Longevity Expert Breaks Down What Fitness Trackers Get Right, What They Get Wrong, and Why It Matters

Wearable health trackers have never been more capable. Heart rate by the second. Sleep stages by the hour. Stress scores, recovery indices, estimated VO₂ max. The data is everywhere, and the market for it is growing by the billions.

But the more data people collect, the more confused many of them become. Numbers arrive without context. Scores fluctuate without explanation. The attempt to gain control over health ends up creating a new kind of anxiety.

That tension is exactly what Niko Hems, Head of Medical Communication at YEARS, explored in an article for t3n, one of Germany’s leading technology publications. 

Millions of people now track their health with consumer devices. But even a dashboard full of reassuring scores leaves important health risks unmeasured.

What Wearables Can Reliably Measure

The starting point is honesty about what consumer devices actually do well.

“Many wearables are reasonably accurate at tracking heart rate and steps, and useful for following sleep-duration trends.” Niko says. “Some can also detect potential atrial fibrillation.”

Heart rate variability tracking has helped many people identify patterns in their recovery and stress responses. Step counts and activity tracking have genuinely moved the needle for people who were previously sedentary. And atrial fibrillation detection, available on several major smartwatch platforms, has been a genuine clinical win: a condition that is easy to miss in a routine doctor’s visit but carries serious stroke risk, caught early by a device on someone’s wrist.

These are real contributions and they should not be dismissed.

Where the Limitations Start

The reliability drops off quickly once you move beyond those core metrics.

“Less reliable metrics include sleep stages, calorie expenditure, stress scores, and estimated VO₂ max,” Niko says. “The first limitation is measurement accuracy. The second is interpretation: even when a wearable picks up a real change, it usually cannot tell you what caused it.”

This is the critical gap. A low VO₂ max estimate on your wrist may indicate reduced cardiorespiratory fitness. It may also reflect measurement error. The device cannot establish the cause. A persistently low estimate can be a useful prompt to review training or discuss reduced exercise tolerance with a physician. It cannot distinguish limited fitness from measurement error or an underlying medical issue. When further investigation is warranted, medical history, cardiopulmonary exercise testing and targeted investigations will help clarify the cause.

The same applies across the board. A stress score that spikes after a difficult conversation tells you the device registered something. It does not tell you whether that spike matters, whether it is a normal physiological response, or whether it is part of a pattern worth addressing.

As Niko explains: “Clinical assessments combine medical history, laboratory testing, validated diagnostics, and physician interpretation. Wearables simply cannot replicate that.”

The Problem With Optimising Without a Baseline

There is another layer to the problem. Most people wearing fitness trackers today are optimising behaviours without a clear picture of where they actually stand. They are pushing activity because their step count was low yesterday. They are adjusting sleep schedules because their deep sleep percentage dipped. They are taking supplements because their stress score looked red.

Wearable feedback can support sensible changes, such as moving more or keeping a consistent sleep schedule. Problems arise when people treat uncertain scores as medical findings, changing routines or taking supplements to correct a number they do not fully understand.

Here, Niko draws a distinction that preventive medicine clinics like YEARS are built around: the difference between measuring more and measuring what matters.

“Wearables will become increasingly valuable, especially for continuous monitoring and early detection,” he says. “However, they cannot replace assessments of important risk factors like ApoB, Lp(a), or structural abnormalities.”

ApoB and Lp(a) are markers that cardiovascular research has firmly linked to heart disease risk. Neither can be measured by any consumer wearable. Both are detectable through standard blood testing. Both are actionable. And both are absent from the dashboard that most people who track their health every day are looking at.

That is not a criticism of the devices. It is a calibration problem. Even highly health-conscious people can overlook risks their devices cannot measure. Good activity and recovery scores do not rule out elevated ApoB, elevated Lp(a), or other clinically relevant findings.

When Tracking Becomes Counterproductive

Niko’s article went further than just diagnosing the measurement gap. It addressed something less discussed: the psychological cost of self-tracking.

The phenomenon of orthosomnia has been documented in clinical literature. For some people, fixation on sleep scores can increase anxiety and make sleep problems harder to manage. The act of checking a score, seeing a red flag, and lying awake interpreting what it means becomes itself a driver of the very problem they are trying to solve.

The same dynamic applies across other metrics. Niko’s practical rule is blunt:

“If a metric does not help you make better decisions, question why you are tracking it.”

That means looking at trends over weeks rather than individual daily readings. It means using wearable data to reinforce behaviours you already know are beneficial: more movement, better sleep consistency, active recovery. And it means resisting the pull to optimise around scores that fluctuate for reasons outside your control.

“Focus on actionable metrics like daily activity, resting heart rate, and sleep duration,” Niko says. “Look at trends over weeks rather than individual readings.”

The Three Differences Between Consumer Gadgets and Preventive Medicine

As wearables become more medically sophisticated, the question naturally arises: can they eventually replace clinical assessments?

Many consumer metrics lack the evidence linking them to meaningful health outcomes. A biological age estimate needs evidence that it measures something meaningful and can guide useful decisions. A precise-looking number alone does not establish clinical value. A recovery score is a proprietary number built on assumptions that may or may not hold for any individual person.

Genuine preventive medicine does something different. It identifies relevant health risks and addresses them through evidence-based interventions. That requires a physician who can review a full diagnostic picture, understand the interactions between different systems, and produce a prioritised plan based on what the data actually shows.

That is what YEARS has built into its model. The clinic’s Core, Evolve, and Ultimate programmes are structured around exactly this principle: not more data, but better interpretation. A single diagnostic day brings together cardiovascular testing, metabolic panels, spiroergometry, and laboratory work that would normally take multiple specialist appointments. Everything is reviewed by a physician who has the complete picture.

“Wearables will become increasingly valuable,” Niko says. “But the future is integrating wearable data with clinical diagnostics and physician-led interpretation to make better preventive decisions.”

The Takeaway for Anyone Tracking Their Health

For the millions of people who have bought a fitness tracker or smartwatch in the past few years, none of this means the device is useless. It means the device has a specific job, and that job is not the same as the job of a clinical assessment.

Wearables are excellent for building habits, tracking trends, and detecting certain cardiac irregularities early. They are not designed to replace the kind of deep diagnostic picture that identifies cardiovascular risk, metabolic dysfunction, or early-stage disease before it becomes a problem.

The people getting the most value from their trackers are usually the ones who understand that distinction. They use the data to reinforce healthy behaviours, not to diagnose conditions. They look at the trends. They ignore the noise. And they go and get a proper health assessment every year or two, with a physician who can read the numbers in context.

“The most effective clinical prevention is not generic,” Niko says. “It is personalised, physician-led, and built on actual diagnostic data.”