October 21, 2014

How Old are YOU? A New Way to Measure Age.

“You’re only as old as you feel."

“Sixty is the new forty.”

Those are just two examples we use to indicate that measuring age is a blurry business.

I might say “I’m 85 years old,” which is true. OK, it means I was born in 1929. But what does that fact really say about my health and my prospects for the future? A lot more than actuarial tables might suggest, according to a new study.

I’ve learned that every person with Parkinson’s has his or her own individual disease… and experiences its symptoms and medications uniquely. In an interesting post last month in one of my favorite blogs, “The New Old Age” in The New York Times, writer Judith Graham shows how measuring age – like the Parkinson’s example -- depends very much on the individual. Like never before in our history – as healthcare improves and longevity increases -- measuring age involves a lot more than counting the passing years.

In her article -- "On New Measurements of Aging" -- Graham recaps a Q&A with a professor of social and behavioral sciences. In that conversation, the teacher describes an easy, and – to me – completely novel way to determine when “old age” begins.

Here’s that brief exchange:

Q:  Your work over the past several years suggests that the conventional definition of old age — as beginning at age 65 — is outdated. Why?

A:  Life expectancy has changed. Disability rates have changed. Health status has changed. Everything is changing about 65-year-olds. They’re not the same as they were in 1950 or as they will be in 2050. Still, conventional measures used across the world treat everyone as becoming old starting at age 65. That distorts our view of aging and public policies related to aging.

Q:  How should we think about the onset of older age?

A:  We should consider people as old when they near the end of their life: when their remaining life expectancy is 15 years or less. Let’s take two 65-year-olds. Say one has a remaining life expectancy of five years. One has a remaining life expectancy of 25 years. Which one is aging faster? We would say the first one, because she’s so much closer to the end of her life. The second one is still far from the end of her life. She’s effectively younger.

Q:  What would this mean in the United States?

A:  In 2010, if you used our definition, men would start being classified as “old” when they reached the age of 69.2 years old and women when they reached the age of 72.3 years old.

Q:  You’ve proposed what you call a "characteristics" approach to evaluating aging. What does this entail?

A:  We think age has much more to do with how people function than how many birthdays they’ve had, so measuring function is the crucial thing. Our research agenda calls for looking at different measures of functioning because aging is multidimensional. We started with hand-grip strength, a measure of upper-body strength.

Q:  Why did you begin there?

A: Hand-grip strength is an amazingly good predictor of future rates of mortality and morbidity, or sickness. It’s been measured for individuals in surveys across the world. We now have comparable data on about 50,000 people from the U.S., many European countries, Japan, South Korea, China. A substantial body of research suggests that this can be used as a reliable predictor of aging.

Q:  Tell me about the study you just published.

A:  We know there are important differences in the U.S. in life expectancy among groups with different levels of education. We decided to compare men and women with low education — those who never graduated from high school — with those with higher education. We wanted to compare them in terms of how rapidly they were aging based on their hand grips.

Q:  What did you find?

A:  A 65-year-old white woman with low education had the same hand-grip strength as a 69.5-year-old white woman with more education. The woman with low education had an age disadvantage of about 4.5 years. She was more like an old person than the woman with higher education. 

For a 65-year-old white man, the difference was 4.6 years. For African-American women, the more educated women had a 3.5-year advantage. For African-American men, there was no difference between people with low and higher education. We don’t understand that finding, but we think it’s interesting and something we need to follow up on.

A:  What are the implications?

Q:  Measuring hand-grip strength is very simple and cheap. We think every primary care doctor should have a dynamometer in their office. At every visit, the doctor could check grip strength for older patients. If someone was in the 45th percentile for their age and the measurements were stable, great. But if that person suddenly dropped to the 25th percentile, then that’s a sign that the doctor should look seriously at what might be going on.

We view this in a larger context. There are going to be more measures than this one. We want to look next at measures of lower-body strength. It may very well be a measure that looks at how long it takes someone to rise from a chair. Then, we will have an upper-body measure and a lower-body measure, and we can compare the two in terms of how aging goes. We envision one day that physicians will have standard age-related tables for these measures and chart their patients’ progress, just as they do with height and weight for children.

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The online journal PLOS ONE included the study’s abstract in a recent article, "Measuring the Speed of Aging across Population Subgroups."

People in different subgroups age at different rates. Surveys containing biomarkers can be used to assess these subgroup differences. We illustrate this using hand-grip strength to produce an easily interpretable, physical-based measure that allows us to compare characteristic-based ages across educational subgroups in the United States. Hand-grip strength has been shown to be a good predictor of future mortality and morbidity, and therefore a useful indicator of population aging. Data from the Health and Retirement Survey (HRS) were used. Two education subgroups were distinguished, those with less than a high school diploma and those with more education. Regressions on hand-grip strength were run for each sex and race using age and education, their interactions and other covariates as independent variables. Ages of identical mean hand-grip strength across education groups were compared for people in the age range 60 to 80. The hand-grip strength of 65 year old white males with less education was the equivalent to that of 69.6 (68.2, 70.9) year old white men with more education, indicating that the more educated men had aged more slowly. This is a constant characteristic age, as defined in the Sanderson and Scherbov article “The characteristics approach to the measurement of population aging” published 2013 in Population and Development Review. Sixty-five year old white females with less education had the same average hand-grip strength as 69.4 (68.2, 70.7) year old white women with more education. African-American women at ages 60 and 65 with more education also aged more slowly than their less educated counterparts. African American men with more education aged at about the same rate as those with less education. This paper expands the toolkit of those interested in population aging by showing how survey data can be used to measure the differential extent of aging across subpopulations.

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