Statistically informed ideas on how to make the world work better.

Category: Health

The costs of too much choice: How the science of evolutionary development justifies Obamacare

One of the more difficult and technical fields one could choose to study is Evo-Devo, or the evolution of development. Briefly, it is the field that studies how genetic programs determine the developmental process, how these programs evolve, and how the types of programs available constrain the directions evolution can take. For example, if humans were to evolve wings (an essential impossibility for many reasons), Evo-Devo lets us make the clear inference that we would not evolve them as sprouting from our shoulders like angels, but rather as modifications of our arms. Why? Because in all tetrapods (i.e., eptiles, amphibians, birds, and mammals) there is a developmental program to produce four limbs. Limbs can be lost (snakes, whales) and modified for flight (bats, birds), but they cannot be added.

One of the key insights to emerge from Evo-Devo is that developmental programs are highly organized. They have evolved ways to facilitate future evolution, called evolvability. They achieve this using mechanisms known as gene regulatory networks, compartmentalization, and canalization. While the details of these mechanisms are beyond the scope of this post, they have in common that they are ways to facilitate long-term evolution at the cost of flexibility. That is, they standardize the developmental process to give consistent results, but limit the forms that can be arrived at. Again, tetrapod limbs are a good example: if tetrapod limbs were not the result of a fairly standardized genetic module, we would be able to evolve them anywhere any time – the nose could become a hand, we could evolve rows of wings up and down our backs, etc. However, the  result would be chaos. It would be too easy for a minor mutation to mess up development, too easy for the final form to depend too heavily on what gene combinations one has (image if parents regularly “accidentally” gave birth to children with 6 or 10 limbs, just because of  how their genes got combined…), and too hard to control the evolution of limbs as the environment changed and a specific sort of form became necessary. In other words, we gave up flexibility for stability and predictability.

How does all this relate to Obamacare?  Read the rest of this entry »

Optimized charitable giving, evidence-based medicine, and the risk of thinking we can measure everything

GiveWell logo, taken from there website.

The GiveWell logo, taken from their website.

I read an interesting blog post this morning on Wonkblog about how some people are getting jobs on Wall Street in order to save the world: the idea is to make as much money as quickly as possible, live on next to nothing, and then use the saved money to save the world more efficiently than one could by joining the Peace Corps or becoming a doctor.

The post discussed a website/organization called GiveWell that takes a very hard-nosed, analytical approach to how we should most efficiently use our charitable dollars to do good in the world. The ballet or the symphony is nice, but by buying bed nets to prevent malaria you could be saving children’s lives for very little money, so guess which GiveWell recommends you to donate to? They choose a small number of top charities among a large number they review, and they are very careful not to make claims that the non-top charities are not useful, only that there is very good evidence that the top charities are useful. I am truly impressed with the thoughtfulness of the approach and the quality of the research they seem to have done.

But – and there’s always a but – it struck me that there is a limit to this approach to charitable giving, and it is strikingly similar to a limitation of evidence-based medicine that I’ve been bumping into recently. Read the rest of this entry »

The benefits of a Mediterranean diet: thoughts on the new study

olive oil

A new study in the New England Journal of Medicine claims that a Mediterranean diet (lots of nuts, fish, olive oil, and fruits and vegetables, not too much dairy, red meat etc.) can dramatically lower cardiovascular disease events and mortality. My opinions on this study are a bit schizophrenic – it confirms what I’ve been saying for a while, but I don’t trust the methods. In the end, I think the study is largely correct, but somewhat by luck.

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Public access to scientific findings: a mixed blessing



The Washington Post is reporting that the Obama administration is ordering greater public access to publicly funded research. This sounds good, but what exactly does it mean, and why wasn’t it done already? In fact, most research funded by the US government through grants to independent researchers (e.g. such as me, at universities) is already required to be made available to the public within 12 months of publication. The same is true for health research here in Canada, via the Canadian Institutes of Health Research (CIHR).

Here’s how the system works now: As a researcher, I want to publish my results. This helps other researchers (and the public) learn what I’ve done, and it helps my career. I do so by submitting an article to a peer-review journal, of which there are many. I make the choice based on how important I think my findings are (and thus how ambitious I can be in shooting for a top journal, which will be more widely read and look better on my CV). The journal may or may not accept my article, and will probably require extensive revisions. The process generally takes about 6 months from the initial submission, assuming the first journal accepts, and it requires a lot of time in terms of revising, formatting, submitting, proofreading, and so forth. This is excluding the time to prepare the original article.

Once my article is published, it is available online at the publisher’s website or in print at any library that subscribes to the journal. Most people now read online. Anyone can access the article’s abstract and some other data about it, but for most journals, only individuals affiliated with a subscribing university can access the full article. Anyone not affiliated can access for around $30, an exorbitant fee. Nearly all of the fees associated with publication are sustained by university library subscriptions. Publishers make enormous profits because they have a monopoly on each journal, and those who pay for the journals are not those who publish in them, removing the normal market forces from the system.

Some journals, however, are open-access, which means anyone anywhere can read the article online for free, but the researcher must generally pay a publication fee of $1000-2000. Most journals that are not open-access offer an option to publish articles as open-access, for a higher fee.

Since the public pays for research through government grants, the argument goes that the public should have access to the results. As a consequence, many funding agencies have started requiring that their grantees make their results public within a year of journal publication. This sounds great, and it is definitely an admirable goal, but the transition is difficult, as illustrated by my recent experience.

I had just had an article accepted in Mechanisms of Ageing and Devleopment (MAD), a good journal in my field and the best one for this particular article. It is a rather technical article unlikely to be of interest to people outside academia, but important as a base for my future research and to describe a method many others are likely to want to use. I had just become aware of CIHR’s new policy that the results had to be publicly available within 12 months, and I thought this was a good thing. So I started looking into what this meant for my upcoming publication.

MAD is owned by Elsevier, the largest academic publishing house. I started poking around their website, and I found that I could pay $3000 (from my grant money, not my pocket) to publish open access. It was not clear if I had the right to make my article public in some way without paying this. (It’s a lot of money, enough to support a summer research student who could complete a project and learn a lot, a much better use in this case than granting theoretic access to a public unlikely to read the article.) There was some information about different levels of access, “green,” “gold,” “white,” etc. It seemed that MAD was green, which meant that I was allowed to submit a non-formatted version of the article to a public archive after 12 months. However, another webpage said that Elsevier had no agreement with CIHR, which meant that I could not submit to an archive. It wasn’t clear.

So I wrote to both CIHR and Elsevier asking for clarifications. They both sent me links to various websites which were not very helpful or which I’d already seen. I finally talked by phone to someone at CIHR, who was very friendly and helpful but did not seem to know what to do. After repeated conversations with her, she suggested that I should try to negotiate the publication contract each time I published an article, an obvious non-starter since I have no leverage in such a negotiation, and since whatever journal functionaries will just want to get rid of my questions as quickly as possible.

Elsevier in fact responded in just this way. I was never able to get more out of them than an effective “just pay the $3000 and stop bothering us.” Eventually, I gave up and paid because I had little hope of finding something else out with more time, and I’d already put a lot of time into the question. But things won’t be any clearer next time around…

I strongly believe that all research findings should be publicly available, and that there should not be any private publishing houses such as Elsevier. Financing for publication should come from an international consortium of governments that agree to pay proportional to the amount their countries produce. It could even be that every researcher is required to pay open access fees for every article from grant money, and that these fees are slightly elevated in order to allow individuals without grant money to publish for free.

But we are a long way from this system. In the meantime, MAD was the journal I needed to publish my article in. Elsevier had a monopoly on MAD, and extorted $3000 from me (much more than the real publication cost, I’m sure). CIHR’s rules, implemented with good intentions but without the necessary agreements with publishers, meant that $3000 of their money (and mine) got wasted. And we are not, in practice, much closer to a true open-access world. In the meantime, I have one more expense and more administrative headaches that will slow down my scientific productivity…

One other quirk reported by the Washington Post: the Obama administration will require government researchers to publish their findings. This also sounds good, but is not workable in practice. Publishing takes an enormous amount of time and effort, and I publish perhaps one tenth of what I could or what I would like to based on time constraints. I have lots of old results sitting in folders that I don’t have time to write up. Forcing me to publish all my results (even the ones I deem less important) would slow down my productivity in generating the truly important results.

So, while well-intentioned, the new rules seem as likely to do harm as to do good….

Idea: A better way to allocate grants for research

There is a paradox that most granting agencies face when they fund research: Researchers have a strong incentive to ask for as much money as possible even if they don’t really need it. One reason is that researchers are evaluated by both their institutions and their peers based on the number of grant dollars obtained (rather than on the quality of their research or their productivity). Another reason is that it’s always better to have a little too much money in the budget than not enough – we might as well estimate high.

These incentives are at work all the time in subtle ways. They mean that researchers ask for more money than they need. There is thus a slow inflation in the accepted “cost of doing business” and in the amounts viewed as normal. There is no reason at all for researchers to try to get by on a shoestring. Perhaps most insidiously, there is an incentive for young researchers to choose research topics that require more money for the same amount of productivity. Several years ago at the University of Michigan, I heard that one of the deans wanted to hire fewer faculty in ecology and evolution and more in lab-based biology because the latter brought in larger grants.* I often see colleagues in developing countries finding cheap and inventive ways to do the same things we do here, just on a fraction of our budgets.

In addition, most granting agencies demand detailed budgets for submitted projects. These budgets require lots of time to prepare, lots of time for peers to review, and are mostly made up anyway – people say in the budget what they need to say to get funded, knowing they can use the money as they wish later. I have even been told by CIHR representatives that I should fudge my budget because it is the best way to get funded!

One reason these problems persist is that in most cases successful grants are chosen with regard to quality but without regard to value. In other words, if there is $1 million left in the budget and a $1 million grant is ranked just above 10 grants that are $100,000, the $1 million grant will be funded and none of the next 10 will be, even if the total value of the next ten projects is 9.5 times that of the $1 million project.

I’ve just devised a system that I think elegantly solves this problem and substantially reduces paperwork. Here is a summary:

1)      For competitions, the funding agency decides a priori on a number of funding tiers (say 7, ranging from $80,000/year to $1 million per year). Each tier has a number of slots available based on the total budget, with many slots available at the lowest tiers and very few at the highest.

2)      Each researcher does not fill out a budget, but simply selects a tier he or she wishes to be considered for. If the grant is awarded, this is the amount that will be received – no more, no less.

3)      All applications are ranked based on quality, without regard to the budget tier chosen.

4)      Funded applications are chosen starting at the lowest tier and choosing the best candidates who applied for that tier, until the number of slots allotted for that tier are filled.

5)      At each higher tier, any applications not chosen for the lower tiers are retained in the competition, and will still be funded at their requested (lower) tier if they rank sufficiently high among the higher-tier applications. In other words, at each tier the highest-ranked applications are funded, including those at that tier and those not selected at lower tiers.

6)      Any remaining funds (due, for example, to lower-tier candidates winning higher-tier slots) can be given to the remaining candidates in order of their rank, irrespective of tier.


This system has a number of clear advantages:

1)      It removes a huge amount of work from both writing and reviewing grants – everything related to budgets, which are usually fudged anyway.

2)      It gives a strong incentive to researchers to conduct their research on the smallest budget possible, since the chances of obtaining a grant are much larger for those with smaller budgets.

3)      It gives a way to fund larger-budget projects or programs when justified, and lets the competition incentivize the researchers to make the determination about necessity.

4)      It gives an incentive to young researchers to choose relatively cost-effective fields of study, improving the cost efficiency of research for decades to come.

5)      It rewards overall candidate quality and frugality simultaneously, in such a way that budget does not become a perverse incentive to do other than the best research.


What do you think? Would it work? What are the challenges?


*Caveat: I heard this story second-hand years ago, and may have misremembered something in the details. But there was unquestionably a perception that expensive research was prioritized by someone higher up.

Obesity and mortality: challenging the conventional wisdom, part III: BMI is nearly useless

I’ve just written a couple posts critiquing the recent study in the Journal of the American Medical Association claiming that overweight people are at lower risk of mortality. This is the third and last, and will be a detailed exploration of why BMI is a bad metric of obesity.

I am certainly not the first to claim this, and indeed there are many researchers who have been defending measures such as waist circumfrence for years. But my point is not just to trash BMI, nor to defend another measure in particular (I think waist circumfrence is also a red herring), but rather to use BMI as an example of how shoddy thinking can lead to the adoption of poor metrics and thus serious public health consequences.

Read the rest of this entry »

Obesity and mortality: challenging the conventional wisdom, part II: Categorisation is fatal

This post is the second in a series critiquing the much-publicized recent study by Flegal et al. in JAMA, which claims that there is a lower risk of mortality among overweight people than normal weight people. As in my last post, my main beef is that our standard categories of BMI are a problem, but here I argue against categorizing altogether. In fact, I think there is a good argument that researchers categorizing BMI is literally fatal for many people.

How so? Well, once we put someone in a bin such as “obese” or “normal,” we have a mental tendency to accept the categories as something real, something objective. But they are not. These cut-offs are arbitrary, chosen mostly because they are nice round numbers. This can be seen easily on a histogram of 53,000 BMIs taken from the NHANES study (American adults age 20+, roughly 1998-2010):

NHANES BMI dist Read the rest of this entry »

Obesity and mortality: challenging the conventional wisdom, part I

A recent article in the Journal of the American Medical Association has gotten a lot of attention for claiming that risk of mortality is lower in overweight people than normal weight people. I will write a series of posts critiquing this article, which I think demonstrates many of the problems with modern epidemiology and research in this field.

This first post is a very simple one: We do not correctly classify obesity. The standard classification used by the article is as follows:

BMI < 18.5 : Underweight

18.5 < BMI < 25 : Normal weight

25 < BMI < 30 : Overweight

30 < BMI < 35 : Obese (grade 1)

35 < BMI : Obese (grades 2-3)

I just calculated my BMI for the first time. BMI is calculated as mass (kg) / height×height (m). I weigh 175-180 lbs (80 kg) and am 6 feet (184 cm) tall. My BMI is thus  around 23.6 – 24.4, depending on the day. This puts me at the upper end of “normal.” In other words, anyone a bit heavier than me is overweight. Here I am:


While I am not underweight (at least not much), anyone who knows me will tell you I am a bit on the lean/slender side. I have to work to avoid being too skinny. I am not at the upper end of normal, I am at the lower end of normal – a pretty broad range on this scale.

Everyone who works with BMI admits that it is an imperfect measure – that it can classify body builders in heavier categories, for example, and that it doesn’t really incorporate body type. But I’m not a body builder, and I have a standard body type, and the standard scale is telling me that I’m not far from being overweight. According to the scale, I would have to lose 55 lbs (25 kg) to become underweight! Even when I had cancer and became a bit emaciated (to the consternation of everyone who saw me), I only lost about 20 lbs.

I use myself as an example, but I am convinced the standard cut-offs are wrong. Many people who are underweight (anorexic or wasting away due to cancer, and thus at higher risk of mortality) are in the “normal” category. And many people at the perfect weight are in the “overweight” category. So it’s no wonder we will see strange results like that from the JAMA study.

How about you? Is your BMI about right according to the scale above?

What Todd Akin gets right about rape and evolution

OK, I’m about to piss a lot of people off. Here goes…

US Senate candidate Todd Akin said, “It seems to me, from what I understand from doctors, [pregnancy from rape is] really rare. If it’s a legitimate rape, the female body has ways to try to shut that whole thing down.”

Todd Akin is an idiot. Tood Akin is ignorant. Todd Akin is insensitive to women. Todd Akin is a religious lunatic. All true. But Tood Akin is also (a little bit) right about rape, and about evolution (which I presume he doesn’t believe in).

Hear me out. I’m not saying no one gets pregnant from rape. I’m not saying we can distinguish between “legitimate” and “illegitimate” rape legally or morally. But I do think that women’s own perceptions of rape can be more or less severe, and that there are biological mechanisms to reduce the probability of pregnancy following a rape.

There is only one fundamental law of biology, and it is this: whenever you think you understand something, it’s more complex than that. Almost every major principle of biology has later been shown to have exceptions or caveats. One example of a simplistic principle is that once sperm are released, nothing the woman does affects the probability of fertilization. In fact, it is well-established that muscular contractions during a woman’s orgasm help draw in sperm and increase the probability of fertilization. During rape, no orgasm. No orgasm, no contractions. No contractions, lower probability of fertilization.

I do not know if other potential mechanisms for avoiding pregnancy from rape have been discovered, but I would bet they exist. It’s not hard to imagine that acute psychological trauma could release hormones that would reduce the probability of implantation, for example. Natural selection should fairly strongly favor avoidance of pregnancy via rape – the psychological trauma caused by rape is itself presumably the result of strong evolutionary pressure on women to make them avoid rape as much as possible.

And if psychological trauma does reduce the chances of pregnancy (I’m not saying it does, I’m saying it might), it is likely that the degree of trauma affects the probability of getting pregnant: more trauma, less probability of getting pregnant. So then we have the question: is all rape equally traumatic? I have no idea. I’m not a woman and I can’t say. But my guess (please, women, correct me if I’m wrong) is that it would be possible to imagine various rape scenarios, some more traumatic and some less. I’m not saying the different scenarios are morally different or legally different; I’m saying that the woman would perceive them as more or less traumatic. Todd Akin was 100% wrong to try to distinguish legitimate and illegitimate rape, but many commentators may have also been wrong to assert that, biologically speaking, all rape (or all insemination) is equivalent.

So let’s criticize Tood Akin for the many things he is guilty of, not for being wrong about biology when the biology is not necessarily well-known, and when his statement contains at least a grain of truth. And let’s take pleasure in the fact that even this religious nutcase has inadvertently invoked evolution in his understanding of rape!

Universal health care is good for the rich

As I mentioned in my last post, I’ve been reading T. R. Reid’s book The Healing of America, a look at different health care systems across the world and what the US can learn from them. The basic point of the book is that in every other industrialized country, there is some form of universal health care, which always results in much less total spending on health care and substantially better health outcomes.

Towards the end, Reid compares two hypothetical American women, rich and lower middle class, who are diagnosed with ovarian cancer. He suggests that the US system works fine for the rich woman, who gets diagnosed early, gets surgery costing $55,000, and lives another 40 years, whereas the working-class woman has no insurance, gets diagnosed too late, and dies because she can’t get surgery.

The basic point of his argument, one made often, is that the US system is really bad for the poor and uninsured. This is undoubtedly true. But there’s another argument we should be making, and are not: the US system is also worse than the alternatives for people who are rich or have good health insurance – for just about everyone, in other words.

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