How we calculate your trajectory

We start from period life expectancy for your country and sex, then add the survivorship adjustment for your attained age. This is the standard life-table property that people who have already reached 60 have a higher expected age at death than a newborn in the same population.

Nothing about you as an individual is in this number yet — it is purely the population you belong to.

Healthy life expectancy (HALE) is published by the WHO and estimates the years a person can expect to live in full health, with years lived in less than full health weighted down. We use the country-specific HALE-to-life-expectancy ratio and apply it to your estimated lifespan.

Profiles associated with lower chronic-disease risk get a small compression adjustment, reflecting evidence that healthier profiles tend to shift a larger share of years into good health rather than simply extending years of illness. The adjustment is deliberately conservative, capped at a few percent.

Each factor in the questionnaire maps to an adjustment in years, derived from published associations between that factor and all-cause mortality. Factors with strong, replicated evidence — smoking, physical activity, blood pressure, glucose — carry more weight than factors with emerging evidence, such as perceived stress.

The adjustments are then dampened with a saturating function so a long list of small effects cannot compound into an implausible total. In other words: the model refuses to promise you twenty extra years.

Unknown answers are neutral. Answering "I don't know" for blood pressure, cholesterol or glucose does not reduce your estimate.

Lifestyle age expresses the size of your total adjustment on the age scale: how old somebody with an average profile would be to sit where your profile sits. It is an illustrative comparison score, not a biological measurement, and it should not be confused with epigenetic or biomarker-based biological age tests.

The What if? simulator does not use separate logic. It rewrites your answers to reflect the change you selected and runs the identical model again, returning a baseline, a scenario result, the difference and an evidence indicator.

Scenario outputs are shown as ranges. A model like this can honestly distinguish "roughly two years" from "roughly nothing"; it cannot honestly distinguish 87.3 from 87.6.

Every result records the model version used, currently v1.0. When datasets or coefficients are updated, older results remain interpretable against the version that produced them.

960 is a consumer wellness and education product. It does not diagnose, screen for, or predict disease, and it deliberately avoids reporting individual disease probabilities, because that would require clinically validated risk equations and clinical inputs we do not collect. Risk is discussed only as broad domains and educational context.