I cannot even count how many clients have told me something along these lines, “I have been to the doctor and they have told me that my blood tests are all normal, but I feel that something has to be wrong somewhere.” Obviously these individuals do not feel well. In many cases they are dealing with a number of symptoms, some commonly related to one another and others just seem random and out of place. This all begs the question – why do their lab results not at all reflect the way they feel? If there was something wrong, the doctor would easily be able to see that, right? Well, not so fast. There is more than one way to skin the proverbial cat when it comes to interpreting lab results of any kind. In some, and quite honestly in many cases, what would otherwise appear to be “normal” values do not actually pan out physiologically in terms of actually being healthy.
Pathological vs. Functional View
Allopathic / Standard medicine looks at most lab values from a “pathological” perspective. What this means is that the body is viewed as a “machine” composed of separate parts (tissues, organs, etc.). The focus is on identifying pathological issues and is highly specialized and predicated on the reduction of symptoms. This approach also relies on late-stage development of disease as a fundamental marker and as long as you do not have a disease or organic pathology you are considered to be “healthy.” But is that really true?
In contrast, the “functional” view looks at the body as an interconnected system of systems and seeks to identify areas of imbalance in normal physiology. The goal of the functional model is to identify the cause, or root, of dysfunction and provide intervention that allows the body to restore optimal physiology. The view of health is one that is much more than the absence of symptoms or disease. Rather, an individual is healthy when s/he has optimal physiology, feels great, and views life as having meaning and purpose.
What is normal? So, when you are told by your physician that your blood test is “normal”, what does that actually mean? What perspective is that view taken from? And just who what are “normal” based off of? The laboratory reference ranges that are used to classify someone as “healthy” are, in fact, averages. (This was not a new concept to me but was driven home when I went to a course at Metametrix Clinical Labs about 4-5 years ago). Different labs have different reference ranges. As a matter of fact, the same lab can have different reference ranges for the same lab value (i.e. – potassium) in different states. What this means is that it is theoretically possible to receive one diagnosis from your lab work and move to another state, have the same blood work run, and receive a completely different diagnosis or no diagnosis at all! It is not at all uncommon to have a test result come back “normal” from one lab and “out of range” for another lab. The fact of the matter is that if your lab results fall within a given reference range used by a given lab – what that means is that you are “average” and not necessarily “healthy.” (Heads up, the “average” person has not been healthy for the last 40 or 50 years) Each lab, or its lab director, sets the reference range for each particular test value (blood, urine or otherwise) based upon a percentage of people who have taken the test with that given lab. This is basically using a bell curve to determine what constitutes “normal” which really means “average.” The more and more people take a given test, and the worse their physiology begins to function, the wider the “normal” (really “average”) reference range becomes. If all of this seems confusing it’s because…well, it is a real head scratcher!
Not that it is ever a good idea to look at a single lab value alone (as that represents a compartmentalized “pathological” approach), but let’s say someone has their fasting insulin levels checked with standard blood work because they are having issues regulating blood sugar. The lab doing the testing uses a reference “normal” range of say 0-20, some use 0-24, and others 0-22. Either way the range is pretty broad. The individual in question happens to have a fasting insulin level of 14. Interpreting from the pathological model, this individual is “normal” and “healthy.” However, it is fairly widely accepted in the “functional” model that many people who are dealing with insulin resistance have fasting insulin levels greater than 10-12. Again, utilizing functional interpretation, one would also be interested in asking their physician to look at additional markers to assess blood sugar handling issues, such as C-Peptide levels (C-Peptide is a compound made in the pancreas in the same relative rate and timing as insulin, but C-Peptide has a much longer half-life than insulin), A1C, fasting glucose, glucagon, cortisol, adrenaline, thyroid, and other markers that can give insight as to why someone may have blood sugar handling issues.
Hopefully, from this example (and there are endless examples just like this one), it is clear to see how your blood test can be “normal” with respect to a given value, but there can still be a functional issue that needs to be addressed to restore optimal physiology and health. It may seem like rocket science, but it actually is not.
By interpreting a blood test from a functional rather than a pathological perspective, the likelihood of getting to the “root” of someone’s health issues increases dramatically. From there the focus is on FUNCTION and HEALTH as opposed to going after symptoms.
This quote from Dicken Weatherby, N.D. sums up what is stated above very nicely:
“Medicine and health care are undergoing a paradigm shift. We are seeing more and more demand from our patients to look at their complex cases from a holistic rather than a mechanistic or reductionistic perspective. In order to do this we need to have diagnostic methods that focus on physiological function as a marker of health, rather than merely the presence of pathology or tissue change as a marker for disease.”
– Blood Chemistry and CBC Analysis: Clinical Laboratory Testing from a Functional Perspective
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