Phenotypic Age Calculator (Levine 2018)
- Calculator
- About 4 min
- Levine 2018 phenotypic age equation
- Runs in your browser, nothing is sent
- Medical review: Medical review pending
What this calculator works out
Phenotypic age is a way of reading nine ordinary blood markers together with your age as a single number on the age scale. It was built to track mortality risk in a US population survey, not to describe how you feel, and it is one of the few biological age measures with a fully published formula.
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Phenotypic age in years
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Age acceleration
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The published equation, in the open
How this compares with a typical online quiz
| Feature | Typical free quiz | Regenerated.com |
|---|---|---|
| Published equation named | Sometimes | Levine, Lu, Quach et al. 2018, with the coefficient table |
| Units handled | One unit set, often unstated | SI inputs with the US conversion on every field |
| CRP floor explained | Rarely | Yes: values under 0.01 mg/dL are floored so the logarithm stays defined |
| Limits of the model stated | Rarely | Yes: a mortality model from a US survey from the late 1980s to 1994, not a diagnosis |
| Email required to see the result | Often | Never |
| Answers sent to a server | Often | Never; scored in your browser, counts-only events |
Which labs you need and how to read them off a US report
All nine markers come from two routine panels: a complete blood count with differential (white cell count, lymphocyte percentage, mean corpuscular volume and red cell distribution width) and a comprehensive metabolic panel (albumin, creatinine, glucose and alkaline phosphatase), plus a C-reactive protein test. Many clinics order a high-sensitivity CRP, which is the same protein measured with a more sensitive assay; it works here as long as you convert the unit.
US reports usually print albumin in g/dL (multiply by 10 for g/L), creatinine in mg/dL (multiply by 88.4 for umol/L), glucose in mg/dL (divide by 18 for mmol/L), CRP in mg/L (divide by 10 for mg/dL) and white cells in K/uL or 10^3/uL, which is the same number as 10^9/L. MCV in fL, RDW in percent and lymphocytes in percent are the same on both sides of the Atlantic. If your differential gives lymphocytes as an absolute count, divide it by the total white count and multiply by 100.
Use a fasting sample if you can, because glucose is one of the heavier-weighted inputs, and avoid testing in the week after an infection, a vaccine or a hard training block, which push CRP and white cells up and can add years to the result that have nothing to do with aging.
What moves phenotypic age, and what does not
In the published coefficients, three markers carry most of the weight for a given change: red cell distribution width (0.3306 per percentage point), glucose (0.1953 per mmol/L) and the natural logarithm of CRP (0.0954 per log unit). Albumin and lymphocyte percentage pull the age down as they rise; creatinine, MCV, alkaline phosphatase and white cells push it up. Because the model is additive in these terms, a single abnormal value can shift the result by several years, which is why two draws a few months apart are worth more than one.
The measure does not include blood pressure, lipids, weight, fitness or any genetic information, and it was never trained to respond to a specific intervention. Studies that report phenotypic age falling after a program of exercise, weight loss or dietary change are reporting movement in these nine markers; whether that translates into longer life has not been shown in a randomized trial. Treat the number as a summary of your current blood work, not as a prediction about you personally.
Methodology and sources
The calculator implements the phenotypic age measure published by Levine, Lu, Quach and colleagues in Aging in 2018. The authors took 42 clinical markers from NHANES III, the third US National Health and Nutrition Examination Survey, run from the late 1980s to 1994, and used a penalized Cox regression on 9,926 adults aged 20 and over with up to 23 years of mortality follow-up to select nine markers plus chronological age. The linear combination is converted into a ten-year mortality score through a Gompertz model and then mapped back onto the age scale, so that phenotypic age is the age at which that mortality score would be typical in the training population. The coefficients were fixed in the paper's supplement and are not re-estimated here. Because the model was derived in a US adult sample, with US laboratory methods of the early 1990s, it is less certain in people under 20, in pregnancy, in acute illness and in laboratories using different assays.
The arithmetic runs in three steps. First, the linear term: xb = -19.907 - 0.0336 x albumin (g/L) + 0.0095 x creatinine (umol/L) + 0.1953 x glucose (mmol/L) + 0.0954 x ln(CRP in mg/dL) - 0.0120 x lymphocytes (%) + 0.0268 x MCV (fL) + 0.3306 x RDW (%) + 0.00188 x alkaline phosphatase (U/L) + 0.0554 x white cells (10^9/L) + 0.0804 x age. Second, the mortality score: M = 1 - exp(-exp(xb) x (exp(120 x 0.0076927) - 1) / 0.0076927). Third, phenotypic age = 141.50225 + ln(-0.00553 x ln(1 - M)) / 0.090165. Worked example: a 40-year-old with albumin 45 g/L, creatinine 80 umol/L, glucose 5.0 mmol/L, CRP 0.1 mg/dL, lymphocytes 30 percent, MCV 90 fL, RDW 13 percent, ALP 70 U/L and white cells 6 x 10^9/L gets a phenotypic age of 33.0 years and an age difference of -7.0 years. CRP is floored at 0.01 mg/dL because the logarithm of zero is undefined.
The bands on this page are educational, not published thresholds. In the NHANES IV validation by Liu and colleagues (2018), each one-year increase in phenotypic age above chronological age was associated with roughly a 9 percent higher all-cause mortality hazard, and people whose phenotypic age ran five or more years ahead of their calendar age carried clearly higher risk of death, disease count and physical limitation than those running five or more years behind. We use that five-year gap, in both directions, to split the result into orientation bands and treat a gap over ten years as a reason to review the individual markers with a clinician. Reference ranges for every input differ between laboratories.
Medical review: Medical review pending. Last updated .
References
- Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573-591. doi:10.18632/aging.101414
- Liu Z, Kuo PL, Horvath S, Crimmins E, Ferrucci L, Levine M. A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: a cohort study. PLoS Med. 2018;15(12):e1002718. doi:10.1371/journal.pmed.1002718
- Levine ME. Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci. 2013;68(6):667-674. doi:10.1093/gerona/gls233