Remember the joke about the drunk man searching unsuccessfully for his keys under the streetlight?
After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, and that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, “this is where the light is.”
We see this behavior all to often in science. Researchers interrogate the data that they have to answer a specific question when the answer is nowhere to be found in that data. Yesterday’s piece in the NYTimes, Does Breast Milk Have a Gender Bias?, illustrates both the “drunkard’s search” as well as the shoddy nature of most breastfeeding research.
This is a “drunkard’s search.” The authors used the data they had instead of the data that is required.
According to Nancy Segal and Satoshi Kanazawa:
In 1973, the biologist Robert Trivers and the computer scientist Dan Willard made a striking prediction about parents and their offspring. According to the principles of evolutionary theory, they argued, the male-to-female ratio of offspring should not be 50-50 (as chance would dictate), but rather should vary as a function of how good (or bad) the conditions are in which the parents find themselves…
In short: If things are good, you have more boys, and give them more stuff. If things are bad, you have more girls, and give more of your stuff to them.
Is this hypothesis correct? In new research of ours, to be published in the April issue of The Journal of Experimental Child Psychology, we suggest that in the case of breast-feeding, at least, it appears to be.
The first red flag is the journal. What is a paper on breastmilk composition doing in The Journal of Experimental Child Psychology when the issue under investigation has nothing to do with child psychology? Almost certainly because the authors couldn’t get it into one of the relevant journals.
The second, glaring red flag is the nature of the study itself. The authors were trying to discern if breastmilk produced for male babies has a different composition or amount than breastmilk produced for female babies. Obviously, the only way to determine that is to compare the composition and volume of the two types of breastmilk.
That’s where the principle of the drunkard’s search comes in. The authors are psychologists, not chemists and they can’t investigate the actual composition of breastmilk. They do have a giant data base of information on adolescents, so they decide to look there.
They offer a Rube Goldberg version of reasoning to explain what they did.
The aim of our research was to figure out how to study the divergent effects of breast milk on sons and daughters on a much larger scale. Our solution: to look at twins.
In light of the emerging evidence of sex-specific variation in breast milk quality, the Trivers-Willard hypothesis implies that breast-feeding may be less beneficial for opposite-sex twins than for same-sex twins. Same-sex twins, after all, can benefit from their mother’s sex-tailored breast milk just as non-twins can. However, the breast milk of mothers of opposite-sex twins cannot be tailored for either sex. Perhaps it is selectively tailored for the wrong sex part of the time, or for neither sex all of the time.
Thus, the Trivers-Willard hypothesis led us to surmise that opposite-sex twins would be disadvantaged for health and growth. This would be reflected in their being shorter and weighing less than same-sex twins.
What??!!
There are so many unwarranted assumptions here that it’s hard to keep track.
Unwarranted assumption #1:Assuming gender specific breastmilk confers benefits. This is a version of the white hat bias that plagues all breastfeeding research: if it’s in breastmilk it must provide a benefit. But that doesn’t have to be true. If breastmilk plays a role in regulating gender composition of a population isn’t doesn’t necessarily have to provide gender specific benefits. It’s only necessary to provide benefits to one gender.
Unwarranted assumption #2: Assuming that looking at adolescent height and weight should tell us whether breastmilk is gender specific. This assumption is just bizarre. If the point of gender specific variations in breastmilk is to regulate the gender composition of the population, we would expect to see the differences in infancy and childhood, not adolescence.
Unwarranted assumption #3: Assuming that the benefits of gender specific breastmilk would be expressed in physical characteristics? Why? The point is supposed to be a survival advantage for one gender over another. What would make height and weight the relevant variables to look at. Wouldn’t survival rates be far more important?
Unwarranted assumption #4: Assuming that it makes any sense at all to look at anything besides the chemical composition and volume of breastmilk to determine whether there are gender specific differences in breastmilk. The authors undertook a drunkard’s search of the data in their possession instead of searching for the answer in the only place it can possibly be: in the composition and volume of breastmilk itself.
And if all that isn’t bad enough, the authors looked at only one twin in each pair, breastfeeding history depended on maternal recall more than a decade after the fact, and zygosity of same sex twins was determined by the mother’s impression instead of genetic testing.
What did they find?
The Wave I sample included 779 twins for whom the sex of their co-twin could be determined; of these, 546 respondents (277 females and 269 males) had same-sex twins and 233 respondents (120 females and 113 males) had opposite-sex twins…
The results showed that, among the ever-breastfed twins, same-sex twins were marginally significantly taller, F(1, 176) = 3.784, p = .053, significantly heavier, F(1, 170) = 5.400, p = .021, and significantly larger (either taller or heavier), F(1, 165) = 5.900, p = .016, than opposite-sex twins. In sharp contrast, among never-breastfed twins, same-sex/opposite-sex twin status was not significantly associated with height, F(1, 275) = 0.228, p = .633, weight, F(1, 266) = 0.417, p = .519, or body size, F(1, 259) = 0.798, p = .373.
The authors’ reasoning is extremely tortured:
The analysis of the Add Health data showed that breastfed same-sex twins were consistently taller and heavier than their opposite-sex counterparts throughout adolescence and early adulthood (from Age 16 to 29). In contrast, never-breastfed same-sex twins were no taller or heavier, and might even have tended to be shorter and lighter, than their opposite-sex counterparts. Our results are consistent with the recent findings that human breast milk may be tailored for each sex to facilitate its health and growth most efficiently. Same-sex twins can benefit from such sex-tailored breast milk, just as singletons can, but opposite-sex twins cannot do so and, therefore, may be at a disadvantage.
That reasoning would only apply if all four of their unwarranted assumptions were true and there’s no evidence that any of them are.
This is shoddy research, not surprising when you consider that it is a drunkard’s search. The authors used the data they had instead of the data that is required. The authors presume to draw conclusions about gender specificity of breastmilk without looking at breastmilk and without looking at infant and child outcomes. There is simply no reason for believing that adolescent height and weight tell us anything about breastmilk and it is irresponsible for the authors to imoly that there is.
Holy hell, what bad research. Let’s say opposite sex twins are significantly smaller in stature than identical twins. Who’s to say it’s the breastmilk that is the cause? Not this study. It could have been hormones in the womb.
Aren’t adolescent boys heavier than girls naturally because one effect of testosterone is to bulk up muscles?
Surely this is a joke…right? Please? *head desk*
Also, the idea of the breastmilk being “confused” as to whether to tailor itself to the girl twin or the boy twin gave me the giggles.
I read this “study” — reported on credulously by the NYTimes — with my jaw in my lap. Thanks for the excellent dismantling of this silly “drunkard’s search.” The flaws in methodology make this study nothing more than a fishing expedition. Worse, the authors work backwards from a conclusion — talk a bout a big red flag! Other studies on this VERY old hypothesis (from 1973) are equally flawed (poor methodology or bad math — one tiny study in Kenyan mothers (n=72) found a scant difference in the fat content of breastmilk of mothers of sons vs daughters, but later had to revise even that small difference up by a factor 3). [1]
Perhaps no one sums up the “research” on the Trivers–Willard hypothesis better than The Proceedings of the Royal Society (B): “Published studies addressing variation in mammalian sex ratios have produced surprisingly contradictory results. Explaining the source of such variation has been a challenge for sex–ratio theory, not least because no mechanism for sex–ratio adjustment is known. A meta–analysis of previous mammalian sex–ratio studies was undertaken to determine if there are any overall patterns in sex–ratio variation. The contradictory nature of previous results was confirmed.“[2]
It’s been almost 45 years since this hypothesis was introduced, and biologists and even computer scientists (!) have been unable to produce evidence in support of it (and not for lack of trying). It might be high time to consider the purely speculative Trivers–Willard effect for the trash bin.
_______
[1] https://www.scientificamerican.com/article/boys-and-girls-may-get-different-breast-milk/
[2] http://rspb.royalsocietypublishing.org/content/271/1549/1723.short
So many problems…but I’ll pick out just one. So I guess now, being heavier is considered “better?” Usually in breastfeeding research, the tendency is to make the data “prove” that formula feeding causes obesity.
I guess the data can mean whatever you want them to mean, if you don’t care about actual science.
The nipple doesn’t instantaneously adjust the milk to the age, gender, health of the suckling?
What are folks’ thoughts on this..
http://human-milk.com/index.html
(“Breastfeeding advert”). – also on facebook.
I felt a bit shaky/unsure about the info and quotes on bedsharing (under the “what’s natural” page) – and also the emphasis on stem cells, anticancer/alzheimer’s properties in the video. (I’m really not up to speed on the science here, and don’t know how fleshed out this all is. Happy to accept the components have been identified in human milk, but unclear if mechanisms and physiological role are established). I really really haven’t done my pubmedding here, but genuinely want to know if anyone has and this might be the quickest way!
Off topic, apols.
I haven’t got the knowledge to comment intelligently, but I’ll just say this: I’ll bet you good money that the research is of the interesting-field-with-promising-preliminary-findings-but-wildly-overblown-and-misapplied variety.
Also: Breastmilk has a lot of scary-sounding chemicals I can’t pronounce!
“What we don’t know: Why are they there? Is it different in preterm or
term milk? Do they matter to infant health? Can we use them for
treatment of any other diseases?”
Yes, that is how I feel about a lot of this stuff – all well and good to show XYZ is present, but what is really important from a health perspective is to know what it does under real conditions in real populations…
Much of this research, I feel is of the “not ready for prime time” variety — fine for it to be published, interesting, thought-provoking etc but very big question marks over the wider applicability/relevance and therefore giving it top billing in a carer-focussed presentation is a bit over the top. (Because there you need to be presenting stuff about REAL outcomes and implications from good quality clinical research in real populations).
The bed-sharing quotes “The knowledge that bed-sharing can be just as SAFE…”; “I wish I’d known that I could have SAFELY co-slept” worries me. (my caps).
The Blair analysis (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107799) often quoted in support of bedsharing safety – actually the confidence intervals for the estimates with this are wide and only just end up non significant, so the analysis from this study is in fact totally consistent with the estimates of other studies showing a risk:
Blair analysis: “The multivariable risk associated with bed-sharing in the absence of
these hazards…
for infants less than 3 months old (OR = 1.6 [95% CI: 0.96–2.7])” (note the 0.96-2.7 confidence intervals for the OR) – I would (and I think most medical statisticians would) interpret this as being consistent with increased risk of SIDS with “safe” bedsharing, actually.
cf the Carpenter analysis:
http://bmjopen.bmj.com/content/3/5/e002299
“When neither parent smoked, and the baby was less than 3 months,
breastfed and had no other risk factors, the AOR for bed sharing versus
room sharing was 5.1 (2.3 to 11.4)”
(lower bound of the carpenter CI just below the upper bound of the blair CI).
My coi: do BF support, and I co-slept (fully aware of a possible risk with SIDS).
wrote too much. what I meant by that is that even the blair study (oft quoted in support of bedsharing safety) is inconclusive with respect to bedsharing safety due to the breadth of the CIs. I really, really don’t think it’s entirely true to the body of the science to communicate to parents that bedsharing w/out other risk factors is “safe” (whatever your interpretation of the word “safe” is).
Yeah. I’m uneasy about what looks to me like bedsharing promotion. I mean, I know it’s where some families end up. Sleep deprivation can be crazy-making and if it’s the only way for some families to get some sleep then I don’t necessarily think it’s a bad thing that those parents can get clear information on how to do it as safely as possible. I don’t like that it’s under a section labelled “What’s Natural” and I don’t like statements like this:
“The cultural expectation that breastfeeding parents sleep separately from their babies doesn’t appear to fit with the evolutionary perspective.”
In some circumstances, it can be dangerous. I’ve never slept with my son in bed with me. I’m a really, really, heavy sleeper so there’s just no way I could have done it safely, regardless of ‘evolutionary perspective’. There is mention of ‘safe’ bedsharing on that page but, although there are some links, there’s no direct mention that it can be unsafe. I think that’s a bit irresponsible.
They claim that 50% of all UK babies have shared their parents bed by the time they are 3 months old. And apparently 70-80% of breastfed babies and then use this figure to show that bedsharing is ‘normal’ and ‘everyone does it’. I would really question this. I mean, is it likely that most breastfeeding mothers have passed out at least once in those first 3 months whilst feeding their babies? Possibly. Does that mean everyone is bedsharing? Uh, no. I think they’re massively stretching in order to reach that conclusion. And if they’re stretching in one area, I would bet they are in others.
That was a creepy video.
I can give you one – Dec 2016 review on published research on stem cells in breast milk led to finding a whopping 9 articles. Breast milk has pluripotent stem cells and women have different amounts in breast milk.
What we don’t know: Why are they there? Is it different in preterm or term milk? Do they matter to infant health? Can we use them for treatment of any other diseases?
Yes, we are looking at using stem cells to treat Alzheimer’s, diabetes and a bunch of other things. We may even be able to retrieve stem cells from breast milk to use for that. Trying to show that breast milk protects against Alzheimer’s, adult cancer, and Type 2 diabetes is not possible right now; any study would be based on what current adults with and without the disorders think about what their parents did to feed them as infants and that’s not a good way to study things.
There was a flurry of interest in the effects of breast-feeding as a protective mechanism for kids at risk of Type-1 diabetes. One study did a good job of following kids at risk of T1D for 29 months and using that data. Breastfeeding had no protective effect. https://www.ncbi.nlm.nih.gov/pubmed/10535447
My conflict of interest-I am hopelessly, shockingly bad at statistics. I failed the exam in medical school and had to resit. I can’t add a column of numbers to save my life-it’ll come out different every time. I can’t do Sudoko. When I do online numerical IQ tests I come out with an IQ of about 70. I couldn’t tell you the difference between mean, mode, median or whatever. It’s all a morass of confuddlement to me.
And I still managed to recognise that this paper, its methodology and its conclusions are basically a shower of shite.
I’m ok with stats. The ANOVA they used is reasonable for the categories they collected; the problem is that the categories they created don’t answer the question the authors are looking to answer. That and the fact that the data set they used doesn’t have the level of information they need to answer the question.
This would be a good example of how adequate stats can’t save mind-blowingly bad study design.
Anecdotally, I know the composition of my breastmilk wasn’t the same between my kids. I had excess lipase when nursing my daughter and had to scald the milk or it would be disgusting after 3-4 weeks in the freezer and she wouldn’t touch it. No such problem with the milk I produced when nursing my son. Now what correlation this has to anything else is anyone’s guess.
I agree with the person who would have given this study design an F. Good grief.
Obviously, your body knew you had a daughter and it knew you were pumping and it decided to add lipase in the milk to foil your plans because it didn’t want your daughter to live, because your environment was better for a boy. 😉
What I want to know is how your boobs know if it’s better time for boys or girls…
Quite possibly the testosterone from the male fetus, still in the mother’s body, affects milk production. But this is just a side effect of the pregnancy, not an evolved advantage. And no, it doesn’t mean that the milk differs depending or who is sucking at any specific point in time.
You weren’t the same between your kids. Age, stress levels, and metabolism were all different, plus when you had the second your body had been affected by carrying the first.
I can’t bring myself to read the paper.
Did they only look at DCDA same sex twins?
Did they control for gestational age at birth, hx of IUGR, NICU stay?
Did they control that genetically identical same-sex twins were more likely to be preemie NICU graduates with IUGR or TTTS?
Or that twins who are NICU graduates are the ones most likely to have had DONOR milk?
Heck no. They used the Add Health data set. Great for studying, for example, the link between teen social factors and mental health outcomes. But absolutely the dumbest dataset possible for trying to determine the composition of breastmilk. I helped pay my way through medical school in the 1990s by working under a PI using this dataset to study teen violence. And I worried our conclusions were a bit of a reach, sheesh.
They also forgot to include SES which is a mind-blowing oversight since the hypothesis is that SES and gender of infant affects breast milk composition.
I also think they messed up how they used gender on top of that. They used gender to sort the twins in categories of “same sex twins” and “different sex twins” which is not going to be useful for the hypothesis the authors gave.
The actual hypothesis they tested was closer to “do same sex-twins have identical growth patterns as different sex twins? If not, is breast milk exposure a possible factor?” to which the answer was “No. Possibly for weight as an adolescent.”
Enormously OT but still:
http://www.independent.co.uk/news/world/americas/mexico-city-policy-donald-trump-reimposes-abortion-a7542216.html
IPPF and MSI are facing a budget shortfall of $130million, because they would rather refuse US money than take it and abide by this rule.
If you are looking for any worthy causes to support…
I’ve just made a donation to IPPF. In the wider scheme of things, it’s just a drop in the ocean but I am so angry that all these rich white men think it’s ok to punish women (especially poor women) for having sex. I’m sick of the rhetoric, I’m sick of policies that will see dead female bodies stack up as a direct result. And for what? I just don’t understand how anyone can be so callous.
The gag order is the most regressive, repressive piece of legislation. It mocks any attempt the USA may try to make as a protector of the right to global freedom of speech.
US Aid money is already prohibited from being used to fund abortion by the Helms Act.
The Mexico City/Global gag rule prevents providers discussing abortion AT ALL.
Even when abortion is legal in that country.
Even if the specific pregnancy is a direct threat to the life or health of the woman.
Even for rape or incest (and we are talking about countries where rape is being or has been used as an act of war or genocide).
Even for foetal abnormalities in countries where the healthcare and social infrastructure doesn’t exist to give anything other than a short, painful life for a disabled child or where disability would lead to abandonment and destitution for the rest of the family.
Given Zika and the global geo-political situation at present this is the single stupidest, most misogynistic piece of legislation that it is possible to pass.
The number of unsafe abortions have fallen worldwide since its repeal. The number of women with access to birth control has risen. This is going to go backwards.
Hopefully Bill&Melinda Gates can find some money down the back of their sofa or something…
I heard Bill Gates was, or soon will be, a trillionaire. And, yes, I hate this bloody executive order just for itself. As a sign of what’s to come, it’s also abominable.
It sucks so many massive sweaty balls that the health and well-being and even the lives of so women all over the globe depends on a few thousand votes in some small states that nevertheless count more than mine does.
I’m having trouble understanding this. Can’t decide if that’s because I’m tired or because it’s nonsensical.
One of the courses I used to teach was an introductory probability and statistics course for gen ed/psychology/allied health majors. I tended to favor projects over exams (just a midterm and final). One of the projects I assigned every term was a hypothetical study design. If one of my students turned this in for their study design projects it would have gotten a big, fat F.
This study is like looking at wheat harvest amounts to predict what the weather was like during the spring of the harvest year. Could it be right? Maybe. Is it likely to be right? Not really. Is it the best way to do such a thing? FUCK NO.
It’s even two steps back from that – looking at wheat harvest amounts, but estimating that by the color of the bags used to carry the wheat…
Nah, not quite that extreme. More like looking at the price of wheat, to guess what the harvest amount was, to predict what the weather was like in the spring.
Ooh, that’s the right metaphor!
ROTFL. That’s the worst paper I’ve read in a while.
My favorite bit – the author’s note in the introduction that in humans the Trivers-Willard hypothesis in humans is that rich moms bias towards sons while poor moms bias towards daughters. (The rationale behind that is that a rich son can produce lots of surviving offspring while a poor son might have no chances to reproduce. A poor daughter will likely have some surviving children while a rich daughter can’t produce as many surviving children as a rich son can through having a very secure single wife, having secure multiple wives and/or having extra-marital offspring.) This hypothesis has been shown in a wide variety of settings.
See the problem yet?
The authors didn’t set up any method of controlling maternal socio-economic status in their model!
By dumping “same-sex twins” into one pile instead of making four separate piles (boy-rich mom, boy-poor mom, girl-rich mom, girl-poor mom), they’ve fucked up the basic hypothesis.
So breastfeeding history depended on maternal recall, but “779 twins for whom the sex of their co-twin could be determined” suggests that there are some twins for whom they didn’t know the sex of the other twin. I’m not sure I can even parse what they’re saying. But does this mean they had some data sources that didn’t identify the babies sex or that the parents couldn’t remember (???) Whaaaa?
Is this something parents commonly forget? Cause I’m pretty sure my recollections of breastfeeding are general impressionistic things – I can remember the emotions and generally that one kid ate more than the other. But unless something has changed today I’m pretty clear that my kids are girls and I have a really good understanding of their personalities. From, you know, living with them.
(Loosely interpreting gender vs sex, I’m pretty sure the authors had no interest in transgender issues!)
Maybe it was a twin pregnancy but miscarried one?
This is the craziest, most convoluted, most confounder-ridden, most confirmation-bias shitshow of a paper I have seen since jen last posted.
Wow. Just, wow.
This is why it is so frustrating when the lactivists and anti-vaxxer link to “studies” that prove they are right. Just because it is published, doesn’t mean it has any merit whatsoever.
Or even that it says what they want it to say. Often I look at the conclusions of the paper and find that they do not support the claim of the person linking to the paper.
Back in the mists of ancient time when I was in college, a mentor told me to look at the Methods and figures before reading the Results and Discussion. Because you don’t always agree.
I always go to the methods and figures before anything else. Often I’m reading a paper on a topic that’s above my ability to read easily as the topic matter is far beyond my expertise. These papers take a lot of work for me to read, as I have to stop and look stuff up pretty much every sentence. I do, however, understand statistical analysis. So I read that first, and if I find evidence of data torturing or other statistical shenanigans, I don’t even bother with the rest.
I sometimes think you all on this site are the only people who actually READ papers. I see RNs all the time who talk about evidence based practice but still insist breast is SIGNIFICANTLY best and marijuana will kill cancer pain. Because, PAPERS.
Marijuana doesn’t kill cancer pain? Maybe it just makes you care less about the pain. I know that the most touted benefit is not pain relief, but appetite accelerant.
Though after I broke my shoulder, I was wondering if someone could score me some weed oil to make me care less about the pain…
I’m confused as well by the emphasis on adolescent weight. Given the teen obesity rates in the U.S., why would you assume that someone who was heavier, but not taller (which seems to be the bulk of their sample) was healthier?
Probably more tortured reasoning. The breastfed ones weighed more, and breastfeeding MUST be best, therefore the fact that they’re heavier must be a good thing. If the kids had all had six fingers on each hand, the paper would have gushed about the wonders of polydactylism.
It’s what they had available in the data.
Most of the ADD-Health data is interview-based. That’s generally best analyzed using qualitative methods like case-studies, but you can attempt to force the data into quantitative methods like ANOVA and linear regressions like the authors did.
That’s why they created a cluster-fuck of “ever breast-feed” which clumped any kid whose mom said “yeah, I breast fed them for (less than three months, less than six months, less than a year, two years or more) into one ginormous group*.
Repeat that for the “Yeah, I am (certain, pretty sure but not 100%, rather unsure but I’m hazarding a guess) that my twins are (identical, fraternal) to make your two groups of identical and fraternal twins.
If that’s all they had, they’d be screwed so you attach some actual quantitative data involving height and weight.
*And if you read the paper (which is behind a paywall), they tried running each BF length group and the results were very, very weak. So….you make a bigger group and try again.
Complete opposite of what I usually hear. “If you don’t breastfeed your child they will be overweight.” But here, breastfeeding makes your child big and strong, more so than formula, and that’s supposed to be good. So I think I follow- when breastmilk does something it’s good, formula does it it is bad..
“The analysis of the Add Health data..[…]…”
The Add Health data?! They are using the Add Heath data? You have got to be kidding.
Henry VIII and his wives beg to differ.
Lost me on this.
I think it’s because he wanted a son, but the only legitimate son he produced was sickly and died young. His daughters, however, were more robust–don’t know if they were fed by their mothers, though.
I believe (although I could be mistaken) that Anne Boleyn wanted to breastfeed Elizabeth but ended up not doing so due to societal pressures. Ladies (and certainly not Queens) very, very rarely breastfed their own children and children were sent off to wet nurses in infancy. This was partly because breastfeeding is known to delay future pregnancies and, obviously, as a Queen who had failed to produce a male heir, she would have been expected to get pregnant again as soon as possible.
OK, Henry VIII was desperate for a son, right? All but one of his Spawns were girls, stillborn or died in infancy. Since back then they had no idea it was sperm that determined a baby’s sex, he blamed his wives for not giving him a surviving male heir. I wouldn’t be at all survived if he blamed breastmilk, too.
(You forgot Fitzroy)
He died before Daddy did, though.
True, but he did survive infancy and he wouldn’t have been in line for the throne anyway
Yes, Discus, I got it, you can quit sending me notifications about the replies on this comment, now!