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If I objectify you, will it make you feel bad enough to objectify yourself? On shopping, sexiness and hormones.
When I was younger, periods were not a fun time, and I was plagued with dysmenorrhea, which is a fancy term for really bad cramps. In high school, I would often take 1000 mg of ibuprofen every four hours to alleviate symptoms to get through all my classes, band, sports practice, and homework (what, it took you this long to realize I was, and am, a dork?).
After having my daughter in 2008, and the thirteen months of lactational amenorrhea that followed it (lactational amenorrhea means absence of periods due to lactation), my periods resumed. Pain during my periods has almost totally ceased, but I have noticed more cycle-related variation in emotion. In particular, my patience and tolerance for rude behavior, and my tendency to cry sentimentally at even the lamest greeting card, skyrocket in my premenstrual phase. I already have low tolerance for rudeness, and I already cry easily. But something about progesterone decline — which is a normal process towards the end of ovulatory cycles — seems to make it harder for me to repress these behaviors in order to fit in culturally with those around me.
I tell this to you to say, I don’t doubt that hormones, and hormonal variation through the cycle, plays some role in variation in female behavior and emotion. And I find this kind of work inherently interesting. I hate to repeat myself, but you will find echoes of my structural and methodological concerns with evolutionary psychology in this post as well.
Durante et al (2011) observe that women spend more money on their appearance than men, and claim that this sex difference is cross-culturally consistent (I wonder, is this consistent across cultures without money?). In order to understand this sex difference, they wish to see whether spending or shopping behavior is dependent on cycle phase. Therefore the authors hypothesize that women choose sexier clothing during ovulation — “even if the women themselves are not consciously aware of this biological fact” (Durante et al 2011: 922), a problematic turn of phase if I ever saw one, but I’ll get to that later. They also consider the effects of priming a shopping woman with images of attractive women and hypothesize there is a greater effect of this priming on high-fertility women.
The participants were female undergraduates and were compensated with course credit or money. The authors claim the participants had no idea the study had anything to do with the menstrual cycle, but the participants had to use LH strips at midcycle to see when she was ovulating (this is a urine test to check for a luteinizing hormone peak, which comes before ovulation).
Here’s the important part, for me:
“The first urine test was scheduled 2 days before the expected day of ovulation. If an LH surge was not detected, women came back each day until an LH surge was detected or six tests had been completed, whichever came first” (Durante et al 2011: 924).
Here are my questions: what is 2 days before the expected day of ovulation? The follicular phase — that’s from menstruation to ovulation — is the most variable phase of the menstrual cycle (Fehring et al. 2006; Lenton et al. 1984). I wonder how many ovulations they missed because of this. Perhaps even worse, how many participants had six LH tests and didn’t have a detectable LH surge? It sounds like they were included in the project. But, they either ovulated before the authors started testing, or they had an anovulatory cycle. That means the authors were including participants in their study that weren’t ovulating… in a study of behavior during ovulation.
Participants viewed a made-up shopping website on a high-fertility (near the LH surge) and low-fertility (about eight days later) day, where they had to select ten items they would like to buy that day. They were randomized into two groups: one shown a site featuring casual clothes, the other featuring clothes and accessories. The clothing on these made-up sites were “pretested to be sexy” (Durante et al 2011: 925). While that is a phrase I never expected to write on this blog, the separate validation they did to determine sexy versus nonsexy clothing seems fine.
Hypothesis 1: Near ovulation, women should be more likely to choose sexier and revealing clothing and other fashion items rather than items that are less revealing and sexy (Durante et al 2011: 923).
Women chose a greater percentage of sexy clothing and accessory items near ovulation: 59.8% ± 21.6 during ovulation, 51.3% ± 22.4 during low fertility. This was a statistically significant difference, but they did a repeated measures ANOVA, and I don’t understand why they didn’t do a paired t-test. Further, statistically significant or not, I question how meaningful it is when the averages are so close and the standard deviations almost completely overlap.
H2: Ovulation should lead women to be especially likely to choose sexier products when women are primed to compare themselves to attractive female rivals (Durante et al 2011: 924).
H3: There should be no differences in product choice between ovulating and nonovulating women when women are primed with unattractive women or men (Durante et al 2011: 924).
Follow-up studies primed sub-sets of participants (so a different cohort, same recruitment methods as above) to think about 1) attractive local women, 2) unattractive local women, 3) attractive local men, 4) unattractive local men. They did this by showing photographs of people who they claimed to be local and asking participants to rate their attractiveness.
When primed with attractive women, the percentages of sexy items chosen were 62.7% for ovulating women and 38.2% for low fertility women (I could not find standard deviations for these values so have no idea how much the two groups overlap). Priming with unattractive women, attractive men, or unattractive men produced no significant difference between low and high fertility women.
H4: Ovulation should lead women to choose sexier products when primed to think about local attractive women who constitute potential direct rivals. However, ovulation should not influence product choice when women are primed to think about women from distant locations because such women do not constitute direct rivals (Durante et al 2011: 924).
The authors used a different method for assessing fertility this time; they asked women their normal menstrual cycle length and counted back from menses to estimate when ovulation would be. So AGAIN, we don’t know how many women actually ovulated in this study, and we don’t know whether a significant portion of women were then grouped in the high-fertility group who shouldn’t have been.
This study is like the previous one in terms of photo priming, but this time the photos were said to be local or distant, and were of women only (so the four groups were local attractive, local unattractive, distant attractive, distant unattractive).
The authors claimed that the relationship between fertility, photo attractiveness and location was “marginally significant,” but the p-value was 0.09. That is, in fact, not significant, as significance is generally only considered under 0.05 unless you cheat and say your study is special and should consider a different limit (they don’t say this in their study).
That said, the only significant effect found of photo priming on high versus low fertility women was in the local attractive women group: high fertility women chose 65.8% sexy items versus low fertility’s 39.1% (I could not find standard deviations for these values so have no idea how much the two groups overlap). These results are almost identical to those found when priming women with attractive women without saying if they are local or not.
How biological are we talking here?
The authors claim a biological cause for the differences found above. And maybe there is, to some extent. But there are two major issues with the authors’ conclusions.
First, there is the major methodological flaw of including women who probably aren’t ovulating in their high-fertility group. Heads up to people who don’t study female physiology: women, even healthy women with “normal” cycle lengths, don’t ovulate every cycle. So if understanding a behavior during ovulation is important to your hypotheses, you need daily hormones on top of that LH test. Then, you know, if you can’t document ovulation, you need to exclude those women from your sample. Oh, and while we’re discussing methods, the authors don’t mention whether the participants were in a relationship or not, or what their sexualities were, or their races or socioeconomic statuses. These are all important to understanding variation in female-female competition (Campbell 2004). And since ornamentation is likely related to honest signals of health, it would be good to know waist to hip ratios, or BMI, or facial symmetry (Streeter and McBurney 2003) (hello, I’m handing someone a dissertation here! Just remember to cite me correctly).
But the second issue relates to the theme I saw throughout this paper, that changes in mood or choice behavior due to ovulation or presence of attractive women is a “biological fact.” Female-female competition is certainly found within human behavior, and behavior changes through the menstrual cycle. But is it fair to call these behaviors strictly biological, or should we have a more nuanced understanding of the interaction between biology and culture?
There are alternative cultural theories out there. Objectification theory proposes that there are consequences to living in a culture that sexually objectifies women: when women are continually appraised based on their looks, it leads to a disconnect between their body and individual (Moffitt and Szymanski 2011). This disempowers women and leads to them feeling as though their bodies exist for the pleasure of others. And if this is what women learn they have to offer others, and they seek affirmation, praise or attention from those around them, it makes sense for women to compete around attractiveness, particularly sexiness.
I would posit that shopping, particularly when primed with the image of an attractive woman, is a kind of objectification. So really, what Durante et al (2011) are measuring are the results of objectifying their study participants. Under these circumstances, a woman is more likely to start treating herself as an object to be evaluated on the basis of her appearance, so it makes sense that she would choose sexier clothing, in an effort to produce a culturally-appropriate, attractive body.
As the study stands, there is no way to parse out the impact of biology or culture — and many cultures encourage objectification, female-female competition and female attractiveness towards men. As for how that interacts with high versus low fertility samples… that’s the interesting part of this paper. If we can trust how the women are parsed. Which we can’t, since some of the high-fertility sample might not have been ovulating.
These high heels are made of deer antlers
|Antler booties from Camilla Skovgaard.|
The authors also seemed enamored with the idea of comparing their female participants to male animals. Twice they mention the idea that they want to determine whether sexy clothing is analogous to a peacock’s tail, a deer’s antlers, or a lion’s mane (really). These three examples, according to the authors, reflect a courtship function, a same-sex competition function, or both functions respectively. The authors go on to say that their results suggest that sexy dressing in women is like deer’s antlers, or, a same-sex competition function.
First, since when are a deer’s antlers only a same-sex competition function? Second, doesn’t it say something that they couldn’t find any examples of this kind of display in a female animal? This begs the question of why female humans do so much more displaying and maintenance of their appearance compared to other female animals, and again, this suggests interactions between biology and culture (Smuts 1995).
We can spin all the stories we want to explain why many human females make efforts to be physically attractive. And I do think Durante et al (2011) are on to something here as, despite methodological concerns they did find differences in high- and low-fertility choices. But if we continue to do this research on undergraduates in western contexts without sufficient hormone analysis, I’m unsure that its meaning extends beyond the participant pool.
Campbell, A. (2004). Female competition: Causes, constraints, content, and contexts Journal of Sex Research, 41 (1), 16-26 DOI: 10.1080/00224490409552210
Durante, KM, Griskevicius, V, Hill, SE, Perilloux, C, & Li, NP (2011). Ovulation, female competition, and product choice: hormonal influences on consumer behavior Journal of Consumer Research, 37 (6), 921-934
Fehring, R., Schneider, M., & Raviele, K. (2006). Variability in the Phases of the Menstrual Cycle Journal of Obstetric, Gynecologic, Neonatal Nursing, 35 (3), 376-384 DOI: 10.1111/j.1552-6909.2006.00051.x
Lenton EA, Landgren BM, Sexton L, & Harper R (1984). Normal variation in the length of the follicular phase of the menstrual cycle: effect of chronological age. British journal of obstetrics and gynaecology, 91 (7), 681-4 PMID: 6743609
Moffitt, L., & Szymanski, D. (2010). Experiencing Sexually Objectifying Environments: A Qualitative Study The Counseling Psychologist, 39 (1), 67-106 DOI: 10.1177/0011000010364551
Smuts, B. (1995). The evolutionary origins of patriarchy Human Nature, 6 (1), 1-32 DOI: 10.1007/BF02734133
Streeter, S. (2003). Waist–hip ratio and attractiveness New evidence and a critique of “a critical test” Evolution and Human Behavior, 24 (2), 88-98 DOI: 10.1016/S1090-5138(02)00121-6
Yesterday I submitted a book chapter and a journal manuscript. I have two substantial blog posts I’m working on, but neither will be ready for this week. However, I have been slowly accumulating Posts of Awesome that I’d like to share. I want to highlight people, writing, and topics that need and deserve more attention in the science blogosphere. I mention a lot of these things on Twitter, but I know a lot of my followers don’t use Twitter. So here goes.
If you have any interest in pregnancy, labor and birth, I do hope you’re reading Science and Sensibility. S&S is a evidence-based blog written by practitioners and scientists, sponsored by Lamaze International. I really like their more technical, informative posts on labor and birth, and today’s post on positioning during the second stage of labor is a winner. The writing is always accessible for layfolks, yet still provides great information for scientists and medical folk.
Remember that Wax et al (2010) article showing homebirth had a mortality rate three times higher than a hospital birth (and the sensational Lancet editorial)? A lot of folks came down hard on the article when it first came out, myself included, but two more pieces came out yesterday that call into question the authors’ conclusions. The first issue is that there were actual mathematical errors in the data (meaning, the data was probably entered into an excel sheet incorrectly), the second is that they fundamentally did the meta-analysis wrong. Wrong. As in, according to one statistician who had no stake in the story or topic, so wrong as to overlook all its other problems.
A few more spicy tidbits: cosmetic breast surgery is on the rise, and one county in Florida has a 70% cesarean rate. Seventy. Percent. Due to some smart marketing and bad decisions, a treatment to prevent pre-term birth that used to be affordable is now more expensive than gold.
Finally, this is sort of ladybusiness, but as Dr. Isis points out, it should really be family (or even just human) business: Why it’s alright to not be your mother, a guest post on AGORA.
The reverberations from Jesse Bering’s post on homophobia as an adaptation continue. And the responses have been brilliant. I especially love Jeremy Yoder’s take over at his blog, Denim and Tweed: An adaptive fairytale with no happy ending.
And then today, DeLene Beeland shared this great post on Twitter: How to Queer Ecology: One Goose at a Time over at Orion Magazine. This is a beautifully-written, thoughtful takedown of the naturalistic fallacy.
Other things to read right now
Danielle Lee has two great pieces worth reading (and I found them both because of Greg Laden): an article on the contribution of Henrietta Lacks, and the Black community, to cell culture, and a profile on Danielle in a natural hair series at Essence.com.
I read this article today by Gina Trapani on her work to make the technical world more friendly to women and other underrepresented or new folks.
A piece on Impostor Syndrome at SciAm (behind a paywall). I don’t want to pathologize all underrepresented groups in science (because frankly, these feelings make sense in the context of environment, even if it’s desirable to move beyond them), but issues around impostor syndrome resonate with me.
Things I wish I didn’t have to link to
Our amusement with Charlie Sheen just demonstrates how little we care about violence against women — especially certain kinds of women. Read The Disposable Woman.
Skepchick Rebecca Watson shares some of her hate mail, and why she doesn’t feel like internetting today: Why I deserved to be called an offensive bitch.
Pat Campbell reposted a twelve-year-old manifesto on gender and education that still holds true: The Gender Wars Must Cease.
Some LOLz and some cutes: a section I added because the last three links were so depressing
This first link doesn’t exactly bring the LOLz, but is an enjoyable read: Female Science Professor continues her series on Academic Novels.
Wax, J., Lucas, F., Lamont, M., Pinette, M., Cartin, A., & Blackstone, J. (2010). Maternal and newborn outcomes in planned home birth vs planned hospital births: a metaanalysis American Journal of Obstetrics and Gynecology DOI: 10.1016/j.ajog.2010.05.028
Editorial staff (2010). Home birth–proceed with caution. Lancet, 376 (9738) PMID: 20674705
If you haven’t seen it yet, or just want to relive it, our women in science blogging panel is now available for viewing:
Key highlights: when I told the audience about how I squatted over a toilet to birth my baby. Oh, there was also a lot of great feminism in there too.
When I was in college, my favorite hangout was the basement of the Harvard Book Store, where they had the used books and cheap remainders (they were also across the street from my freshman dorm, Wigglesworth, and yes, that is a most excellent name). I worked my way through several sci-fi and fantasy series, and got nearly all my Women’s Studies books, because of that one lovely room.
One night in my freshman year I was browsing the philosophy section with a new boyfriend, a person with whom I often felt inferior and less-educated. I saw an author name on the spine of an old hardcover and, hoping to impress the boyfriend, pointed it out. “Hobbes Machiavelli, I’ve read stuff by him,” I said. I arched my eyebrows with what I hoped was an air of intelligence.
The boyfriend, and a nearby witness, both turned towards me. “Hobbes and Machiavelli are two different people,” he said slowly.
As a blush crept up my face, I realized several things: the excerpt of “The Prince” I had barely skimmed in high school was by Niccolo Machiavelli, Hobbes was a totally different dude, and my boyfriend thought I was a posturing idiot.
It’s a good idea to know what you’re talking about before opening your mouth.
* * *
These days, if I don’t know the answer to something, I don’t try to fake it. Recently, a Twitter follower suggested I write on this New Scientist story and the empirical article upon which it was reporting on brain activity, hormones and Premenstrual Dysphoric Disorder. As I am not an expert on issues of the brain, rather than try to be I enlisted brilliant neuroscientist Scicurious to do tag-team blog posts where we could each cover the material where we had expertise. I had a few thoughts about the way the New Scientist article author framed the study, and about the hormone analyses. So I’ll talk about that, and Sci will cover BRAINZ in this post.
What is this study about?
Rapkin et al (2011) seek to understand why a minority of women experience Premenstrual Dysphoric Disorder (PMDD), a suite of premenstrual behaviors that include severe and debilitating irritability, depression and anxiety. They used PET scans to look at brain stuff (cue Scicurious) and also looked at hormone concentrations to see if the reproductive hormones that decline in the premenstrual phase had anything to do with it. They found no difference in hormone concentrations between control and PMDD women, but did find variation in cerebellar activity by menstrual phase. You need to read Scicurious’s take on this, because she provides important background and context to the study of the cerebellum for mood.
The New Scientist piece makes a lot of the potential effect of progesterone on GABA receptors in the brain, but as far as I can tell the article itself does not measure GABA receptors. Progesterone, allopregnanolone and GABA are all interrelated and important chemicals when it comes to mood (Concas et al 1998), but like I said, since the study didn’t actually look at GABA, I’m not going there. Sci has also made some important points about this issue, and on what the study authors found (which is admittedly cool) with what they discuss around GABA (which might be a wee bit of a stretch).
Nits to pick with New Scientist
Zukerman, the author of the New Scientist piece, begins her piece, entitled “Why women get anxious at ‘that time of the month’” with this:
“Is it that time of the month? These are the words no man should ever utter. How about this for a diplomatic alternative: “Are your GABA receptors playing up?”
You may be spot on. It seems that these brain cells are to blame for some women’s monthly mood swings.
Many women feel a little irritable before menstruating, but up to 8 per cent suffer extreme symptoms, including anxiety, depression and fatigue.”
There are a few things that trouble me about this. First, without citing any actual incidence of this symptom, the author claims that many women suffer from irritability before their period. This just perpetuates the idea that irritability is a common premenstrual trait, when the premenstrual phase is an incredibly variable period. This is despite the fact that at most only eight percent of women actually get these symptoms to the point that they are debilitating (the two studies the study authors cite give a 5% and 8% incidence, so 8% may be high).
From a public health or science research perspective, eight percent of reproductively aged women is a pretty significant quantity. I absolutely want more research to be done on PMDD and, full disclosure, I’m running some pilot studies to work on it in the future myself. However, these results don’t necessarily translate to women who may just get a little irritable or experience other mild behavioral symptoms before their period.
And that is why both the title and the “Is it that time of the month” joke at the start of the story were misleading. Besides its obvious sexism, where any female behavior that deviates from the pleasing and passive risks eliciting that question, the link here in the mind of a popular reader is that women’s behavior is governed by hormone and brain interactions more generally than the paper actually implies.
So, to reiterate: PMDD impacts maybe eight percent of reproductively aged women (notice that I keep specifically referencing “reproductively-aged women,” which further shrinks the pool of women down to those between menarche and menopause). This is nothing to sneeze at. But this isn’t everyone.
In order to see if there were differences in hormone concentrations between normal and PMDD women, Rapkin et al (2011) took blood on the days of the PET scans: this translated into one follicular phase (first half of the cycle, between menses and ovulation) and one late luteal phase collection (the week or so before the next menses). They found no difference in the mean concentrations of estradiol and progesterone between the two groups, at either time period.
|Table 1 from Rapkin et al (2011). None of these differences between groups are significant according to the authors, but they didn’t report p-values anywhere I could find.|
There are several problems with this. First, the sample size is tiny. I have certainly been known to run analyses with fewer subjects, but the way I and other folks who do hormone work get around this is to sample each individual many more times. When collecting hormone information on reproductively-aged women, for instance, you want to collect a minimum of one menstrual cycle’s worth of data… every single day.
My advisor raised me right, and so I did a power analysis of the data the study authors provided. A power analysis is a way to determine the statistical power of a test. You can do it beforehand to determine an appropriate sample size for your experiment, or afterwards if you didn’t find something statistically significant and don’t know if your analysis was effective. When there are small but important differences between two groups, but the sample size is also small, your statistical test can be insignificant and thus miss that important difference.
Let’s take the hormone and time period that should be the most meaningful: progesterone in the late luteal phase. PMDD women had 5.50 ± 5.27 ng/mL, and control women had 6.76 ± 7.53 ng/mL. If we say that the smallest difference between these two groups that would be interesting is around 6 ng/mL (just splitting the difference between the two standard deviations, but this is pretty generous), then according to my calculations this test only has a power of about 60%. Therefore, 40% of the time a test with a sample size this small wouldn’t catch a potentially important difference between the groups. To put it into more perspective, the standard is to have a power of at least 80%.
What’s blood got to do with it?
|On Fertile Ground, by Peter T. Ellison. Go to the Amazon page to embiggen the image and you’ll see the plastic tube one of the women is holding to collect spit.|
Most people with a clinical background or doing a more clinical collaboration seem to be needle-happy. That is, when they want to measure hormones, they take it out of your arm rather than from the many other places you can get it: blood spots (using a little lancet on your finger), saliva, urine, and feces. This will some day be a blog post in its own right.
Here is the short answer: saliva is very often better than venous blood. Hormones are secreted from their organs in a pulsatile way, meaning they are released in short bursts, which leads to measurements going up and down quickly. Since they circulate in the blood, serum measurements of hormones are likely to pick up this noise. This is yet another reason why only two samples for each of the twenty four subjects is troubling. There are other reasons, related to what version of the hormone you are measuring when getting it from blood, spit or elsewhere, the higher compliance and greater frequency of sampling you can do with saliva, and the fact that you don’t have to stick your subjects or increase their risk of infection.
The only studies looking at variation in hormones across the cycle in menstrually-related mood disorders use blood (Bloch et al 1998, Rubinow et al 1988). The Bloch et al 1998 measures 10 women with PMS and 10 controls using serum every day for a cycle (hooray, every day!) but they measure testosterone, cortisol, and other hormones not comparable to this study. Plus, they are looking at women with PMS, not PMDD, which is a much more broadly-defined syndrome. It would be harder to find a difference between these two groups than controls and women with PMDD.
The Rubinow et al 1988 is old enough that I can’t get it online, the abstract says nothing about how frequently the hormones are measured or the number of women in the study, and I don’t know how strictly they define menstrual disorders (again, as opposed to the rather strictly-defined PMDD).
Variation is the spice of life
My last issue with the hormones is with the two windows during which they measured them. Women were measured in their follicular phase anywhere from 8-12 days into their cycle for the first measurement; then the late luteal phase measurement was 10-14 days after a measured LH surge (which occurs around midcycle).
Here is the kind of variation I see when I measure women’s hormone concentrations every day. What you’re looking at is salivary estradiol (pmol/L) measured daily in over twenty Polish women, aligned by midcycle drop date. The first graph is all the women together, the second is the average and standard deviation.
|Individual Polish women’s estradiol concentrations.|
|Average Polish women’s estradiol concentrations.|
Here is salivary progesterone from the same population, aligned by the end of the cycle. Again, the first graph is everyone individually, the second is average and standard deviation.
|Individual Polish women’s progesterone concentrations.|
|Average Polish women’s progesterone concentrations.|
A few important things to note: this isn’t the same way the study authors aligned their data (though the way I have shown it here is more physiologically meaningful) and the units are different. However, if you look at about the times when the study authors were taking their measurements – mid to late follicular phase and late luteal phase – you see a TON of variation between those days, both within and between women. This is why a single measurement in that general window is, in essence, of no use. You have way too much noise in a single measurement to be able to begin to say anything about differences between groups.
PMDD is very likely related to hormone concentrations – if not in their average values between groups, then in how those hormones differentially impact brain functioning (the brain sensitivity stuff Sci discusses so well). But we won’t know these potential differences if we don’t gather the hormone data correctly. Just because brain scans are cool — and really, they are and I applaud the study authors for doing stuff that I simply cannot do and finding interesting results — doesn’t mean you can give the hormones the short shrift.
Bloch M, Schmidt PJ, Su TP, Tobin MB, & Rubinow DR (1998). Pituitary-adrenal hormones and testosterone across the menstrual cycle in women with premenstrual syndrome and controls. Biological psychiatry, 43 (12), 897-903 PMID: 9627744
Concas A, Mostallino MC, Porcu P, Follesa P, Barbaccia ML, Trabucchi M, Purdy RH, Grisenti P, & Biggio G (1998). Role of brain allopregnanolone in the plasticity of gamma-aminobutyric acid type A receptor in rat brain during pregnancy and after delivery. Proceedings of the National Academy of Sciences of the United States of America, 95 (22), 13284-9 PMID: 9789080
Rapkin AJ, Berman SM, Mandelkern MA, Silverman DH, Morgan M, & London ED (2011). Neuroimaging evidence of cerebellar involvement in premenstrual dysphoric disorder. Biological psychiatry, 69 (4), 374-80 PMID: 21092938
Rubinow DR, Hoban MC, Grover GN, Galloway DS, Roy-Byrne P, Andersen R, & Merriam GR (1988). Changes in plasma hormones across the menstrual cycle in patients with menstrually related mood disorder and in control subjects. American journal of obstetrics and gynecology, 158 (1), 5-11 PMID: 2962499