This test is most useful if any of these apply to you.
Two people can be the same age on the calendar and have very different blood-marker patterns. Yearly bloodwork can hold clues, but most labs are read one number at a time. This score combines routine blood markers into a single estimate of whether your biology looks more like a healthier-aging pattern or a higher-risk one.
This is a newer, exploratory aging measure. It is not a diagnosis, and there is no official cutoff. Use it as a baseline and a trend, then read the score beside the markers that created it.
The Longevity Score is not one substance in your blood. The specimen is a blood draw. Some inputs are measured from serum or plasma and others from whole blood, but the score itself is calculated after the component tests are done.
The score is built from many routine markers at once, weighting patterns linked with healthier aging. Inflammation, blood sugar control, cholesterol handling, immune balance, kidney function, and liver function can all affect it.
Published models like this use machine learning trained on large medical-record datasets. In one Nature Aging model, a mildly low neutrophil count and lower alkaline phosphatase tracked with healthier aging apart from major chronic disease risk. Neutrophils are a type of white blood cell. Alkaline phosphatase is an enzyme measured in routine blood chemistry. Those patterns would be easy to miss if each marker were read alone.
Because the inputs are ordinary blood tests, the score measures your marker profile directly. What it reflects, aging speed, is an inference drawn from how those markers behave in large populations, not something the blood literally shows.
The strongest outcome data come from related biological-aging scores, not this exact Longevity Score. In a UK Biobank cohort of 332,012 adults, people in the fastest-aging quarter had 54% higher overall mortality risk and 41 to 44% higher risk of developing more than one chronic condition than those in the slowest-aging quarter.
Life expectancy moved the same way. At age 45, people who already had three overlapping condition categories lost 5.3 years compared with healthy peers. If their biological aging was also accelerated, the loss was another 5.8 to 7.0 years in that study. These figures came from KDM-BA and PhenoAge, not this score.
Related composite health scores point the same way. Adults with the healthiest profiles on a widely studied heart-health index lived longer free of heart disease, diabetes, cancer, and dementia: roughly 6.9 more disease-free years for men and 9.4 for women, measured from age 50. That index is not this score, but it is built from overlapping ingredients.
A low Longevity Score is a prompt to look closer, not a verdict. Its main use is pattern recognition: it can flag a set of ordinary-looking labs that may deserve attention together.
This score has no official cutoff that says healthy above here, worried below there. That sounds like a weakness. It is why your trend matters more than any single number: your own past readings become the reference point that no population range can give you.
One reading can wobble after a cold, surgery, or a hard race. A repeated direction is harder to fake, especially when the same component markers explain it each time.
A few things can push the number around without your aging actually changing. The first one matters most, because it is common and easy to miss.
Evidence-backed interventions that affect your Longevity Score level
Longevity Score is best interpreted alongside these tests.
Longevity Score is included in these pre-built panels.