What Is Causing Disparities in C-Section Rates between Black and White Pregnant People?

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Rachel Feltman: Picture two pregnant people walking into the same hospital to give birth. They have identical medical histories and experienced identical pregnancies. They’re seeing the same obstetrician. The only difference between them is that one is Black and the other is white. According to a study of births in New Jersey hospitals, the Black patient would be about 20 percent more likely to get an unscheduled C-section than the white patient.

That number takes into account factors like differences in health status or access to good hospitals and doctors. Without controlling for those variables, the number is even higher, with researchers finding that Black pregnant people are almost 25 percent more likely to get an unscheduled C-section than their white peers.

C-sections can, of course, save lives. But they also carry all the risks of a serious surgery, so the idea that people might be pressured into having C-sections unnecessarily is troubling enough. The fact that this seems to happen disproportionately to Black people is even more disturbing.


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For Scientific American’s Science Quickly, I’m Rachel Feltman. Joining us today is Adriana Corredor-Waldron, an assistant professor of economics at NC State University and one of the authors of the working paper I mentioned.

Thanks so much for taking the time to talk with us today.

Adriana Corredor-Waldron: Thank you for having me.

Feltman: So I’m curious: You know, as somebody focusing on economics, what prompted you to study C-sections?

Corredor-Waldron: In my research in general I am interested in understanding how public policy changes or shape health care provision and also provider behavior. But specifically to this paper, what we wanted to understand is why Black infants are more likely to be deliver by C-section than white infants—and this is a pattern that you see across the United States.

We have data on New Jersey, so the first thing that we checked is if we can replicate this part—this pattern in New Jersey. And what we find is that, as well as the aggregates in the U.S., but also previous studies that had suggested in different health care systems, we can see the same pattern emerging for this state.

Feltman: Mm, and why is an increase in C-sections troubling from, you know, a maternal and fetal health perspective?

Corredor-Waldron: I want to clarify that this paper’s—what we want to talk about: it’s low-risk mothers getting an unscheduled C-section …

Feltman: Right.

Corredor-Waldron: C-sections among high-risk mothers can save the life of the baby and the life of the mother.

Feltman: Absolutely, yeah.

Corredor-Waldron: But when we talked about C-sections among low-risk mothers, we are basically saying that mothers are receiving a surgical procedure that carries a higher risk for complications, but also in the case of C-section, that is something that is gonna put the mother in a completely different track for future pregnancies. So we are taking low-risk mothers and then performing these discretionary C-section, and then from the next birth on they will very likely need another surgical, or another C-section, procedure.

Feltman: And did you uncover anything that helped explain what’s driving these disparities?

Corredor-Waldron: What we have is very rich data from New Jersey from 2008 to 2017. And we are able to rule out what people might think is driving this racial disparity: we’re able to rule out, one by one, medical risk factors from the birth certificates that include eclampsia, previous C-section, if it—there is a breech presentation, and we fit all this data from [more than] 900,000 birth to a machine-learning algorithm. So the machine-learning algorithm is learning from the decisions that the providers have been making during this time period and predicting the probability that the mother needs an appropriate, or a medical necessary, C-section.

So that’s what we do when we say that we do control for observable medical risk factor for the appropriateness of having a C-section, so even after adjusting for differences among Black and white in their observable medical risk factors, even after adjusting for the hospital that they delivered and this—their socioeconomic characteristic, what we find is from this 25 percent racial gap, controlling for these factors only reduce the gap to 20 percent. And this remaining 20 percent is explained—or it’s [likely] driven by provider discretion.

Feltman: So basically if patients who were essentially identical in terms of their medical history and needs, but one was a white patient and one was Black, went to the same hospital, you found that the Black patient is more likely to be given a C-section.

Corredor-Waldron: Yeah, and even if they see the same physician.

Feltman: Wow, yeah. And what are some other ways that pregnant people of color might be receiving different care than their white counterparts?

Corredor-Waldron: We don’t have the data to answer exactly what’s driving the doctor decision.

Feltman: Mm-hmm.

Corredor-Waldron: What we can say is that it’s not likely due to unobserved risk factors. We do not completely show the full picture that the doctor is seeing at the moment of making that decision.

Feltman: Mm-hmm.

Corredor-Waldron: But what we show is that if we see what happened with the racial gap when the operating room is busy with a scheduled C-section versus when it’s empty, what you find is that this racial gap, it’s only present when the operating room is empty.

Feltman: Mm.

Corredor-Waldron: And what we think that this is showing is that if Black mothers were truly better candidates—and we are not able to capture this through the medical discharge records—then we should see that there is a gap regardless, if there is empty or if busy, but what we are seeing is that it’s not likely due to unobserved risk factors.

Now, if this is coming from a lack of patience from the part of the doctor, a difference in communication styles and cultural difference or if this coming from doctor’s perception of risk, that it differs between Black or white mothers, but we don’t have enough data to—or the right data to answer that part.

Feltman: So when we talk about patience, are we essentially saying that physicians are perhaps quicker to say, you know, “This labor is going too slowly; I would recommend a C-section,” for a Black patient?

Corredor-Waldron: That could be one possibility. Again, we are not able to say from the data what is exactly going on. Another possibility could be we are all reading the [Centers for Disease Control and Prevention] reports on infant—or Black infant mortality …

Feltman: Mm.

Corredor-Waldron: And we have also evidence from previous papers that maternity wards do vary along their perception of risk and how they act on it; so there are some maternity wards that are more reactive—like, they wait ’til there is a complication, and they act on it—and these type of maternity wards, they have a lower C-section rate versus maternity wards that are more, like, proactive—like, “I want to avoid a complication”—and this type of behavior tends to result in higher C-section.

So again, for this, we would need more qualitative data kind of, like, getting into exactly, like, how the doctors make these type of decisions. But let’s put it this way: like, the literature has evidence of both.

Feltman: Yeah, so what needs to change systemically to make maternal health care more equitable?

Corredor-Waldron: Yeah, one thing that comes to mind is promote diversity in the medical profession. So we do find some evidence that the racial gap decreases when there is concordance, meaning when the Black [mother’s] attendant physician is a Black doctor…

Feltman: Mm-hmm.

Corredor-Waldron: … that the racial gap decreases. So there is suggestive evidence, although it’s not statistically significant, that this channel could help us improve these indicators.

Another one is advocates—so ensure that the mothers have an advocate, like a birth doula. Unfortunately, even though the existing evidence show that doulas are good for the mothers in terms of decreasing C-sections, doulas aren’t typically covered by insurance.

Feltman: Mm.

Corredor-Waldron: And this is someone, a third person, that will be advocating for the mother, a person that have seen a lot of births and they know how things should look like, right?

And I think the third one—this is something that regulators have been trying to implement—is value-based payments, where the payment, it’s not based on the number of resources used but on the patient health, how much value we added with this procedure. And this is because we are seeing the discrepancy when it comes to when the operating room is empty versus when it’s busy.

Feltman: Yeah, so basically making sure that there isn’t a financial incentive to promote surgeries that aren’t necessary but rather a financial incentive to make sure everything is being done as simply and helpfully as possible.

Corredor-Waldron: Yeah, exactly. To preserve patient health at the end, that’s what we care.

Feltman: Absolutely. Are you doing any further research on this question?

Corredor-Waldron: We need to publish, first, this one [laughs], but we are also thinking about, “Okay, what other decisions that are made around childbirth?” And one is inductions. We also have the data, so it would be interesting to see if there is any pattern at all between races on how likely it is to get an induction and what are the consequences on the health of the mother and the baby.

Feltman: Awesome. Well, thank you so much for coming on the podcast today.

Corredor-Waldron: Thank you so much for the opportunity. I am really looking forward to spread the message.

Feltman: That’s all for today’s episode. We’ll be back on Friday to hear how AI could help us study the psychology of the dead.

Science Quickly is produced by me, Rachel Feltman, along with Fonda Mwangi, Kelso Harper, Madison Goldberg and Jeff DelViscio. Shayna Posses and Aaron Shattuck fact-check our show. Our theme music was composed by Dominic Smith. Subscribe to Scientific American for more up-to-date and in-depth science news.

For Scientific American, this is Rachel Feltman. See you next time!



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