Reminder: scientists’ attitudes affect what they investigate

You may have seen the headline that a new species of praying mantis was discovered, and named after Ruth Bader Ginsburg. Here’s what I consider the really interesting part:

Typically, researchers study mantis specimens’ male genitalia to delineate their species. But Sydney Brannoch, the Ph.D. candidate at Case Western Reserve University who led the ginsburgae study, decided to study female mantis’ genitalia instead—and, thanks to her innovation, was able to distinguish Ilomantis ginsburgae as a new species. (The specimen she studied had actually been sitting around since 1967; you can learn more about Brannoch’s methodology here.)

One of the most important ways that scientists’ goals, attitudes, and beliefs can influence how science is done is in what question is asked. An anecdote (from here) about industry funding of scientific studies put it this way: “Industry funding doesn’t bias the results, but it does buy the question.” (Of course, given positive publication bias, the money/persistence to ask a certain question over and over can affect what we think we know about the answer to a question.) But it’s not just industry funding that influences what questions get asked. In a society where weight is seen as the obvious cause of any health issue a fat person might have, the idea of looking at causes that are correlated with weight instead of assuming it’s the weight itself might seem ridiculous and not worth investigating.

A response to Emma Lindsey’s “Why do fat people even care about dating skinny people?”

I thought that this Emma Lindsey piece did have some good points, but she also misses some stuff that seems obvious to me, as someone who’s actually fat and involved in fat acceptance, and she definitely comes off as condescending at times. But she’s also wrong in an interesting way instead of the same-old-same-old anti-fat-acceptance arguments.

A bad relationship waiting to happen? Will the fat mouse’s constant body criticism sap the thin mouse’s self-esteem? Is the fat mouse setting up the thin mouse as the arbiter of attractiveness?

Emma Lindsey conflates wanting to date skinny people and wanting to be seen as equally valuable as skinny people (say, wanting to see more fat/skinny pairings in magazine ads). Romantically valuable, in this case, but it’s part of the overall project of wanting to be equally valuable.If fat people are only ever with other fat people, that implies there’s some reason for fat and skinny people not to date each other, and in this culture the implied reason is that a fat person is always too unattractive for a skinny person to date, that it would be inconceivable for a skinny person to find a fat person attractive–which Lindsey, as a not-fat person, knows from experience is not true, in addition to the fact that it reinforces all the bad memes about fat people being disgusting, etc. Perhaps it’s unavoidable that this will subconsciously “reinforc[e] the notion of “attractive” people as judges”, but I don’t think it’s better to never show fat/skinny couples, as if they are never a thing that happens and a skinny person would never be seen with a gross fat person.

Calories In-Calories Out: Not Even Wrong

I recently read an overall-pretty-good article in The Atlantic called “What Does a Calorie Measure?” about how calorie counting is being criticized by some people, often in favor of focusing on satiety. This helped me to hit on what I’ve decided is the perfect way of describing the calories in-calories out, ELMM philosophy: not even wrong.

Sometimes a good idea will get oversimplified in more casual speech–a blog post about how intent is not fucking magic becomes “intent doesn’t matter”, or “calories in-calories out uses two numbers that are harder than people think to calculate and most people aren’t that good at ignoring hunger anyway” becomes “calories in-calories out is wrong”. But it’s not wrong. It’s not even wrong.

The more strict meaning of not even wrong is that something is bad science because it’s unfalsifiable. Calories in-calories out fits this sense in a way–the average dieter isn’t going to have access to the kind of precision measuring equipment (measuring temperature or carbon dioxide) to calculate precisely how many calories they’re burning, and they’re probably going to rely on food packaging or measuring cups–or even more imprecisely, estimating “a fist-sized portion”, etc. to give them a rough count of calories. So if they gain or lose more weight than predicted, then they have to assume that their estimates of how many calories they burned or how many calories they took in were wrong. If scientists only had the tools available to the average person, calories in-calories out would be unfalsifiable.

But what I’m primarily getting at uses the phrase “not even wrong” in a looser sense. Calories in-calories out is not useful information. Most people most of the time will not be able to follow a food plan that relies on ignoring internal cues–even leaving aside all the problems with correctly estimating calories in/out. Satiety will be a more relevant cue to most people than the calories on a nutrition label.

Also, some thoughts about that Atlantic article not related to the main thrust of this post:

-If the salad is only 300 calories, no, I’m not going to feel an absence of hunger for several hours after a chicken salad, trust me. I’ll probably feel full longer than with 300 calories of cheesecake, but still.

-Is the idea of satiety useful from a HAES perspective? I think it can be. If you focus on it not as a way to weigh less but as a way for your body’s hunger and fullness signals to work the way they’re meant to with foods that are not too far from traditional human diets, and don’t interpret as an all-or-nothing, only-eat-foods-with-high-satiety-values, I think it makes sense.

 

 

Genes and BMI Part 2: Evidence for a genetic influence on weight in a post-‘obesity epidemic’ world

My previous post talked about how it is possible for differences between groups to have one cause, and differences within those groups to have a different cause–that disproving changing genes as a cause of the ‘obesity epidemic’ does not prove that who gets fat and who doesn’t in our environment is due to, say, what your parents fed you as a child more than your genes. (There’s also a pretty good explanation of heritability and BMI here.) But is there positive evidence that it is not only possible, but that is indeed what’s happening–that genes play a fairly large role in who gets fat and who doesn’t in an “obesity epidemic”? Yes.

There’s a reason I’m being very careful to say “caused by changing genes” and not “caused by genes” as a great deal of popular writing does: whether and how much we gain weight given a change in environment is influenced by our genes, at both an individual and macro level. Just as the increase in height in response to more/better nutrition was part of our genetic potential, the population-wide increase in weight was possible because of our genetic potential. Both a general human tendency towards “thrifty genes”–genes that were influenced by a history of food shortages to store lots of fat in case of future food shortages–and differential “thriftiness” in individuals can lead to people putting on weight in good times in anticipation of bad times. And a tendency to put on more weight than before in good times after experiencing lean times–or a diet, since the intellectual part of our brains isn’t really talking to the homeostasis-keep-us-from-starving part of our brains–is also part of our genetic potential.

We can probably rule out “what your parents fed you as a child” as a reason why some people get fat and some don’t: adopted children’s BMIs are influenced a great deal by their biological parents’, with no significant influence from their adoptive parents’ BMIs. A study by Dr. Albert Stunkard of adult twins, some of whom had been adopted, found that the twins’ BMIs were very similar, and just as close together whether they were raised together or apart.

A deliberately-engineered change in environment can also show just how strong the genetic influence on weight is. A study by Dr. Claude Bouchard of 12 pairs of identical male twins found that within each pair, the two twins were highly similar to each other in amount and location of weight gain when Bouchard deliberately overfed the men by an extra 1000 calories a day–but there was a great deal of variation between different twin pairs. The pair gaining the most added about 29 lbs, while the pair gaining the least added about 9.5 lbs. (Most of the twin pairs returned to their original weight when taken out of the artificial-overfeeding environment.)

If it were just these three studies, then maybe things wouldn’t be so clear-cut. These were three of the ones that I remembered reading about in the past and/or that Traci Mann refers to in Secrets From The Eating Lab. But the title of this editorial from 2008 perhaps sums it up best: Obesity–still highly heritable after all these years.

(None of these measures of genetic effects on BMI are based on finding specific genes that influence BMI. Adoptee and twin studies are based on how much related or genetically identical individuals resemble each other, not on finding particular genes.)

Do any of these studies mean that significantly changing one’s BMI is completely impossible for everyone? No, but they do mean that for most people, the reason they weigh less or more than the average person in their environment is not because of some great effort or virtue on their part (or lack thereof), or because their parents gave them the exact right foods in the exact right ways, but because of their genes. And, sure, because of some of the new trendy research topics like gut bacteria, too. Some people will, through extraordinary effort, life circumstances, etc. be able to defeat their gene/environment combo, but most people who think they are thin through hard work would probably only be slightly fatter without their efforts. In other words, most thin people bragging about how they are thin through their own effort are the proverbial “born on third, think they hit a triple”. There was an editorial that I’ve never been able to find again, but it had a metaphor that really struck me: people would ask the writer, Isn’t it obvious that if you took two people and gave one free access to a constantly stocked fridge and gave the other carefully rationed meals, one would be fatter? The writer’s response: sure, but the difference in environment between people’s homes in obesity-epidemic countries is typically more like giving one person one constantly-stocked fridge and the other two constantly-stocked fridges.

Genes and BMI Part 1: Between-group variation and within-group variation are different things!

The Atlantic recently published a piece that is overall worth reading (and which I hopefully will write a separate blog post about soon), Rethinking the Calorie. It’s a relatively comprehensive look at the reasons why measuring “calories in” is not straightforward at all; it spends a lot of time on gut microbes in particular. One thing that they get wrong, though they are hardly alone in getting it wrong, is this:

Until recently, the idea that genetics plays a significant role in obesity had some traction: Researchers hypothesized that evolutionary pressures may have favored genes that predisposed some people to hold on to more calories in the form of added fat. Today, however, most scientists believe we can’t blame DNA for making us overweight. “The prevalence of obesity started to rise quite sharply in the 1980s,” says Nestle. “Genetics did not change in that 10- or 20-year period. So genetics can only account for part of it.”

The change in obesity rates between population does not imply that there isn’t a significant role for genetics in who gets fat. The amount of within-population variation is an order of magnitude different than the change in weight of the population between the 1980s and now.

Americans have gained about 30 lbs, along with about an inch of height, since the 1960s. But you can also find Americans with a three hundred lb difference in weight–100 lb people and 400 lb people both exist, and neither are all *that* uncommon. Speaking of that one-inch increase in height (or the ~4-inch increase in height that many countries have experienced over the last hundred years), that also doesn’t disprove that genetics play a significant role in height, and no one would seriously argue that it did, because differences between populations and the differences within populations don’t necessarily have the same causes.

For that matter, the differences in gut microbes and their association with BMI is all very interesting (sincerely!), but since they’re looking at differences between individuals in the same population and not differences between the gut microbes of, say, 1960s Americans and now, they’ve done nothing to show that gut microbes have anything to do with the significant changes in BMI at the population level known as the “obesity epidemic”.

This isn’t the first time that the difference between within-group variation and between-group variation has come up in a political context. It’s also come up in the context of race and intelligence, or more accurately, IQ tests, since we can’t directly measure actual intelligence. Performance on IQ tests has a significant heritable component; some people have tried to argue that this means that if black people as a group have lower IQ scores, it must be for genetic reasons. Those people are making a similar error, but in reverse–they are assuming that the cause of between-group and within-group differences must be the same, but they are taking a big component of within-group differences and assuming it must apply to between-group differences; in the case of BMI, people are also assuming that between-group and within-group differences must have the same cause(s), but they’re assuming that the “real” cause is the between-group cause.

An analogy I’ve seen used in the context of race and IQ is also useful here. Imagine two gardens with many varieties of corn growing in them. Within each garden, environmental conditions are the same. Each part of the garden is getting equal amounts of light, water, fertilizer, etc. The only reason the plants vary within each garden is because of their genes. But one garden gets optimal light, water, fertilizer, etc. and the other does not get the right amount of those resources. The difference between the gardens is not because of the plants’ genes, it’s because of their environment.

The concept is a bit counterintuitive, but it’s something I would expect scientists and experts on nutrition and weight to understand. And yet I see a surprisingly large number who don’t, even among those who are a bit smarter than to go along with “everyone knows” in other cases–for example, Barbara Berkeley. But definitely plenty from a certain food & nutrition writer who seems to be a very popular source of quotes and commentary for journalists.

Gut bacteria and blood sugar

There is an interesting new study out that looks at gut bacteria, a personalized-diet-creating algorithm, and blood sugar. Basically, they collected a bunch of data including biometrics (e.g. age, weight, hip circumference, A1c), family history, and, notably, gut bacteria (in a stool sample), then had participants use a continuous glucose monitor and keep track of their food, exercise, and sleep for week, then used that data to create an algorithm predicting blood sugar response, used that algorithm to create personalized “good” and “bad” diet plans that would either keep blood sugar levels down or spike them, respectively, pitted those diets against “good” and “bad” personalized diet plans created by a dietician with access to the same meal and glucose monitor data, and along the way looked at the way glucose response changes and is changed by gut bacteria.

I read a few articles and a blog post about this study before reading the full text of the study itself, and whether because I was reading quickly and missed a small but important word that went against the general emphasis of the article (I missed a “both” in this Atlantic article), information was omitted, the articles were just unclear, or actually misleading (it seemed like this ScienceDaily article’s repeated vague references to diets “working” were designed to encourage people to think of weight loss rather than blood sugar response), there were several ways that the study was not what it initially appeared.

Review: Secrets from the Eating Lab

I first became interested in this book after reading an interview with author Traci Mann from shortly before the book came out. If her name seems familiar, you may recognize it from a study that is often cited in fatosphere blogs, Medicare’s search for obesity treatments: diets are not the answer [article/press release about the study]. This is a relatively short, readable book, with occasional flashes of humor, which despite its brevity is a fairly comprehensive look at the science around weight loss and gain, set points, and the psychology behind eating. However, despite its strong critique of diets and the weight loss industry, and its skeptical stance towards the importance of BMI, it is not 100% weight neutral because it recommends staying at the low end of your set point range, so readers for whom any pro-weight-manipulation talk is problematic should proceed with caution.

Is cheese an addictive substance?

I’ve come across a couple articles recently alleging that cheese is addictive, based on a study that pointed to pizza as the most addictive food out of the 35 foods they looked at. Both articles point to the supposed opiate effect of casein, a milk protein.

So is cheese addictive? And more specifically, is cheese addictive because casein is an opiate-like chemical? Spoiler alert: no.

Some cheese that you shouldn’t eat

The Abstinence-Only Approach to Weight

Many people reject same arguments in favor of abstinence-only education, or arguments for why it’s okay to slut-shame, that they apply to weight loss/maintenance attempts*:

-If people don’t have sex, they do not get STDs or become pregnant from sex. Therefore, abstinence works 100% of the time! If teenagers have sex after an abstinence-only course, this does not represent a failure of abstinence-only. [Analogous to–Answering people pointing out the low success rate for maintaining a large weight loss with “If you eat less calories than you burn, you’ll lose weight; it’s just thermodynamics,” and/or pointing out that people who are put in labs with their calorie intake strictly controlled and no access to outside food will lose weight while they’re in the lab. If dieters/”lifestyle change”-ers fail to maintain weight loss, it is not a failure of the diet/lifestyle change.]

-It’s reasonable to expect teenagers to abstain from sex, and for adults to abstain from sex until marriage, or perhaps even afterwards periodically, if they and their partner both want to have sex but don’t want to get pregnant. It’s reasonable to expect gay people to just be celibate their whole lives unless and until they are able to experience heterosexual attraction. [Analogous to–Just ignore your hunger signals forever! Instead, count calories forever! (Or maybe we’ll pretend like counting calories [or other method for keeping close tabs on amount of food] forever is not something you have to do, because hey, I’m thin and I don’t have to do it, and obviously everyone else works the same as me!)]

-Valuing pleasure is selfish. Why should I pay health insurance money that goes towards your birth control? [Analogous to–fat people are using up all the healthcare money; I am outraged that I have to pay for fat people’s healthcare. (Note that ‘valuing pleasure’ is often not the most accurate description of why people are fat, but in cases where it is I think that people have the right to make that choice.)]

-I can tell that you have lots of sex from the way you dress. I can tell that you have sex much more irresponsibly than me from the fact that you are an unwed mother (even if I also had unmarried sex). [Analogous to–I can tell what your health behaviors are by looking at your body.]

-If you can’t “resist temptation”/won’t deny your biologically-related desires in a situation where it’s not hurting anyone, I assume that you can’t control them when they do hurt someone. You’re probably a rapist. [Analogous to–fat people would be perfectly willing to/already are eating food that would go to starving people, if only they weren’t eating it.]

-Corporations are brainwashing impressionable youth and they totally wouldn’t have sex if it weren’t for corrupt media. [Analogous to–Fat people are dupes of corporations; we should pity them in the most condescending way possible. (I’m not letting corporations off the hook for their role in health, environmental damage, and other bad stuff relating to our food supply, but fat people are not uniquely duped/manipulated/controlled by corporations in a way other people aren’t, and corporations don’t uniquely dupe people when they sell food everyone agrees is unhealthy–just look at the health obsessives using NutriBullet (LV Anderson does a good job debunking its magical health claims and examining how people are convinced of those claims; definitely worth a read), which is not stereotypically associated with fat people the way that soda or fast food is.)]

I’m far from the first to point out that we take a similar moralistic approach towards eating and exercise behaviors that we “used to” around sex (except many people still do feel that way about sex, and I’m not sure that anyone’s completely free of it). Often it’s in the context of anorexia and eating disorders, in other words, how to be “pure” oneself. This is about how it applies to the people trying to control the behavior of others. [Fat is not a behavior, but weight loss attempts are.]

*Obviously some people believe in both, but there are plenty out there who are very pro-weight-loss-attempts but very anti-abstinence-only.

Chocolate and Disillusionment

Recently it was revealed in i09 that a study on the health effects of chocolate was B.S. It wasn’t faked, but it was B.S., as it was designed to be, because the people doing it wanted to see how much press such a bad study would get.

This flower is kinda chocolatey-looking. “The Watchman” hollyhock, from my garden at a previous residence.

A couple blogs I sometimes read, Pharyngula and The Incidental Economist, have pointed out the questionable ethics of publishing a study that involved lying to the participants (but participants are often lied to, at least in psychological studies), their fellow scientists, and the media; I’m not sure if I’m equally concerned or not. (Pharyngula also points out, “it’s a spectacular way to illustrate p-hacking and the unreliability of peer review”.) Multiple people have also pointed out that most/all of the places publishing the chocolate study were not reputable (depending on your definition of reputable–I’d say Prevention is an edge case). (Daniel Engber notes that this may be because there have been multiple other studies showing benefits for chocolate, so this one lacks novelty, rather than solely because few were fooled.)

A couple sources quoted in the Pharyngula post included some surprising objections, though.

Rachel Ehrenberg:

There’s real wrongdoing in both science and journalism (most infamously, see Stephen Glass, Jayson Blair, Janet Cooke, Jonah Lehrer, Brian Williams). But intentionally creating wrong to make a point is both bizarre and potentially very damaging.

“Our key resource as journalists is credibility,” Edmonds told me. “And a deceptive ploy like this could damage that.”

Chris Lee:

The end of the experiment is that millions of people all over the world were told that chocolate will help them lose weight. The consequence is that all those people who search (in vain) for fad diets—often to help them with their self-image—have been given yet another false data point and another failure to reflect upon.

In terms of ethical analysis, this is an experiment that did not tell us anything that wasn’t known already. On that score alone, the experiment fails to pass muster. Then there are the downsides. The reputation of science journals and science communicators just got a slight additional tarnish.

So, why is it a bad thing that people know that “science journals and science communicators” sometimes publish garbage? Why is it a bad thing for people to know that fad diets are often based on garbage science/”science”? I’m sure that these guys are worried that people will think ALL science is garbage based on this, but I’m not sure that that’s worse than people thinking that NO science is garbage. Best case scenario, people will be more skeptical of science journalism and wait for a strong consensus. Worst case scenario, they will retreat to “common sense”. (Well, some might get into the particularly bad kinds of alternative medicine, I guess, but I doubt that this will push many people into that who weren’t interested in it before.) Worst case scenario if they’re NOT skeptical of science reporting: they jump on every new bandwagon and waste their money on a bunch of questionably-effective supplements and such, and try potentially-dangerous new health advice that they think was proved by “a study”.

There are writers in FA who connect their religious views with their Fat Acceptance blogging in a way I find interesting and very poetic at times. For me, there are resonances between Fat Acceptance and atheism as well. One that’s relevant here: the end of belief in something isn’t always sad, at least once you’ve fully processed it. It can be liberating.

On to some more detailed discussion of the study.

Slate Star Codex also discussed the chocolate study, and how some people are taking unwarranted conclusions from it. I think some of his commentary about Conclusion 1 is kind of questionable–he’s combining findings of blood pressure reduction, flow-mediated dilation, insulin sensitivity, absolute BMI, and weight gain. Only the non-meta-analyses had findings related to BMI or weight gain, and even with meta-analyses we should be cautious, since the bias against publishing negative findings can affect them too, and from what I can tell from a quick pass, the effects were statistically significant but small in magnitude. (And similarly, in Conclusion 2, I think he overstates how much certainty we can have about chocolate’s health benefits.)

Anyway, the most important takeaway from this most recent chocolate study, besides, perhaps, Slate Star Codex’s Trust Science Journalism Less [with caveats about where it’s reported, etc], is that many scientific studies will measure multiple variables to see if one of them is significant. In the words of John Bohannon, one of the chocolate study’s authors and the author of the i09 article

Here’s a dirty little science secret: If you measure a large number of things about a small number of people, you are almost guaranteed to get a “statistically significant” result. Our study included 18 different measurements—weight, cholesterol, sodium, blood protein levels, sleep quality, well-being, etc.—from 15 people. (One subject was dropped.) That study design is a recipe for false positives.

…

With our 18 measurements, we had a 60% chance of getting some“significant” result with p < 0.05. (The measurements weren’t independent, so it could be even higher.) The game was stacked in our favor.

It’s called p-hacking—fiddling with your experimental design and data to push p under 0.05—and it’s a big problem. Most scientists are honest and do it unconsciously. They get negative results, convince themselves they goofed, and repeat the experiment until it “works.” Or they drop “outlier” data points.

Similarly, although the Look AHEAD study was nowhere near suffering from the low sample size problem that the chocolate study had, the fact that it reported no effect of weight loss on heart attacks, strokes, cardiovascular deaths, blood sugar, blood pressure, cholesterol… Oh look! They took fewer medications! …Well, that’s why I’m skeptical of how meaningful the fewer medications part is.

Bohannon also says

People who are desperate for reliable information face a bewildering array of diet guidance—salt is bad, salt is good, protein is good, protein is bad, fat is bad, fat is good—that changes like the weather. But science will figure it out, right? Now that we’re calling obesity an epidemic, funding will flow to the best scientists and all of this noise will die down, leaving us with clear answers to the causes and treatments.

Short answer: no. One reason that Bohannon doesn’t explicitly say is that “now that we’re calling obesity an epidemic” is leading to exactly the opposite–not an appetite for yearslong studies, but a big appetite for quick and headline-grabbing studies. Calling obesity an epidemic means that people’s emotions are running higher, that they’re willing to try things that don’t actually work because of the “don’t just stand there, do something!” effect. (I’m more inclined to say “don’t just do something, stand there!”)