Diagnostics and longevity. When testing helps — and when it only multiplies anxiety

1. What does diagnostics mean in healthy aging?

In the conventional sense, diagnostics is associated with detecting a specific disease — alongside preventive medicine and screening (see Preventive medicine and longevity). In longevity and healthspan, however, diagnostics can serve a broader purpose: not only asking “is disease present?” but also “in which direction, and how quickly, is my health changing?”.

This distinction matters in practice. Screening asks whether a specific, defined disease may be present. Diagnostics understood as tracking a health trajectory asks whether metabolic, cardiovascular or inflammatory measures are moving in an unfavourable direction before they cross a diagnostic threshold. The approaches complement each other, but confusing them leads to two common errors: overinterpreting one borderline result or dismissing a slow but consistent trend.

2. Why does one test result say less than it seems?

Every laboratory measure — glucose, cholesterol or creatinine — varies naturally within the same person for reasons unrelated to disease. Circadian rhythm, hydration, the last meal, menstrual-cycle phase and stress can all matter. Research on biological variation shows that, for many analytes, within-person variation is large enough that one result inside a broad population reference interval may conceal a meaningful change for that individual. Conversely, one mildly out-of-range result may be physiological for that person.

This is the basis of the “reference change value” (RCV): a statistically calculated difference between two measurements in the same person that is large enough to be more likely to represent genuine change rather than random variation. In other words, “has this result changed meaningfully from the previous one?” can be more useful than “is this result normal?”.

3. What changes when we follow many measures over time?

One of the best-known examples of long-term, multidimensional monitoring is Michael Snyder’s Stanford study, in which one person was followed for more than a year using an extensive “omics” profile — genome, transcriptome, proteome and metabolome. During follow-up, two viral infections occurred, and the data revealed the development of insulin resistance and early signs of type 2 diabetes before typical clinical symptoms appeared.

This study — initially involving one person and later extended to larger groups — does not show that this degree of monitoring should become standard. It remains expensive, impractical research. It does, however, illustrate an important healthspan principle: molecular changes may precede symptoms by months, and regular multidimensional tracking — even in a simpler form, such as a basic blood panel repeated under comparable conditions — can provide more information than a one-off “check-up”.

4. Do more tests mean more health?

Not automatically — and this is one of the less comfortable findings in diagnostics research. An analysis published in The BMJ describes overdiagnosis: broadening disease definitions, lowering diagnostic thresholds and widespread untargeted testing can detect abnormalities that would never become clinical problems, while generating anxiety, further investigations and sometimes unnecessary treatment.

This is not an argument against diagnostics. It is an argument for targeted, contextual diagnostics. A test is worth considering when it answers a specific clinical question or follows a previously observed trend — not when the only goal is to “check everything possible”. This matters particularly for expanded commercial “wellness” panels: the more variables measured without a prior question, the greater the chance of a statistically inevitable incidental abnormality with no clinical significance.

5. Participatory diagnostics — where is the field heading?

“P4 medicine” — predictive, preventive, personalised and participatory — describes a proposed direction for diagnostics: away from isolated tests performed in response to symptoms and towards continuous monitoring in which the patient is an active participant rather than merely the recipient of a result.

This remains largely a vision rather than routine clinical practice. Infrastructure, costs and clinical validation of many proposed tools — including epigenetic clocks and extended omics panels — are not yet sufficient for routine use in an individual patient. We discuss the limitations of biological clocks in Biomarkers and longevity and Biological age. The general direction — less waiting for symptoms, more understanding of one’s health trajectory — is nevertheless consistent with healthspan science.

6. Which assessment methods are available today?

No single method answers every question about health. Blood tests remain central to metabolic and cardiovascular assessment; urine tests and 24-hour urine collection provide a different time window and different parameters; imaging such as DEXA assesses body composition and bone density; continuous monitoring, such as glucose monitoring, shows dynamics rather than a single reading. Each method has different uses, limitations and exposure windows — an overview is available in Assessment methods.

Using diagnostics thoughtfully for healthy aging is not about choosing the “best” method. It is about matching a method to a specific question and, importantly, maintaining regularity and comparable measurement conditions so that a trend can be interpreted.

Research limitations. The reference change value assumes knowledge of an individual’s biological variation for a given parameter. In clinical practice this is rarely known precisely, so population averages are used, limiting individual accuracy. The initial individual “omics” profiling study (iPOP) was a case report with very limited generalisability; later work included larger groups, but the method is still not validated for routine clinical use. Literature on overdiagnosis focuses mainly on cancer and cardiovascular screening. Applying it to broad “wellness panels” is a reasonable analogy, but the phenomenon has not been studied directly in that exact context. P4 medicine remains largely a research programme and conceptual model.

One small step

Rather than reacting to one worrying result, choose two or three basic measures — for example blood pressure and fasting glucose — and follow them regularly under comparable conditions. Bring the trend from several measurements, not only one number, to your conversation with a clinician.

This content is educational and does not replace medical advice, diagnosis or treatment.