It isn’t just how long we might live that’s of interest. It also matters a lot how healthy our future years are. We’ll see in this post that health is a tough thing to measure.
Life expectancy measures a quantity of time. It says nothing about the quality of that time. And therefore a natural question that arises is: how much of one’s future life expectancy is likely to be spent in good health? That’s what “healthy life expectancy” measures.
You can guess one thing about such a measure before you ever look at the actual numbers. There’s not a lot of ambiguity about whether someone is alive or dead. In contrast, there’s a lot of ambiguity about whether someone is healthy or not, and if not, how unhealthy that person is. And so it’s inevitable that measures of healthy life expectancy are less reliable than measures of life expectancy; that measures will vary depending on how health is perceived; and that from time to time there will be changes in the classification of health perception and therefore in the measures themselves even when nothing has actually changed. In short, we know there’ll be some subjectivity rather than pure objectivity in the numbers.
Nevertheless, it’s interesting to at least get some order of magnitude for healthy life expectancies, to compare them with life expectancies, even if we should interpret the numbers in a sort of touchy-feely way.
Of all the many papers on the subject, there’s an early one by Michael Wolfson, then the Director General of Statistics Canada, that sets out the concepts (and one particular approach to measurement) very well, so I’ll rely on it for my explanation here.
A sample survey of Canada’s population was taken for two purposes. One was to establish the prevalence of six broad kinds of ill health: sensory problems (vision, hearing and speech); mobility; emotional state; thinking and memory; dexterity; and level of pain and discomfort. The other was to assign a score to how bad the ill health was, by asking the respondents to rank preferences for various health conditions (yes, very subjective). From that a proportion and a degree of ill health were estimated for each age and gender, and then these numbers were combined with life expectancy tables.
For example, if for a particular combination of age and gender 30% of the population had some form of ill health with an average severity of 40%, the aggregate ill health is as if the product of the two numbers (meaning 12%) are totally ill and the remainder (meaning 88%) are perfectly healthy; so this group is assessed as having spent 88% of its year in good health (and therefore 12% of its year in a state of perfectly ill health, or total disability). And so on. Eventually it becomes possible to estimate how many years of perfectly good health and how many years of perfectly ill health are contained in the group’s life expectancy.
Many other approaches are feasible. For example, in 2001 the UK census for the first time asked the question: “Over the last 12 months would you say your health has on the whole been: Good? Fairly good? Not good?” And “good” and “fairly good” are counted as healthy and “not good” as unhealthy. Or there’s a “global burden of disease” study to estimate severity-adjusted prevalence by age and gender. For example, dementia is assessed as 66.6% disabled, AIDS 54.7%, low back pain 32.2%, blindness 19.5%. That was in 2010. But 6 years earlier, low back pain was 6.1% and blindness 59.4%. Assessments can change substantially.
You get the idea that these numbers should not be treated as gospel.
Now for some results, and then some helpful overall conclusions from Wolfson.
Table L 03.1 shows a small and arbitrary selection of countries for which The World Health Organization published these international comparisons in 2016, for males and females combined, for life expectancy and healthy life expectancy at birth. And Table L 03.2 shows the corresponding numbers for those who survive to age 60.
Table L 03.1: Comparison of life expectancy and healthy life expectancy at birth
Country LE at birth (yrs) HALE at birth (yrs) Ratio HALE/LE
Japan 83.7 74.9 89%
Australia 82.8 71.9 87%
France 82.4 72.0 87%
Canada 82.2 72.3 88%
Netherlands 81.9 72.2 88%
United Kingdom 81.2 71.4 88%
Germany 81.0 71.3 88%
USA 79.3 69.1 87%
Poland 77.5 68.7 89%
China 76.1 68.5 90%
Russian Federation 70.5 63.3 90%
India 68.3 59.5 87%
Table L 03.2: Comparison of life expectancy and healthy life expectancy at age 60
Country LE at 60 (yrs) HALE at 60 (yrs) Ratio HALE/LE
Japan 26.1 21.1 81%
Australia 25.5 19.6 77%
France 25.7 20.3 79%
Canada 25.0 19.7 79%
Netherlands 24.2 19.3 80%
United Kingdom 24.1 18.8 78%
Germany 23.7 18.6 78%
USA 23.6 18.1 77%
Poland 21.8 17.0 78%
China 19.7 15.9 81%
Russian Federation 18.6 15.1 81%
India 17.9 13.3 74%
Notice that all the healthy life expectancies at birth are almost 90% of the respective life expectancies. And since young and middle-aged years are typically much healthier than post-work years, much of the gap between the total and healthy life expectancies must occur after age 60. In other words, the ratio of healthy to total remaining life expectancy at 60 must be noticeably lower than 90%.
Sure enough, the ratio at age 60 has dropped to around 80%.
Remember that the measuring convention for HALE is to split the count between those who are notionally completely healthy and those who are notionally completely disabled. So the 80% is not as clean as saying that we can expect 80% of our future lifespan at 60 to be completely free from disability, unless we also accept that the other 20% will be spent completely disabled. In practice, therefore, what this means is that we are likely, on average, to spend something less than 80% completely healthy and therefore something more than 20% at least partially disabled.
I searched extensively for further statistics that I would have found insightful, without success. For example, in any given country, for each gender/age combination, show me the prevalence of disability, that is, the proportion of the population of that gender and age with some form of disability. Show me also, for those without disability at each gender/age combination, the incidence of disability, that is, what proportion of the healthy change from healthy to disabled at that age. If I’m healthy, this would give me some initial idea of how likely it is that I will develop some disability in the next year. Some prevalence statistics exist. But incidence statistics were beyond my ability to locate.
On the whole, while the actual numbers are indications at best, I found Wolfson’s four overall conclusions very helpful in interpreting them.
- First, he says that the societal burden of ill health is higher for women than for men. “Since the prevalence of chronic conditions increases with age and women live longer, they spend a longer period with chronic conditions. Also, at age 65 and older, women tend to be in notably poorer health than men the same age.”
- Second, the burden is highest among those in early old age, not among the most elderly. By this he means that there are so many more people in early old age that their ill health aggregates to a more serious problem for society than the fewer (though less healthy) really elderly. Note that that’s a societal rather than an individual burden he’s talking about. From an individual perspective, I have no doubt the burden increases with age.
- Third, sensory problems and pain comprise the largest components of the burden of ill health. (And that was before low back pain was assessed more severely by the WHO.)
- Finally, higher socioeconomic status confers a dual advantage, longer life expectancy as well as a lower burden of ill health.
In most countries, the average person can expect to spend something up to 80% of our expected future lifespan after age 60 in reasonably good health.
 It goes by other names too, such as “health-adjusted life expectancy (HALE)” or “healthy life years” or “disability-adjusted life years”.
 Wolfson, Michael C. (1996). “Health-adjusted life expectancy”. Statistics Canada Health Reports, Vol. 8 No. 1 (Summer 1996).
 Cited in wikipedia, “World Health Statistics 2016: Monitoring health for the SDGs Annex B: tables of health statistics by country, WHO region and globally”. World Health Organization. 2016. Retrieved 27 June 2016.
I have written about retirement planning before and some of that material also relates to topics or issues that are being discussed here. Where relevant I draw on material from three sources: The Retirement Plan Solution (co-authored with Bob Collie and Matt Smith, published by John Wiley & Sons, Inc., 2009), my foreword to Someday Rich (by Timothy Noonan and Matt Smith, also published by Wiley, 2012), and my occasional column The Art of Investment in the FT Money supplement of The Financial Times, published in the UK. I am grateful to the other authors and to The Financial Times for permission to use the material here.