What “biological age” means
Biological age is a number that claims to say how old a body is, rather than how many birthdays it has had. The number almost always comes from an epigenetic clock: an algorithm that reads DNA methylation patterns at a few hundred to a few thousand sites in the genome and maps them onto an age. The first of these, the Horvath clock from 2013, predicted chronological age with striking accuracy across a whole population. Later clocks changed the target: second-generation tools such as DNAmPhenoAge and DNAmGrimAge were trained on mortality and disease rather than birthdays, so they report a risk estimate dressed up as an age; third-generation clocks such as DunedinPACE report a pace of aging — a velocity rather than a position.
There is still no agreed definition of biological age and no gold-standard measure to validate a clock against. That is not a detail: without a definition, two clocks can disagree about the same person and both can be “right” by their own training.
What underwriting uses today
Traditional insurance relies heavily on chronological age for risk classification, alongside sex, smoking, blood pressure, body mass index and medical history. Those factors are not a rough proxy for aging — they are the things aging does to a body, measured directly. The very signals a clock indirectly senses, such as inflammation and metabolic dysfunction, are already captured by existing underwriting, which is why the practical question for an insurer is whether a clock adds information beyond them. The answer in the research so far is: not yet, for an individual applicant.
Why insurers are not buying it yet
The accuracy of epigenetic clocks is a population-level property. Applied to one person, a clock carries an error of roughly four years in either direction — which is often as large as the difference the test is claiming to detect. A reported result of “biological age 46” should really read “epigenetic age 46, range 42 to 50”, and a change between two tests inside that band tells you nothing.
Batch effects, sample handling, the time of day of the draw, sleep, stress and exercise all move the reading. There is no agreed definition of biological age, no gold standard, and no prospective study yet proving that a clock adds independent predictive value for an individual applicant beyond the traditional risk factors. Until such a study exists, a clock adds nothing an underwriter can price on — and insurers, who price on evidence, are not using them as underwriting inputs.
Where it might go
The idea is not dead; it is early. A 2025 paper in the journal Risks proposes biological age underwriting in phases, from a supplementary input to, eventually, a primary risk classifier, and estimates the proposed innovations could reduce longevity-risk exposure by 42–67%. The paper's own 35% figure belongs to its mortality model, not to underwriting: the Investment-Adjusted Mortality Model cut prediction error (MAPE) by about 35% against traditional Lee–Carter approaches during periods of significant medical-technology advance. Insurtech startups including Gero and Deep Longevity already offer biological-age testing services to insurance companies.
None of that is a product you can buy today. The same writing that predicts adoption also flags the barriers: discrimination and anti-selection, data privacy, equitable access, and the need for compliance frameworks if biological age ever becomes a legal and regulatory category. The honest summary is that biological age underwriting is a research proposal with pilots attached, not a market practice.
What this means if you bought a test
If you have paid for a biological age or pace-of-aging test, treat the single number as a rough signal, not a health readout. A result inside the error band is not a verdict on your health, and a change between two tests inside that band is not evidence that an intervention worked. It will not change your premium today: no standard health or life application asks for it, and no underwriting table uses it. What can change your premium is the set of things the clock is indirectly sensing — blood pressure, weight, smoking, blood sugar — measured directly and improved over time, which is also what the condition guides on this site are about.
Worked example
Consider an ILLUSTRATIVE applicant, a fit 50-year-old, told by a test that his biological age is 46 and that he is aging at 0.7 years per year. On the population statistics, the clock is measuring something real. On the individual statistics, the reading carries an error of roughly four years either way — so the honest reading is “epigenetic age 46, range 42 to 50” — and the underwriter, who already has his blood pressure, cholesterol, smoking history and medical record, learns nothing new from it. The example's value is the gap between a population fact and an individual fact, and no real test result, person or insurer is described.
Illustrative example only — not a fact about any real policy.