What Is Your Health Trajectory?

Your labs may be normal. But what are they telling you about where you are heading?

Imagine leaving your annual physical with reassuring news: “Your laboratory results are normal.” You put the report away and return to your routine. But what if the more useful question is not simply whether today’s results are normal? What if it is how those results have changed—and what they may be telling you together?

A laboratory reference range is important. It helps clinicians recognize abnormalities and apply established diagnostic criteria. But a single measurement is only one point in a longer story. It cannot, by itself, describe the direction of your health, explain a symptom, or establish what will happen next.

Four normal glucose results. One unanswered question.

Consider a hypothetical person whose fasting glucose rises from 78 to 82 to 85 to 95 mg/dL over four annual measurements. Every result remains below the usual U.S. prediabetes threshold of 100 mg/dL. None independently establishes prediabetes. Yet if this change is sustained under comparable testing conditions, would it be worth discussing?

Perhaps the rise reflects ordinary biological or measurement variability, an illness, medication, changes in sleep, or differences in test conditions. Perhaps it is a meaningful change in glucose regulation. The graph alone cannot tell us. That is exactly why it is a reason to investigate rather than a reason to diagnose—or to panic.

Now imagine that, over the same years, waist circumference, blood pressure, and triglycerides also increased. The question becomes more interesting: are these separate changes, or parts of a connected metabolic pattern?

Prediabetes is common—and often unrecognized

The U.S. Centers for Disease Control and Prevention (CDC) estimates that 115.2 million American adults have prediabetes. About eight in ten adults with prediabetes are unaware that they have it. Those are population estimates, not a prediction about any individual reader. They nevertheless make an important point: waiting for symptoms or for someone to mention an abnormal result can miss opportunities for earlier assessment.

Source: CDC National Diabetes Statistics Report (updated September 2026) and CDC “Prediabetes: Could It Be You?” (February 2026). Estimates refer to different populations and should not be added together.

A fasting glucose result below 100 mg/dL does not rule out prediabetes detected by HbA1c or a two-hour oral glucose tolerance test. Conversely, one rising fasting-glucose series is not sufficient to establish a diagnosis. The right next step depends on the individual and the surrounding clinical information.

What if glucose is not changing alone?

Metabolic syndrome describes a clustering of metabolic risk factors: abdominal adiposity, elevated triglycerides, low HDL cholesterol, elevated blood pressure, and elevated fasting glucose. Under commonly used criteria, three of five components qualify for the syndrome. So, metabolic syndrome often uses this binary, yes or no, formula. The components are familiar; their relationships are often less visible in an ordinary review of results.

Consider a hypothetical example of a pattern I have encountered frequently in clinical practice. The numbers are illustrative, but the underlying problem is familiar: several metabolic measurements gradually change, often without attracting much attention. Importantly, I have also seen unfavorable patterns improve with appropriate intervention.

Illustrative adult male; component thresholds vary by definition and may depend on sex, ancestry, treatment status, and clinical context. These are not patient records.

At one point, the person may meet no criteria. Later, several values may move unfavorably before a three-of-five classification is reached. Even after that classification, two people with “metabolic syndrome” can differ substantially in the magnitude of their abnormalities. A binary label answers an important question—does the person meet the definition?—but it does not capture the entire trajectory. A continuous measure can add useful context.

The national picture: common, but not a simple straight-line epidemic

A recent analysis of 11,570 U.S. adults using the CDC’s National Health and Nutrition Examination Survey (NHANES) data from 2013 through 2023 estimated an overall weighted metabolic syndrome prevalence of 38.7%. The overall change across survey cycles was not statistically significant. Among adults aged 60 years or older, however, prevalence increased from 50.2% in 2013–2014 to 62.4% in 2021–2023. That age-specific finding deserves attention without mischaracterizing the overall national trend.

These findings do not mean that any particular person will follow a worsening path. They do mean that metabolic patterns worth recognizing are common enough to deserve serious attention. Too often, we respond to metabolic syndrome one measurement at a time: medication for blood pressure, another for glucose, perhaps another for cholesterol. These treatments may be appropriate and important. But are we also investigating why several metabolic abnormalities developed together? And are we addressing the underlying contributors that might improve more than one measurement at a time?

From binary metrics to continuous metabolic severity

The metabolic syndrome severity score (MSSS, or MetS-Z) offers a complementary way to interpret the same five measurements. Rather than counting only how many values cross a cutoff, it combines their measured values into a continuous score. The published models account for sex- and race/ethnicity-related differences in how the components relate to one another.

This matters because your metabolic health is personal. Two individuals can meet the same diagnostic criteria yet have very different metabolic profiles. A continuous metabolic syndrome severity score gives us another way to examine those differences and, importantly, observe whether the combined pattern is improving or worsening over time. It complements clinical assessment rather than replacing it.

These are the same measurements from our hypothetical individual. We haven't collected any new information. We've simply examined the relationships among the measurements rather than interpreting each one separately.

What happens next? The same metabolic profile could worsen, stabilize, or improve. Becoming aware of the pattern is the first step. Understanding potential contributors, obtaining knowledgeable guidance, implementing appropriate changes, and measuring the response can help determine whether the trajectory changes. The next measurement is not predetermined. MSSS provides a way to follow changes in modeled metabolic syndrome severity, not a promise that any particular intervention will work.

The most important possibility: the trajectory can change

An unfavorable trajectory is not a forecast. Lifestyle, physiology, medications, life circumstances, and other influences change over time. For some people, excess adiposity and insulin resistance may be major contributors. For others, the relevant drivers and constraints differ. That is why a thoughtful plan investigates the individual rather than assuming everyone has the same root cause.

Depending on the person, care may involve changes in nutrition, exercise, sleep, stress management, medications, and treatment of contributing conditions. An effective intervention should do more than produce a plan on paper: it should monitor whether metabolic markers, fitness, function, and quality of life actually respond.

In a 2022 AJPM Focus publication, our team reported a retrospective chart review of 536 participants in a personalized, multifaceted lifestyle program targeting contributors to hyperinsulinemia and insulin resistance. These are not merely theoretical possibilities: we documented meaningful improvements in metabolic health, including reversal of metabolic syndrome criteria and normalization of hyperglycemia in substantial proportions of the relevant groups.

Among participants meeting metabolic syndrome criteria at baseline, 42% no longer met those criteria at follow-up. Among participants with prediabetes, 35% normalized hyperglycemia. Among those with type 2 diabetes, 46% reduced HbA1c below diabetic cutoffs; this result should not automatically be described as medication-independent remission. The study also reported improvements in waist circumference, triglycerides, blood pressure, MSSS, and major increases in estimated cardiorespiratory fitness.

These findings illustrate the practical reason to identify metabolic patterns: the goal is not to give someone another score. The goal is to find modifiable contributors, choose an appropriate intervention, and evaluate whether meaningful change follows. That is a different conversation from merely asking whether today’s laboratory report is flagged as abnormal.

Employers Have Health Trajectories, Too. And They Are Paying for Them.

Self-funded employers face a familiar problem: healthcare costs continue to rise year after year. Much of the discussion focuses on the increasing price of medical services, pharmaceuticals, and insurance administration. These are legitimate concerns. But another driver deserves far more attention: the growing burden of chronic disease and the healthcare utilization it generates.

What if the problem isn't just what we pay for treatment, but how many people continue to need it?

Consider prediabetes. Millions of American adults have it, and most are unaware. Without effective intervention, a meaningful proportion will progress to type 2 diabetes. Published estimates of annual progression vary by population and risk profile, with rates of approximately 6–11% reported in some higher-risk groups.

For an employer, that progression represents more than a change in diagnosis. It can mean additional medications, laboratory testing, office visits, monitoring, and potentially costly complications. If the annual healthcare cost associated with type 2 diabetes is approximately $12,000 per affected person in an illustrative cost model, the financial implications of continued progression become substantial.

Now consider an alternative trajectory.

In our published Health Ballistics program evaluation, the annual progression from prediabetes to type 2 diabetes was approximately 1.7%. This does not guarantee that another population will achieve the same result, but it demonstrates why changing the trajectory deserves serious consideration.

The difference between 6–11% annual progression and approximately 2% can become meaningful when applied to hundreds or thousands of employees over several years.

And this represents only one potential opportunity. What might happen if more employees also reversed metabolic syndrome, improved blood pressure, reduced hyperglycemia, and increased cardiorespiratory fitness?

Most employer wellness programs focus on risk reduction and struggle to demonstrate a financial return. We believe the conversation should begin with something more tangible: measurable improvement in health, including the normalization or reversal of established metabolic abnormalities.

Explore the potential impact yourself. Our Prediabetes Progression Calculator allows employers to explore how different progression rates and treatment costs could influence future healthcare spending. It is a scenario-planning tool, not a guarantee of savings.

For self-funded employers, the opportunity is to examine two trajectories: the cost of continuing with the current burden of disease, and the potential value of changing it through effective, measurable intervention.

Actual savings must account for program costs, participation, sustained outcomes, and real healthcare claims. But those are reasons to measure the results—not reasons to ignore the opportunity.

The question isn't simply how much healthcare will cost next year. It's how much of that future cost might be avoidable if we begin changing health trajectories today.

So, what is your trajectory?

If you have several years of laboratory reports, put them side by side. Look beyond the values marked high or low. Has your fasting glucose changed? What about triglycerides, HDL cholesterol, waist circumference, blood pressure, or fitness? Are several measurements changing together? And if your health seems to be declining, should you simply attribute it to getting older—or might there be modifiable contributors worth investigating? You do not need to wait for a diagnosis to begin asking better questions. Our free Plan2Peak self-assessments can provide a starting point, and a more personalized evaluation can help put your results into context.

A normal value can be reassuring. A changing value can be informative. Neither should be interpreted alone. What matters is understanding the relationships, considering the individual, and measuring what happens after a decision is made.

Your history does not determine your future. But understanding your trajectory may help you change it.

Explore the evidence

These sources are provided in reader-friendly form. Each title is a clickable link to the original report, study, or tool.

Centers for Disease Control and Prevention (CDC) — National Diabetes Statistics Report — U.S. estimates of diabetes, prediabetes, and undiagnosed disease

CDC — Prediabetes: Could It Be You? — 115.2 million adults and 8 in 10 unaware

JAMA — Trends and Prevalence of the Metabolic Syndrome Among US Adults — NHANES 2013–2023

Gurka and colleagues, Metabolism — An Examination of Sex and Racial/Ethnic Differences in the Metabolic Syndrome Among Adults — development of continuous MSSS

University of Florida / MetS Calc — Metabolic Syndrome Severity Calculator — background, interpretation, and published model

Cummings and colleagues, AJPM Focus (2022) — Lifestyle Therapy Targeting Hyperinsulinemia Normalizes Hyperglycemia and Surrogate Markers of Insulin Resistance in a Large, Free-Living Population — 536-person retrospective review

CDC — Preventing Type 2 Diabetes — risk recognition and prevention approaches