Defining Normal

By | February 17, 2014

Pay close attention to the small peak on the right.

In this blog I would like to explore the important distinction between average and normal. In the blog entitled “Health and Disease” I spoke about the importance of how one defines normal. A common practice in medicine is to look at the results of a particular test and select the mean or the median value as define this as normal. Sounds simple, right? There is however a subtle philosophical problem with this approach. It tacitly assumes that the sample population is normal with respect to the disease or condition being studied. Let me give you an example unrelated to pain or aging. Suppose you had set up a blood lab to determine the hemoglobin concentrations for a group of patients and that to calibrate the lab you looked at the average hemoglobin concentration for 100 randomly selected neighborhood patients. Unfortunately the neighborhood in which the lab is located has a very high proportion of residents who are recent immigrants from Southern Italy, a place where the disease Thalassemia is common. People with this disease usually are moderately anemic, so the normal value determined by this method of calibration would be spuriously low. Furthermore the distribution of hemoglobin values would be abnormal, showing the two distinct peaks of a bimodal distribution one representing the people with Thalassemia and the other representing those without the disease rather than the smooth bell shaped curve of a normal distribution. To make matters worse the average value determined in this study, which would be expected to lie somewhere between the two peaks may actually be representative of no one.  At Schlesinger Pain Centers we rarely take this approach.

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