Why Average Health Is Not the Goal

‘Everything looks normal.’ It is one of the most common things members hear in a primary care office, and one of the most misleading. Normal, in clinical medicine, typically means within the statistical range observed in a broad population. That population includes people who are overweight, sedentary, prediabetic, and chronically stressed. Normal, in other words, is a description of average Americans, and average American health is not a particularly high bar.

Sixty-eight percent of American adults are overweight or obese. Forty-seven percent have at least one chronic disease. Rates of metabolic syndrome, prediabetes, and cardiovascular disease are rising across every age group. If your lab results look like the average of this population, you are not healthy. You are average. And average, in the current health environment, is dangerous.

The traditional medical model is built around the treatment of established disease. You develop symptoms, you get tested, you receive a diagnosis, and you receive a treatment. This model has enormous value. It has also created a system that is structurally incapable of preventing the diseases it is excellent at managing.

Prevention requires intervention before symptoms appear. That means testing people who feel fine, identifying risks in people who are asymptomatic, and making changes to trajectory before a diagnosis is necessary. This is not how the standard healthcare system is designed, incentivized, or paid for. Insurance reimburses treatment, not prevention, and this shapes what gets done in the average clinical encounter.

Precision medicine operates from a different premise entirely. The goal is not to diagnose disease; it is to prevent the conditions under which disease becomes inevitable.

The precision approach begins with a more complete picture of what is actually happening in your body.

Standard lipid panels measure LDL, HDL, and total cholesterol. These numbers have value, but they miss important dimensions of cardiovascular risk. ApoB, the primary protein on LDL particles, is a more direct measure of atherogenic particle burden. Lp(a), a genetic variant of LDL, is a major risk factor largely independent of LDL and completely invisible on standard panels. Coronary artery calcium scoring, a low-dose CT scan, can detect subclinical atherosclerosis years before it causes symptoms.

Fasting blood glucose tells you whether you have diabetes. Fasting insulin, HOMA-IR, and continuous glucose monitoring data tell you how hard your pancreas is working, how resistant your cells are becoming to insulin, and whether you are on a trajectory toward metabolic disease years before your glucose rises. These distinctions are clinically important and almost never tested in standard primary care.

Your weight tells you almost nothing useful. Body composition testing separates lean mass from fat mass, and identifies visceral adiposity, the fat surrounding internal organs that drives metabolic dysfunction and cardiovascular risk. Two people with identical weight and BMI can have radically different health profiles depending on their body composition.

VO2 max is the single strongest predictor of all-cause mortality in the research literature, more predictive than blood pressure, more predictive than cholesterol, more predictive than smoking status. It is almost never measured in standard care. In our practice, it is a cornerstone assessment.

Our goal is not to move your numbers from the bottom of the normal range to the middle. Our goal is to move them from the middle of the normal range to the top quartile for optimal health, and beyond, toward the performance benchmarks associated with low disease risk and high functional longevity.