To calculate someone’s life expectancy, scientists look for molecular changes that take place in cells. This approach determines mortality risk by focusing on a person’s rate of aging (biological age) as distinct from their chronological age.

But a novel approach has emerged that takes information from routine blood tests carried out at a doctor’s office. Proponents of the new strategy suggest these readily-available measurements can be used as a practical, accurate and easy-to-interpret “lifespan calculator.”

Unlike genetic tests, which provide information that’s engraved in stone, the blood data used to establish biological age can be modified by lifestyle changes to increase an individual’s lifespan.

The new aging measure is called Phenotypic Age. Here’s how it works. . .

Women Age More Slowly Than Men

A team of scientists from various institutions such as Yale, Johns Hopkins, UCLA and the National Institutes of Health analyzed 42 biomarkers taken from 9,926 people who took part in the US National Health and Nutrition Examination Surveys (NHANES).

Taking six years (1988 -1994) of medical, lifestyle and mortality data, the researchers were able to identify nine key clinical measures that determined risk of death and life expectancy.

They then validated these nine biomarkers by looking at a further 11,432 people aged 20 – 84 taken from NHANES between 1999 and 2010.

The researchers found Phenotypic Age, compiled from the nine blood markers, predicted all-cause mortality consistently and accurately.

Women were found on average to have a lower phenotype compared to men of the same age, i.e. they aged more slowly.

Predicts Mortality Even Among Healthy People

If Phenotypic Age was much higher than a person’s real (i.e. chronological) age, the risk of dying younger shot up.

A quarter of the fastest-agers among 50 to 64-year-olds died over the following decade compared to only one in five of the slowest agers in the 65 to 84 age group. In other words, older people with a healthy Phenotypic Age were at less risk of death than younger people with a poor score on this metric.

For every additional year Phenotypic Age was above chronological age the risk of death rose by 14, 10 and 8 per cent in those aged 20 – 39, 40 – 64 and 65 – 84 respectively. To unpack that and make it more graphic, a 25-year-old with a Phenotypic Age of 26 was at 14% greater risk of death than a 25-year-old with a Phenotypic Age of 25.

In short, being “old for your age” is not a good thing.

The authors wrote, “The finding that Phenotypic Age was predictive of mortality among both healthy and unhealthy populations is novel.

“…we were able to show that Phenotypic Age was predictive of all-cause mortality among disease-free, healthy older adults.

“This suggests that Phenotypic Age is not simply a measure of disease or morbidity and instead may be a marker that tracks the effect of aging before diseases become clinically evident.

“This suggests that in a clinical setting, Phenotypic Age could be used to stratify risk among persons who otherwise ‘appear’ healthy.”

I think this figure could be useful for motivating people. Compared to the usual “You need to get your blood pressure down, you need to get your blood sugar down, etc.”, this test provides a vivid reminder that you’re literally taking years off your life if you don’t.

The Nine Biomarkers of Aging

These are the metrics the test uses, and what they may indicate:

  • albumin: liver or kidney disease
  • creatinine: kidney problems
  • glucose (blood sugar): insulin resistance/diabetes/metabolic syndrome
  • C-reactive protein: marker of inflammation
  • lymphocyte per cent: immune system problems
  • mean cell volume (size of red blood cells): anemia or vitamin deficiencies
  • red blood cell distribution width (shape/size of red blood cells): anemia, nutritional deficiencies, liver disease
  • alkaline phosphatase: liver or bone-related problems
  • white blood cell count: compromised immune system or bone marrow disorder

Commenting on the research, Dr. Morgan Levine, pathologist at Yale and lead author, believed the test’s biggest advantage was in preventing disease developing in those at high risk.

“It’ll show you how you can reduce their risk because you can plug all the numbers in and see how the risk drops if they bring their glucose down for example,” she said.

Dr. Levine and her team are now working on the next step: to develop concrete ways for people to slow down or lower their biological age.