E (1:56)

Women have been seen as either too kind of variable, hormonally, like, noisy, and therefore bad sources of data, and. Or we have just taken a male body as a standard and used that to produce knowledge for everyone.

D (2:10)

So that's Marina DiMarco. She's a philosopher of science at Washington University in St. Louis. And she told us that over time, scientists and activists realized that there was this huge gap in data for research on women.

B (2:22)

Yeah.

D (2:23)

They started pushing for more inclusive policies, and there were even protests about this in the 1980s and 90s.

C (2:29)

And Congress listened. They passed a law in 1993 requiring researchers to include women and people of color in federally funded medical trials.

E (2:37)

Wow.

D (2:37)

Nice. Now women are in a lot more studies and we study differences between the sexes by enrolling men and women, and then we compare data from each group. But many people say the way we include women in medical research can still get pretty messy.

B (2:54)

Today on the show, how we sort the sexes in medicine and why there's a lot of problems with that. You're listening to Short Wave, the Science podcast from npr.

F (3:08)

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A (4:12)

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B (4:31)

Okay, Aru and Angelo, Today we're talking about sex differences as it relates to the world of medicine, medical care, medical research. And I remember from a previous episode that our colleague Hannah Chin reported learning that sex is hard to define. It can be defined, in fact, by a lot of things, like anatomy or hormones or chromosomes.

D (4:50)

So many things. And Morena says that confusion can carry over into how sex is defined when you're a patient in a doctor's office.

E (4:56)

I've never been to a doctor's appointment where someone checked how many X chromosomes I had or what kinds of gametes I make. As far as I know, like, no one's ever even measured my estrogen or testosterone levels. And yet my clinical treatment is supposed to be based on sex categories.

C (5:13)

And before we go further, we just want to say that we're using women and men in super binary ways because many studies and experts still use these terms even though we know that gender and even sex are not binary.

D (5:25)

That makes sense. Yeah.

B (5:26)

So how do researchers or doctors account for this complexity in sex?

D (5:31)

Well, we kind of don't.

C (5:33)

Nope.

D (5:34)

Metaphorically speaking, our medical system tends to sort people into two buckets, a blue bucket or a pink bucket. And it's really easy to do that. But a lot of researchers say that that might cause some problems.

C (5:44)

The first one is that we might be missing similarities between the pink and the blue buckets. In many cases, there's a lot of overlap, like with height, for example.

G (5:52)

You can look around and you can see, yes, on average, men are taller than women.

C (5:57)

This is Donna Maney. She's a neuroscientist at Emory University.

G (6:01)

But also, as everyone knows, if I say to you, oh, this person is 5, 9, what's their sex? I mean, you might be able to guess, but you're not always going to get that right.

D (6:13)

Right.

B (6:14)

I mean, I'm five, eight, and there are plenty of men who are my exact height.

C (6:17)

Totally. So Donna says ignoring the overlaps between sexes could have real consequences, like in women who experience heart attacks. How so?

D (6:26)

Okay, so the most common symptom of a heart attack, regardless of your sex or gender, is chest pain. But the American Heart Associ says that women may experience a wider, less recognized range of symptoms, like fatigue or indigestion.

G (6:40)

Is that because we have different ways of having a heart attack pathophysiologically, or is it because women present their symptoms in a different gendered way?

D (6:52)

Alison McGregor is a doctor at the Medical University of South Carolina. She spent years looking into women's health and medicine and how it might be different than men's, including whether those differences are why women with heart attacks are treated later than men and die at a higher rate. And at the same time, there's definitely

G (7:10)

crossover between men and women of who has those symptoms. If we could just make it so that way, these are all symptoms that people could present in and then have those be flagged. That's ideal.

C (7:23)

Donna pointed out the same thing. Like this has real life stakes.

G (7:27)

You can imagine that a man might be having a heart attack and he might be having nausea and jaw pain, but he's been told that those are women's symptoms of heart attack. And so that's very dangerous for him because that will delay his treatment.

B (7:40)

This is dangerous for everyone because of the oversimplification of the two bucket system, blue and pink it misses overlaps.

D (7:50)

Yeah, it totally can. And this leads to our second problem. And because when you sort people into two big buckets, you're just going to get averages. And so Marina says that when we do this, we can miss the diversity within those categories. So I'll give you an example. The three of us identify as women, but we might actually be really genetically different. So I can be more similar to a male coworker than I am to the two of you.

E (8:14)

We make a recommendation for all of the pink, and it only actually works for, like a subset of them. As my collaborator Madeline Pape has put it. Like, we're really just moving from a one size fits all approach to a two size fits most approach.

B (8:32)

I think about this all the time. Like when I go to the gym, there are so many different types of bodies. Even if people are the same sex, they can look vastly, vastly different. So averages can only take us so far because at the end of the day, doctors are treating individuals.

C (8:48)

Exactly. Marina also brought this up to us.

E (8:50)

If you have variation in that population or if the population you studied is different from the person that you're prescribing a medication to, there has to be some kind of like, leap or inferential move there.

B (9:02)

Right.

E (9:02)

You're taking a risk.

C (9:03)

And on top of that, there's the issue that some people don't fit into either of those buckets. Like intersex people and trans people who have started gender affirming hormone treatment.

E (9:13)

We reinforce the idea that people come in those two types when in fact we have significant evidence that they don't.

D (9:20)

And Emily, you're not going to believe this. There is another problem with the two bucket system.

B (9:27)

Of course there is. Tell me.

D (9:29)

Yeah, it only lets you ask questions about two buckets. And if you find a difference, then you might think it's about the buckets. But there are lots of other reasons we might see differences between the buckets or between the sexes. And we talked about this with another expert, Sarah Richardson. She says those reasons don't exclusively have to do with your sex, like your weight, your age, your hormones, even if you're taking other medication.

E (9:54)

Women are not only prescribed drugs at a higher rate, but more drugs at the same time.

D (9:59)

Sarah is the director of the Gender Asylab at Harvard, where she works with Marina.

B (10:03)

So we would expect that drug usage is also higher.

D (10:06)

Partially this is because women tend to go to the doctor more often than men do. Like, they just interact with hospitals and health care way more often. Right.

B (10:15)

Like in drug research, we may See differences in outcomes that we think have to do with sex, but actually it could come from a multitude of different factors.

C (10:24)

Yeah. And one of the most controversial ways that this can play out is through sex based drug dosing. Like the idea that women should be taking a different amount of a medication than men. And that's exactly what happened with the drug Zolpidem, which is also known as Ambien.

A (10:39)

You fall asleep fast, stay asleep longer,

D (10:41)

and generally wake without feeling groggy the next morning.

B (10:44)

Ambien works like a dream. Oh, yes, Ambien, the pill that is designed to help people fall asleep.

D (10:51)

Right.

C (10:52)

So there's research showing that on average, Ambien stays longer in women's systems than in men's, which means that a woman might be more sleepy the morning after taking it and could be at risk for driving accidents.

D (11:04)

So in 2013, the FDA actually lowered Ambien's recommended starting dose for women, which was a huge deal.

A (11:11)

Wow.

D (11:11)

Yeah. It's the first and only drug where there is a dose based on your sex. And many people saw this as a huge win for women's health.

C (11:20)

But some researchers pointed out a few concerns with the FDA making this change. One was that, like we talked about earlier, there was still a lot of overlap with how quickly men and women process the drug.

G (11:32)

That does not mean that all women are going to respond the same way to a drug and all men are going to respond another way to the drug. And yet that that's kind of how a statistically significant difference is interpreted.

D (11:42)

It was also not entirely clear what was causing the sex difference. Some people say that more research is needed and even said the lower starting dose could lead to women being undertreated.

E (11:52)

That's wild.

B (11:54)

Given these examples, Ambien heart attack symptoms, it makes me think about how sex is such a problematic variable when it comes to research. Right. Because sex difference is so nuanced, so hot. Take. Should we just not look at sex in medical research at all and maybe just put every everyone together in one big group?

C (12:12)

Well, not exactly. From talking to all these experts, it's really just about being super specific about what you mean when you study sex. Like, if you're studying cervical cancer, your definition of sex will probably focus on anatomy.

D (12:25)

And being more clear will also help us get at what the real problem is. Marina says sometimes the focus on biology actually obscures the fact or distracts from the fact that women aren't always treated the same as men at the doctor's office.

E (12:37)

If you focus on biology as an explanation for differences in outcomes across members of social groups. It naturalizes inequality by putting biology first and assuming that whatever is different about men and women, it's about their bodies instead of about how society treats us.

D (12:54)

And it could be both. So lots of studies show that women's pain is taken less seriously. This really matters for the heart attack issue. Studies as recently as this year show that women who come to the hospital with chest pain get seen by a doctor later than men do for the same symptoms.

B (13:09)

So I want to make sure I have this. All right, you're saying it is still important to include both men and women in medical studies?

C (13:16)

Yeah. To make sure that you're studying a diverse set of people that represents society.

B (13:20)

Yes, but we need to be more specific about it and more inclusive. And if we find a difference, we should think about whether that is because society treats different sexes differently.

C (13:30)

Yeah, pretty much. And some experts have said there's still work to be done. We've been focusing on NIH funded studies, but there's still a lot of research that's funded privately. That's why some people suggest that the policy requiring that women be involved in medical research should be extended to agencies like the FDA that review these studies, and not just limited to the organizations that fund them.

B (13:52)

Okay. And Angela, Dr. Zhang, what kind of medical world do you want to live in that would get around this problem?

D (14:00)

Yeah. So I think we dream of this world of precision medicine where everyone gets exactly the care that's right for them. Right. And know exactly makes up your body and your genes and your hormones. But we're not there yet. And in the meantime, we need to focus on what we know and can do right now. So I can't change your genes yet. I don't have these tests yet, but I can help you get to your appointments, and I can try to make sure that you feel listened to and taken care of.

B (14:24)

Angela Aru, thank you so much for bringing us this story.

C (14:28)

Thanks, Emily.

D (14:29)

Thanks, Emily. It's great to be here.

B (14:31)

If you liked this episode of Short Wave, please share it with a friend. Because we know, based on multiple studies that word of mouth is one of the top ways to grow a podcast. Please and thank you. This episode was produced by Hannah Chin. It was edited by our showrunner, Rebecca Ramirez. Tyler Jones checked the facts. Kwesi Lee was the audio engineer. I'm Emily Kwong. Thank you for listening to Short Wave, the science podcast from N.

A (14:59)

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F (15:30)

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