Harvard’s GenderSci Lab is unlike most university laboratories. The group’s mandate is to interrogate the scientific study of sex and gender; it brings together historians, anthropologists, social scientists, and philosophers. So when the coronavirus crisis reached the US in March, they didn’t have to halt half-completed experiments or scramble to make arrangements for lab animals. Nevertheless, the change wasn’t easy. “We were all struggling with the circumstances of living under Covid and wondering how we would continue to work together,” says Sarah Richardson, a professor of the history of science at Harvard University and the lab’s director. “We wondered, is all the work that we generally do even important in this moment?”
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But sex and gender soon became major issues in the fight against Covid-19. In mid-February, the Chinese Center for Disease Control and Prevention analyzed data from 72,314 Covid-19 patients and reported that men in their sample were almost twice as likely to die as women. This initial result pointed researchers and commentators toward smoking as a reason for men’s relatively poor prognosis, since over half of Chinese men smoke while very few Chinese women do. But as the virus spread across the world and continued to kill men in greater numbers, alternative explanations proliferated, and references to intrinsic female biology—estrogen, the X chromosome—became more common. As of today, among the 53 countries that report their case and death data separated by sex, men account for approximately 51 percent of Covid-19 cases but 58 percent of deaths.
In these frequent appeals to biology, Richardson and her team saw a familiar pattern. They contend that physicians, researchers, and the media have a tendency to focus on biology while underemphasizing the social determinants of men’s and women’s health. While factors like chromosomes and hormones—often captured under the label “sex”—do indeed play a role in health, women and men also experience radically different social environments. Gender, a more amorphous concept that captures a person’s social roles and experiences, has profound implications for health: It helps determine how we are treated by our surroundings and how we treat them in return.
So Richardson and her team decided to investigate what was going on for themselves. “We were like, ‘OK, let’s start looking with a totally open mind,’” she says. But before they could begin, they had to get a better picture of who was contracting, and dying from, the disease. Yet data sets that track Covid-19 cases and deaths by sex, age, and other demographic factors are hard to come by. “We began by just simply trying to look for the data, and we couldn’t find it,” Richardson says. “So we realized that we would have to assemble it on our own.”
Combing the website of each US state’s public health department, the GenderSci Lab team created the largest centralized repository of sex-separated US Covid-19 data. Last month, they publicly released a data tracker that assimilates that information, in the hope that other scholars can unlock the mystery of why Covid-19 seems to kill more men. Richardson believes that a nuanced approach to this question could not only solve an academic problem but also assist in the fight against the disease. “If we really want tailored interventions that identify vulnerabilities and save lives, we have to be thinking about how these contextual factors are driving these patterns—not, necessarily, whether one is a man or a woman,” she says.
But while researchers across disciplines broadly agree that both social and biological factors are likely to play a role in this disparity, they struggle to identify the most important causes for one critical reason: State data is often inadequate, incomplete, and unreliable. “It’s very hard to make accurate claims when you have terrible data,” says Emily Wentzell, an associate professor of anthropology at the University of Iowa who studies the relationship between gender and medicine. “And the data in the US on who actually has Covid is abysmal.”
What does it mean to say that the SARS-CoV-2 virus attacks men with more ferocity than it does women? As a first step, you might check which group tests positive for Covid-19 more often. As of July 6, the GenderSci Lab’s data tracker told a mixed story: In 33 states, women were more likely to test positive than men, whereas in 16 states, plus DC, Puerto Rico, and the US Virgin Islands, men were more likely to test positive. (Hawaii does not report cases by sex.) Although the margin was generally narrow, some differences were more extreme: In New York, men were about 10 percent more likely to test positive than women, and women in Louisiana were almost 30 percent more likely than men to test positive.
Overall, these figures suggest that women may be more likely to contract Covid-19 than men, which makes some experts wonder whether social factors could be at play. “Women are employed in caretaking professions—including professional childcare and professional elder care—at a much greater rate than men,” Wentzell says, and these professions make social distancing difficult. Women are also more likely to be nurses, who must be in close contact with patients for extended periods of time.
But it’s also possible that these testing differences don’t mean very much at all. “Screening does not the story tell,” says Marcia Stefanick, a professor of medicine at the Stanford University School of Medicine and an expert in men’s and women’s health disparities. “You need to know how good a screening [it is]: Are men and women being screened at the same rate?” People who have mild symptoms, or none, may never get tested, and so test results provide only a small, skewed window onto the true landscape of Covid-19 cases.
And when women do develop symptoms, they may be more likely than men to proactively seek testing. “Women tend to seek more health care than men in response to health issues that they have,” says Kathryn Schubert, president and CEO of the Society for Women’s Health Research. “They’re more likely to have a doctor that they see for routine care, and they’re more likely to have seen a doctor recently. So they already may be in the health care system and may be more attuned to their current health status.”
Ultimately, it’s hard to tell whether women’s preponderance among positive cases means they are more likely to get ill—or simply more likely to get tested. And since very few states track the occupations of the people who are coming down with Covid-19, it’s also difficult to evaluate how exposure in professional environments, like hospitals or nursing homes, might intersect with gender.
On the other hand, Stefanick says, “deaths are definitely very helpful” for understanding sex-related differences in Covid-19 outcomes. While some Covid-19 deaths may be misclassified, hospitals, where most Americans die, currently test their patients for the novel coronavirus. Most of those deaths are probably captured in the data, whereas Covid-19 cases among the living are far more likely to be undercounted.
At a first glance, GenderSci Lab’s death data as of July 6 also looked mixed: In 12 states, women were more likely to die of Covid-19 than men as a fraction of the total population. These differences could be dramatic—while the data showed that women were around 10 percent more likely to die than men in Massachusetts, men were over 40 percent more likely to die in nearby New York, which saw the most severe Covid-19 outbreak in the US so far.
But death rates may also give a distorted impression. The novel coronavirus is a more vicious killer among the elderly, and women are more likely than men to reach an advanced age. To compensate, the GenderSci Lab team used national statistics for the numbers of men and women who have died of Covid-19 in each age group to adjust their data—this way, they could compare the death rates of men in their sixties against those of women in their sixties, and so on.
The team had enough data to apply this procedure for 43 states, and, although the margin varied, this time they found a stable pattern: In every one of those states, men were more likely than women of the same age to die of Covid-19.
While inconsistent testing and differences in exposure might explain sex differences in the number of cases, there is no single, obvious answer to why Covid-19 takes a disproportionate toll on men.
Richardson and her group initiated their project in response to what they saw as an overemphasis on biological explanations. Speculation about the role of hormones, in particular, has become widespread enough that some institutions are experimenting with giving estrogen patches and progesterone injections to male patients, on the assumption that these hormones may be protective.
On a purely theoretical level, this theory makes some sense: Many of the cells that make up the immune system have estrogen receptors, which means that they can detect and respond to the presence of estrogen in the bloodstream. Depending on their type, immune cells will proliferate, dwindle, change their activity, or produce more or less of certain proteins when exposed to additional estrogen—and these changes could make for a more powerful immune system. And researchers at the University of Iowa have demonstrated that female mice who had their ovaries removed (and so had much lower levels of estrogen) are more susceptible to the coronavirus that causes SARS, which is closely related to SARS-CoV-2. But no studies have yet established a direct link between estrogen and Covid-19 severity in rodents, not to mention humans.
Wentzell isn’t surprised that scientists and the media might gravitate toward hormone levels as an explanation. “Both men and women have testosterone and estrogen, but we call testosterone the male hormone, estrogen the female hormone,” she says. “Our mythologies about what those hormones do to you as a person are fundamental to our ways of understanding how men and women fundamentally are,” she says. People so strongly associate hormones with sex that they immediately seem like good explanations for differences between men’s and women’s health.
Stefanick also finds a hormonal explanation unlikely. It simply doesn’t make sense, she says, “because lots of the deaths are post-menopausal aged women who have low estrogen.” In the population hardest hit by the epidemic—the elderly—hormone levels vary much less between men and women than they do for younger people.
Other biological factors may play a role, but, as of yet, theories outnumber high-quality studies. Stefanick, for her part, believes that chromosomes have attracted too little attention. Much like in the case of hormones, “people have this misconception that the X chromosome is a female chromosome,” she says. “It’s not—men and women have X chromosomes. But women have two of them. And there’s a whole bunch of genes on that X chromosome that are part of the immune system.”
Women do tend to have stronger immune systems than men, and they are far more likely to develop autoimmune diseases, disorders in which the immune system becomes excessively active and starts to attack the body’s own, healthy cells. But a strong immune reaction is not necessarily beneficial for fighting off the novel coronavirus. Some patients may be dying from cytokine storms, which occur when the body mounts an overzealous response to a disease and wreaks havoc on its own cells. So far, no studies have proven a link among the X chromosome, immune response, and Covid-19 mortality rates.
Other biological theories have centered around ACE2, a protein that the virus uses to gain entry to and hijack cells. In a recent study led by a team at the University of Groningen in the Netherlands, researchers observed higher levels of ACE2 in men than in women—but all of their subjects had heart failure, so the study’s relevance to Covid-19 patients is unclear. And the gene for ACE2 is located on the X chromosome, which might suggest that women should have more, not less, of the protein. “There is conflicting data as to how ACE2 is playing a role” in this sex difference, says Garima Sharma, an assistant professor of medicine at the Johns Hopkins School of Medicine.
In the end, chromosomes, hormones, and protein levels may not even be the most promising explanations for mortality differences. Some researchers are currently seeking an explanation in the link between a patient’s comorbidities—preexisting conditions like heart disease, chronic obstructive pulmonary disease (COPD), type 2 diabetes, or obesity—and the severity of their illness. (In the US, obesity is more common among women, while heart disease, diabetes, and COPD predominate among men.)
Although these diseases manifest biologically, they speak to the ways in which “living with a certain kind of gender performance is encoded in your body,” Wentzell says. In other words, gendered behaviors, like working certain jobs or following particular diets, can have profound impacts on biology. “And this is because of cultural assumptions that men should act in a certain way,” she continues. “Men in many different cultures are more likely to engage in risky behaviors including smoking. They’re less likely to engage in preventative health care and slower to seek emergency care. And they also tend to be worse than women at controlling chronic conditions like diabetes and hypertension. And these all have to do with cultural pressures to act as if you are invulnerable.”
Heather Shattuck-Heidorn, an assistant professor of women and gender studies at the University of Southern Maine and assistant director of the GenderSci Lab, has seen these dynamics play out in her personal life. “My husband is a freight train conductor, a super blue-collar job, and he brought a salad into work one day,” she says. “And he got made fun of in the break room for eating salad. All the guys were questioning his masculinity, his sexuality.” Her experience illustrates one way that gender could set off a cascade of risks: A lifetime of unhealthy dietary choices could make a person more vulnerable to heart disease and diabetes, which in turn may worsen a case of Covid-19.
But these comorbidities, too, have biological roots. “You can’t say that heart disease is a strictly gender-related illness,” Shattuck-Heidorn says. Although lifestyle factors like diet and smoking are the most reliable risk factors for heart disease, estrogen also appears to play a protective role: Women are much more likely to develop heart disease after they go through menopause and their estrogen levels decrease.
And to make the issue even more complex, gendered behavior can even play a role in risk for infectious diseases like Covid-19. A survey from the National Bureau of Economic Research published in June found that men were less likely to view Covid-19 as a serious health risk and less likely to comply with public health rules, like washing their hands and staying home. “American leaders like Trump and Pence have been notable exceptions globally for their refusal to wear a mask,” Wentzell says. “That has very much been a statement, and I think a gendered one, that a tough, strong man, a leader, doesn’t wear a mask.” (Both politicians have recently reversed their stance on mask-wearing.)
Ultimately, the biological and social causes of diseases, including Covid-19, are likely inextricable. To emphasize this idea, the GenderSci Lab team does not use the words sex or gender separately but instead deploys the neologism gender/sex. At this point, researchers don’t yet know enough to say whether men die more frequently of Covid-19 because of their sex or because of their gender, and a question that depends on that dichotomy might not even have an answer.
While the members of the GenderSci Lab team were interested to see that their new tracker shows a mortality difference favoring women in almost every state, another feature of the data drew their attention: the substantial variation among states in those differences. Adjusting for age, men are almost twice as likely as women to die in states like New York and Texas, whereas the death rates are nearly identical in Idaho and South Dakota. For Shattuck-Heidorn, this suggests that social factors play a bigger role than biology—if biology is to blame, then the ratios should be more uniform. “Maybe there is some aspect of sex-linked biology playing into this, but it’s looking like it’s being swamped by contextual social factors,” she says. “The variability in death rates is immense.”
Other scholars think the overall pattern of greater male deaths is more meaningful. “You still see this one phenomenon make it through all that variability,” says Stefanick. “It’s passing my consistency test.” Of course, a consistent state-to-state pattern could still be primarily caused by social factors, since the states are culturally similar in many ways.
But public health data collection is a decentralized process run by individual state health departments, so comparing states can be difficult. “States follow radically different systems of how data is collected and reported,” Shattuck-Heidorn says. For Schubert, these inconsistencies make it impossible to say whether the variation among states is meaningful. “At the end of the day, if we’re comparing apples to oranges, it’s not going to make a difference,” she says. “It has to all be done in a collective, standardized way.”
And the data isn’t just incomparable from state to state: It is also insufficiently detailed. Researchers like Richardson and Shattuck-Heidorn desperately want data that not only tracks deaths by sex, age, comorbidities, and other factors separately, but also records how those variables overlap. To test whether heart disease might explain the sex difference in Covid-19 deaths, a scientist would want data about how many men and women who died of Covid-19 also had heart disease. Just knowing the numbers of men and women who died of Covid-19 and, separately, how many people with and without heart disease died of Covid-19 wouldn’t be enough to link the sex difference in deaths to heart disease.
But while some states do track comorbidities, they generally don’t divide up that data by sex. Similarly, it is extremely difficult to evaluate whether race, occupation, and age play into the sex differences in Covid-19 case and death rates because most states also don’t record how those attributes interact with sex. “Our current frustration is that we cannot see sex-disaggregated data by age, by race/ethnicity, by comorbidity, or by occupation,” Richardson says. “We want that so much. And we cannot see it.”
Sharma has similar concerns. “I truly want to see—once you control for hypertension, once you control for chronic lung disease, once you control for diabetes, once you control for obesity, once you control for cardiovascular disease or myocardial infarction, once you control for heart failure, once you truly control for smoking and all other high-risk behaviors—if you control for all of that, is there still a sex-specific or a sex-dependent case-fatality rate?” she wonders.
Even the labels of “male” and “female” conceal a great deal of complexity. A 2016 report estimated that 0.6 percent of the US population identifies as transgender, and arguments about hormones and gendered behavior that apply to cisgender people may not be as relevant to that group. But no state has offered more detailed information about the gender identities of their Covid-19 patients than a “male/female” binary label. “We are talking about people ascribed male or female, attributed male or female, by public health agencies,” Richardson says.
Interestingly, about 5 percent of individuals are categorized as unknown in some state data sets, according to Richardson. “We don’t know how to interpret that,” she says. Perhaps these individuals are nonbinary—or perhaps that data is simply missing too.
The data is getting better, albeit slowly; New Jersery just started reporting cases and deaths by sex last week, and Georgia now provides an anonymized spreadsheet that includes the age, sex, race, and county of each Covid-19 death, as well as whether the person had a preexisting chronic condition. This week, the GenderSci Lab will release a Covid-19 “data report card” that will rate the quality of the data coming from each state and, with any luck, convince lagging states to improve their data.
There may be ways of getting at answers without waiting for public health departments to produce better data. Shattuck-Heidorn went back to studies from the previous coronavirus pandemics, SARS and MERS, and found a pattern that she predicts will repeat itself with Covid-19. “I looked deep into that data and saw that they, too, had an initial sex difference that was then later explained by the fact that men are on average more unhealthy than women,” she says. For example, researchers in Taiwan analyzed data from the MERS epidemic, in which men also appeared more likely to die than women, and found that this difference disappeared once they controlled for age and preexisting conditions. But this study was conducted in 2017, five years into the MERS epidemic, when high-quality data had become available. It is not yet clear how long we will have to wait for similar Covid-19 data.
For now, Covid-19’s differential impact on men and women remains difficult to explain and resolve. Shattuck-Heidorn worries that ignoring this conundrum could hamstring the public health response to the pandemic. Deborah Birx, the White House’s coronavirus response coordinator, urged early in the pandemic that men, in particular, should get tested for the virus. “It seems like a really crude way to do public health messaging for risk, if it is actually not male versus female that’s the most important factor,” Shattuck-Heidorn says.
Richardson, too, believes that we may miss important opportunities to push forward the Covid-19 response if we focus too myopically on biological sex differences. “There’s great promise in reducing these disparities if we can understand how those socially relevant and demographic variables are driving this pattern,” she says. “It deeply disturbs us to think of panicked clinicians putting estrogen patches on men.”
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