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Functional Blood Chemistry: Optimal Ranges for Optimal Health
Striving Towards Optimal Health with Functional Blood Analysis
The optimal range of a given blood biomarker is a narrow band of upper and lower limits that correspond to the optimally healthy levels for that biomarker. In contrast to the “normal” reference ranges used in allopathic medicine, the optimal range is meant to reflect optimal health and function health rather than the absence of disease.
Medical practitioners track their patients’ progress towards and away from the optimal range to detect early changes in metabolism and trends towards dysfunction. Optimal ranges provide the practitioner with an opportunity to explore imbalances before they progress into pathology. In this way, practitioners can treat dysfunction before it evolves into a disease. Let’s break down the what and how of the optimal range.
Under allopathic approaches, a practitioner might take one blood test, note that a given biomarker isn’t low or high enough to indicate the presence of disease, and reassure the patient that everything looks normal — even if that patient is still experiencing dysfunction like fatigue, pain or inflammation.
That’s because the broad reference ranges used by the laboratories that analyze blood samples are based on averages, not on actual health. When faced with these broad ranges, a practitioner or a patient might conclude that because a biomarker falls within normal limits, there is no disease and no need for treatment. But relying on these reference ranges when conducting a blood biomarker functional analysis can be a mistake. Where do these reference ranges come from?
To calculate a biomarker range, labs test samples of blood drawn from a certain population with similar characteristics e.g. age, gender, health status, race— for example, a lab might take blood from 150 males between the ages of 40 to 75.
Next, labs assess the levels of the relevant biomarker within that sample and generate a bell curve from the results. In order to determine the upper and lower limit of the reference range (the reference interval), they use 2 points of standard deviation i.e. the upper 2.5% and lower 2.5% of the bell curve are considered "not normal". The remainder represents the range in which 95% of the sampled population’s blood biomarker levels fall. This is defined as “normal.”
However, it should be evident that equating this “normal” biomarker range with a healthy biomarker range is problematic. Consider the fact that the sampled population is essentially a random snapshot, intended to capture the average — not what’s healthy. In many parts of the world, people are obese, exercise less than they should, eat a poor diet, are exposed to pollutants, and more. Average blood biomarker ranges from these populations will wildly misrepresent the optimal health targets patients should be shooting for.
Many practitioners don't consider how the standard blood biomarker ranges are determined. If a practitioner is having a challenging time diagnosing a patients’ complaints, orders a blood test and sees that the results fall within the reference range, they might conclude that there was no useful diagnostic information from the blood test that they ordered and that they need additional, more invasive testing to make a diagnosis — or worse, that the patient is exaggerating their symptoms.
The standard blood biomarker ranges aren’t designed to measure health, but rather where a patient falls in comparison to the average. Understanding this is an essential first step to making better, more impactful assessments and treatment plans.
Using functional or optimal ranges, practitioners can help identify when a patient is trending towards dysfunction and help guide them back to health. The standard reference ranges described above are useful at diagnosing pathology; that is, if some disease is causing a given biomarker to register as excessively high or low, it can serve as a clear sign to practitioners that the patient is suffering from a clinical condition and that their diagnostic thinking was correct.
However, this kind of black-and-white thinking — where the patient is either healthy or sick with a clinical condition — leaves many dysfunctional, unhealthy patients to suffer. Under the functional approach, we use tighter, optimal ranges that represent the ideal level for a given biomarker. When a biomarker strays above or below that range, practitioners can use this as a sign that there is dysfunction and an intervention is needed, whether that’s the prescription of supplements, dietary and lifestyle changes, or any other type of treatment, including pharmaceutical intervention if warranted.
To make even greater use of functional blood chemistry’s optimal ranges, practitioners can track their patient's blood test results over time and observe as biomarkers shift towards or away from the optimal range.
Naturally, no individual blood-based biomarker can provide a practitioner with the whole picture of their patients’ health. As an example, you can explore our series on endothelial dysfunction — under this condition, biomarkers like homocysteine and glucose will be elevated while biomarkers like testosterone and adiponectin will be diminished. This pattern of blood-based biomarker change is distinct from, say, that created by a condition like prediabetes — both involve elevated glucose, but the whole of the biomarker landscape looks different in endothelial dysfunction than it does in prediabetes.
Thus, functional practitioners must examine a matrix of biomarkers in order to accurately assess their patients’ health.
An estimated 60-70% of medical decisions are based on laboratory results and interpretation. But as clarified by the examples above, practitioners using the allopathic approach may be making decisions for their patients far too late to prevent certain conditions.
This doesn’t mean that functional practitioners should abandon the use of blood tests as a diagnostic tool; rather, functional practitioners should approach blood testing in the same way they’ve been trained to approach medicine as a whole — functionally.
Using the tighter, optimal ranges for a given biomarker enables functional practitioners to detect the risk of and progression towards a number of undesirable conditions, including:
Functional Blood Chemistry Analysis serves as a complement to other functional assessments. By tracking changes in blood chemistry in combination with an individual’s clinical presentation and symptoms over time, practitioners gain a powerful method of more rapidly identifying dysfunction before it becomes disease and monitoring the impact of their treatment plans.
For many medical practitioners, taking a functional approach to blood chemistry analysis is a novel technique. It could be that your discipline doesn’t traditionally focus on blood chemistry analysis, such as naturopathy or osteopathy. Or, it could be that you’re familiar with blood chemistry analysis, but focusing on functional ranges is new to you.
Medical practitioners that want to learn more about the fundamentals of functional blood chemistry analysis and how to implement it in their practice could benefit from our Functional Blood Chemistry Analysis (FBCA) Mastery Training. Registrants will:
Learning about blood biomarkers and how they can expedite your diagnostic process is an incredible opportunity to enhance your practice. Sign up for the FBCA Mastery Training today and begin learning how to drastically improve your patients’ outcomes.
If you’re still curious about how FBCA works, check out our page, About Blood Chemistry. After all, as medical practitioners, knowledge is the best tool in our toolkit to fight against disease and dysfunction.
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