CDC Data on Declining US Fertility Rate Is Being Used by White Nationalists

The United States Centers for Disease Control and Prevention reported this week that the rate that American babies are being born is below what’s needed to sustain the population. In classic demographical fashion, the report also broke down these statistics by race and state. This common statistical practice spawned some unintended consequences after the data caught the attention of white nationalists, an outcome that critics blame on irresponsible reporting.

"If someone were paranoid about people and white genocide, it would be yet another feather in that cap.

The report showed that the total fertility rate (TFR), for women of all races and origins, is predicted to be below the rate needed to sustain the population (TFR refers to the number of babies 1,000 women can be expected to have over the course of their reproductive lifetimes). Some Twitter users were more interested in the racial breakdown of that information that the CDC included in its report: For white women, there were no states that met the necessary “rate of replacement,” for black women there were 12 states that met that mark, and for women of Hispanic origin, there were 29 states. As public health experts pointed out to Inverse, the report didn’t include the crucial context about racial and socioeconomic inequalities needed to make sense of this data.

Within hours of the report’s release, the alt-right blog Infowars aggregated the Daily Mail’s story on the report, claiming that “experts” say that “the much smaller proportion of immigrant-born women are having more children.” Hateful comments surfaced on Twitter: “we have promoted replacement by primitive societies,” wrote one user; another said, “mission accomplished for the social engineers.” A Twitter user with 44,8000 followers, @RAMZPAUL, wrote: “Our people are losing hope, we need a homeland.”

In short, these statistics and the science behind them were used by some to perpetuate a white nationalist narrative.

Charles Gallagher, Ph.D., an expert on interracial group relationships at La Salle University, tells Inverse that it’s easy for reports like these to be taken out of context. The report did not clearly discuss the underlying social or economic factors behind the racial breakdown of the TFR and includes no discussion section or other contextual information to this end.

“If someone were paranoid about people and white genocide, it would be yet another feather in that cap,” Gallagher says. “Here’s the problem: You can’t really be responsible for how people use social science data. I see in the kind of work I do people have taken stuff I’ve published and taken it entirely out of context. People use it, they manipulate it, they massage it, they misinterpret it, for their own ideological purposes.”

Ashwin Vasan, Ph.D., an assistant professor at Columbia University’s Mailman School of Public Health, says that the intentional “massaging” of data is a hot topic of debate in the public health sphere. The fact that the CDC report failed to mention the nation’s geographical and racial inequities in access to family planning services or quality of care alongside its racial breakdown made the data vulnerable to misuse by “pernicious actors.”

It’s incumbent upon public health activists to head off “massaging,” he argues.

"It’s incumbent upon us to try to stem some of that through additional background and historical context.

“It’s high time that public health as a field, and epidemiology as a field, took some ownership of contextualizing the narrative in some way,” Vasan tells Inverse. “Particularly in this day and age where we see incredible social, economic and racial polarization and division, the notion that we can just put data out there and wash our hands of the implications is probably not correct. It’s incumbent upon us to try to stem some of that through additional background and historical context.”

In today’s charged political climate, it is perhaps no longer enough to present public health data in the straightforward, objective, and traditional demographic style used by the CDC. While the new report includes a “Discussion” section to round up trends in the statistics it presents, it doesn’t delve into the reasons or historical context behind the numbers it describes. If it did, it might have been less easily misconstrued by Vasan’s “pernicious actors.”

"I think one way to avoid the notion that we’re cherry-picking when we do this is to standardize it, to make it a part of every report.

The complex story behind the TFR statistics and the way it breaks down by race, says Gallagher, involves a vast range of reasons why people do or do not choose to have children, from economic stability to health concerns. In an email to Inverse, the author of the report, Brady E. Hamilton, Ph.D., emphasized that the important drivers of this decline in the nation’s TFR are the decline in birth rates (the actual number of live births per thousand people in the population) for teens and in women under 30. This report lists birth rates by state and age group, but it doesn’t place them into context with the TFR trend, which is the type of context that Vasan argues is necessary in these kinds of reports.

The simple act of adding a context section to the front matter of the paper could have gone a long way to potentially shaping how this information was presented. This is already a common aspect of papers published in medical journals, says Vasan, adding that he would like to see this become standard practice in the field.

“I think one way to avoid the notion that we’re cherry-picking when we do this is to standardize it, to make it a part of every report,” he says.

Still, even that wouldn’t change the fact that data in the report is presented as if it exists in a vacuum when, in reality, it will be interpreted according to the ideologies far from the labs at the Center For Health Statistics. With any luck, we’ll see more basic context added to these reports in the future. It may not stop people from cherrypicking facts, but it may make it easier to debunk their arguments in the future:

“Look: If we’re going to describe any kind of racial, demographic or economic or sexual orientation disparities,” says Vasan, “we need to provide basic context as to what prior data tells us about some of the structural inequalities.”

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