research methodology, and research rigor and integrity. [ Indiana University Bloomington School of Public Health ]

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