July 31, 2019| By Jean-Marc Fix, FSA, MAAA
Mercifully, death happens only once to each of
us. Nonetheless as I look at my Facebook feed, I can’t help but notice that
death and disease are taking more and more space, surpassing news about
weddings and births. You might say aging is an unfortunate, yet inescapable,
fact of life. I say it is an opportunity to learn about mortality, past
and future.
Mortality Compression
and Trends
As mortality rates have decreased at younger
ages, a larger proportion of all deaths occurs in a smaller number of advanced
years. This increase in concentration of deaths makes for better statistical
significance, as more deaths make it easier to get to the true rate of death.
For the same reason that it is hard to know if a coin is fair by tossing it
only once versus tossing it a million times, with more data you have more
information. It also makes it more important to get it right.
So let’s take a look at the number of male
deaths in the U.S. from 1960 compared to 2017.
This statistical stability may lure us into a
false sense of safety as we try to predict the future. And, what’s happened to
the death rate of 75-year-old males before 2010?
What do you think happens if we check the death
rate through 2017?
Surprise!
The Issues With Causes
of Death
Some, like Jim Vaupel, have posited that life
expectancy improves at a very constant rate despite the opinions of experts in
the field.1 No rationale is given: It just is, like the
Sommerfeld fine structure constant or Moore’s Law. I can’t help but equate it
to the uneasy feeling of the person who jumps from the Empire State building
and can be heard, as he falls by each floor, saying “…so far, so good…”.
Everyone will die of something. We all, and
maybe actuaries and underwriters even more so, like to classify things to help
solve problems. We look for insight, trying to understand the cause of death.
Of course, understanding the various causes of death can help us predict the
future, but this knowledge is of limited long-term value, although causes of
death for chronic conditions, especially critical at the older age, have a lot
of inertia and do not change quickly, they do change.
Two issues complicate how we can use information
about the causes of death. The first is that the recording of the cause of
death is fraught with difficulty. When the latest version of the International
Classification of Diseases (ICD 10) implemented a different hierarchy of
causes, it created a sudden discontinuity in data, requiring macro adjustments
in the statistics and artefactual changes in the trends; for instance, the
incidence of Alzheimer’s disease.
This complicates the accurate and consistent
recording of the relevant cause of death.
The second issue is an effect highlighted by the
work of John Wilmoth, which modeled causes of death.2 He
confirmed, as cited in a soon to be published SOA research report, that the
more causes you look at, the more pessimistic your view of future mortality
becomes from a mathematical standpoint. The most pessimistic cause with the
highest mortality rate tends to dominate your model.
Causes of Death - and
Drivers of Mortality
Cause of death doesn’t change by chance. Cause
of death is influenced by treatment and medical technology. Today, you don’t
necessarily die from a heart attack because we can restore your heart’s
function. Yet we know that underlying factors strongly impact causes of death,
and they are influenced by demographic and behavioral changes. Most students of
mortality will recognize the impact of decreasing smoking prevalence - and
increasing prevalence of obesity - in the mortality changes we have seen,
although the later has still not had an impact on older ages in a clear way. Very
few people have died directly from smoking or from being obese, yet the impact
of both is significant and, in my mind, critical to understanding the future of
mortality.
Those “causes of causes” are what we call the
drivers of mortality. Understanding what they are, their impact, which is
changing, and their reach will give us the clues to project mortality in the
mid-term. Some we know, such as smoking and obesity. Others we can see coming
like the impact of obesity on children or better nutrition and the adoption of
a healthy lifestyle around exercise and activity (10,000 steps anyone?). Some
are harder to quantify, such as the impact of driverless cars or immunological
treatment of cancers such as CAR T-cell immunotherapy.3 Harder
to quantify but certainly not safe to ignore.
As for the long term? The distant future is a
combination of many factors, both individual and societal. Like in the past,
maybe you’ll hear me say as I go by your office window “so far, so good.” Will
you think I’m falling, though? Maybe I’m flying…
Endnotes
All mortality charts created via Human Mortality Database (HMD). Life Table for Males and
Females 1x1 (Age Interval x Year Interval)
1.
Vaupel.
2.
Wilmoth, John R.,
“Are mortality projections always more pessimistic when disaggregated by cause
of death?,” Mathematical Population Studies, An International Journal of
Mathematical Demography, Vol. 5, 1995.
http://www.genre.com/knowledge/blog/understanding-mortality-lessons-from-older-ages-en.html?utm_campaign=Subscription%20Management%20Center&utm_source=hs_email&utm_medium=email&utm_content=75197307&_hsenc=p2ANqtz-9rxnn8Luv6fMKjP5S7ZJkcLhmtb31AQAnktApzfXXfQrIpcpEGsc8AFannKH2hsOW2agjxQkRm4mm6suQkerIEWoo8QA&_hsmi=75197307
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