Suppose I told you that research shows that the ideal C-section rate — the lowest rate compatible with the lowest rates of perinatal and maternal death — is 75%.
You’d balk, right? That couldn’t possibly be true.
Suppose I told you that research shows that the ideal C-section rate is 15%?
Most people, particularly non-obstetricians, would probably nod their heads in agreement. That sounds about right to them, confirming what everyone already “knows,” that that C-section rates in industrialized countries are “too high.”
Now let me tell you the truth:
There is no more evidence for an ideal C-section rate of 15% than there is for an ideal C-section rate of 75%. Indeed, there’s no evidence at all for ANY ideal C-section rate, a fact that has been acknowledged by the World Health Organization. Buried deep in its handbook Monitoring Emergency Obstetric Care, you can find this:
Although the WHO has recommended since 1985 that the rate not exceed 10-15 per cent, there is no empirical evidence for an optimum percentage … the optimum rate is unknown …
[pullquote align=”right” color=”#c94242″]There no evidence for an ideal C-section rate of 10-15% because no industrialized country with low levels of perinatal and maternal mortality has a C-section rate of 10-15%.[/pullquote]
So why did the World Health Organization recently reaffirm its commitment to a C-section rate no higher than 10%?
The answer is white hat bias.
As I explained recently, white hat bias was first described in reference to obesity research, including purported preventive effects of breastfeeding on subsequent obesity. White hat bias is a form of confirmation bias, the natural tendency of people to accept information that confirms what they believe. Confirmation bias is why Tea Party members watch Fox News. They want to have their beliefs, prejudices, and wishes always confirmed, never challenged.
White hat bias is confirmation bias in service of what are seen as laudable goals:
‘White hat bias’ (WHB) [is] bias leading to distortion of information in the service of what may be perceived to be righteous ends… WHB bias may be conjectured to be fuelled by feelings of righteous zeal, indignation toward certain aspects of industry, or other factors.
White hat bias leads scientists, doctors and public health officials to substitute what they fervently believe for what the actual scientific evidence shows. For example, obesity researchers, doctors and public health officials routinely claim that normal to low BMI is “healthiest.” But the scientific evidence shows, and has always shown, that people with higher than normal BMI, overweight but not morbidly obese, are the people who live the longest. So why don’t scientists, doctors and public health officials advise people that being slightly overweight is healthiest? Because white hat bias leads them to ignore the scientific evidence in favor of what they deeply believe: being overweight must be bad for your health.
Their motives are pure. They ignore what the scientific evidence shows because it doesn’t comport with what they are absolutely, positively certain must be true. Moreover, they believe, with some justification, that the current US epidemic of morbid obesity (which isn’t healthy at all) is the result of corporations placing profits ahead of creating healthy food options.
But if science teaches us anything it’s that what we believe may be very different from the truth. Paraphrasing Thomas Henry Huxley: The highest duty of scientists lies in submitting to the evidence however it may jar against their inclinations.
The problem of white hat bias in regard to C-sections is, if anything, worse than the problem of white hat bias in obesity research. Everyone “knows” that the C-section rate is too high despite the fact that the existing evidence for this belief is circumstantial at best. It goes something like this: if historically high C-section rates don’t lead to historically low mortality rates, there must be too many C-sections. In other words, since perinatal and maternal mortality rates haven’t dropped remarkably as the C-section rate has increased remarkably, those increases C-sections were unnecessary.
The belief that there is an ideal C-section rate, and that it is considerably lower than the C-section rates in contemporary industrialized countries is white hat bias at its most basic, resting as it does on other deeply held beliefs: The cost of health care is too high; we need to find a way to rein it in. Midwives are cheaper than obstetricians; we need to find a way to employ more of them and less obstetricians. C-sections are surgery; we should always avoid surgery whenever possible. But regardless of the pure motives of many of those promoting an idea C-section rate, their beliefs are a reflection of their biases and thoroughly ignore the scientific evidence.
As it happens, I also believe that the C-section rate is too high. I say this as a clinician who had a 16% C-section rate (and 0% forceps rate) during my years of private practice. But there’s a difference between what I might believe and what the scientific evidence actually shows.
There is simply NO EVIDENCE that a C-section rate of 10-15% is ideal because NO industrialized country with low levels of perinatal and maternal mortality has a C-section rate of 10- 15%! Indeed, the average C-section rate for countries with low rates of perinatal and maternal mortality is approximately 22%.
That’s an exceedingly inconvenient fact for those arguing that an ideal C-section rate of 10-15% will yield low levels of perinatal and maternal mortality. It’s just like the inconvenient fact in obesity research that those who are healthiest don’t have normal BMIs, but are actually overweight. However, as Neil de Grasse Tyson has noted:
The good thing about science is that it’s true whether or not you believe in it.
That applies equally to scientists as well as to purveyors of pseudoscience.
There is no scientific evidence for an ideal C-section rate and certainly no evidence for a C-section rate of 10-15%. Anyone who tells you otherwise, including the World Health Organization, probably has his, her or its heart in the right place, but that doesn’t make it true. It makes it white hat bias.
