The Origin of Medical Myths
My father, a retired physician, used to tell me about one his patients who blamed his doctors for his ills: “I was fine before I came to see you but by the end of my first visit, I had high blood pressure and high cholesterol. What are you doing to me?” His patient was kidding – at least I think he was – but it’s an example of how reasoning can go wrong when an initial event is assumed to cause something that occurs soon afterwards. On the other hand, my father used to joke that his children (especially me) were the cause of his gray hair. As improbable as it was that my father was the cause of his patient’s elevated blood pressure, similar faulty assumptions are the basis of many medical myths.
Insulin Therapy for Diabetes: Prevention or Culprit
I have heard from patients who have diabetes that they would rather avoid taking insulin because they fear it will hasten complications such as amputation of limbs or kidney failure. Never mind that doctors would never knowingly prescribe a medication with a complication rate that exceeds its benefits, but most research suggests that if there’s any long-term effect of careful blood-sugar control in diabetes – which often requires insulin - it is to reduce the risk of complications.
Why would such a myth be so persistent? It is probably based on experience with family or friends who took insulin for their diabetes and later developed these complications. It is certainly true that people with diabetes may have significant problems with circulation that may slow wound healing. And non-healing or infected wounds sometimes require amputation of the involved limb, but this is more common among those with the more severe deficiency of insulin, not just resistance to it. And it is these more severe cases (called type I when the problem is lack of insulin in the body) that require insulin therapy, often years before the complications develop.
So, although the insulin comes first for many patients with diabetes, it is the disease for which insulin is required - and not the insulin itself - that increases the risk of complications. Unfortunately, avoiding insulin therapy because of the mistaken assumption that it may cause complications could actually increase the risk of those same complications.
Cause and Effect: It Seems So Simple
You twist your ankle and now it’s sore. The cause and the effect are straightforward, but in many (or even most) medical situations, a number of factors may complicate matters:
Lack of complete understanding for a variety of common conditions, no cause has been identified. Examples include most cases of high blood pressure, arthritis, and back pain. Yet, human nature demands an explanation, so when the timing seems right, we assume the cause of a problem is whatever preceded that problem. This probably explains why so many people with high blood pressure blame emotional stress or other external factors for a condition whose cause is, in fact, almost always unknowable (at least at the present time).
The chicken-and-egg dilemma. It may be exceedingly difficult to know which factor occurred first. For example, people who have widespread achiness due to fibromyalgia often complain of poor sleep. A theory has developed that the poor sleep causes the diffuse achiness characteristic of this disease. On the other hand, maybe the achiness causes difficulty sleeping. The cycle of poor sleep at night and achiness during the day surely don’t make either better, but with our current level of limited understanding, knowing which came first (suggesting that factor as a potential cause) is impossible.
Confounding variables In medical research, a factor that routinely influences an outcome but is not accounted for in the research because it is not measured or recognized as important; this can lead to faulty assumptions about causation. For example, many people blame how they feel (“I’m so tired”) on their diet (“I should stop eating so many sweets!”) and certainly there may be a connection. However, there are other factors that could cause the same problem that have not been taken into account. In the example above, too little sleep, worrying about a deadline at work or the antihistamine taken the night before could be the true cause of fatigue. These other factors are confounders and unless they are also considered, it’s easy to make a faulty assumption about cause and effect.
When did it all begin? In many conditions, it is difficult or impossible to determine when the condition developed. This can lead to faulty assumptions about causation when based on “suspicious timing.” For example, the kidney is responsible for ridding the body of uric acid, a normal waste product. Kidney disease leads to an elevated blood level of uric acid, and an elevated uric acid is a clear risk factor for gout. So, because many people with gout have kidney disease that may have begun long before symptoms developed, many assume that gout caused the subsequent symptoms of kidney disease; in fact, the kidney disease usually develops first and increases the chance that gout will develop.
Bottom Line: Don’t Jump to Conclusions
In making health-care decisions, as in so many other situations, we should all do our best to avoid assumptions and drawing quick conclusions. Doing so may lead to unwise choices. Tell your health-care provider your concerns about your health, your medications or any medical recommendations made to you. If your concerns are based on inaccurate or incomplete information, setting the record straight could improve your understanding of your health and any illnesses you have. More important, you may even improve your health by changing your mind about a health decision you have made.
And if I practice what I preach, maybe I’ll stop blaming my kids for my graying hair.
For example, if smokers are found to have high blood pressure more often than non-smokers, smoking may be assumed to be the cause. (In fact, nicotine can raise blood pressure). However, if smokers are also overweight more often than non-smokers, one must account for weight before attributing the cause of blood pressure problems solely to smoking. Weight is a “confounder” is this example because it can cause the same effect as the factor assumed to be causal (smoking); confounding is an important source of error in medical research. It is likely that many important factors that contribute to disease have not yet been discovered and therefore cannot be specifically accounted for in research – until their importance is recognized, these factors could be confounding research and confusing conclusions about cause and effect. Meanwhile, the assumptions of cause and effect are in error.