Monday, May 20, 2013

Retirement harmful to health or... an uncertainty principle?

Years and years:  but who's counting?
Breaking news!  As reported by the BBC ("Retirement Harmful to Health"): "...the chances of becoming ill appear to increase with the length of time spent in retirement."  Even more astonishing, the effect is the same for men and women. 
The study, published by the Institute of Economic Affairs (IEA), a think tank, found that retirement results in a "drastic decline in health" in the medium and long term.
The IEA said the study suggests people should work for longer for health as well as economic reasons.
This is of course just as astonishing as the fact that having more birthdays increases your lifespan (someone must have won a Nobel prize for that discovery! or at least got a headline story in the NY Times Science supplement).

Retirement is, of course, highly correlated with aging, which is, obviously, highly correlated with length of retirement and, of course, aging is highly correlated with ill health.  Further, people still working but already in ill health are more likely to retire than people healthy and still able to work well into old age.  And, since the report considers mental as well as physical health, it's also relevant that people with an ill spouse may be more likely to retire, which may increase their chances of becoming depressed.  So if this study had reached any other conclusions than that retirement is correlated with ill health, that would have been worthy of headlines.

It turns out that the background to the report treats the question in a relatively nuanced way, even if the conclusions are much less nuanced. E.g., from the report:
...evidence suggests that poorer health increases the likelihood of retirement. When looking at health and retirement it is therefore very difficult to separate cause from effect. In addition, a plethora of variables that cannot be observed are likely to bias results in any empirical studies -- and it is difficult to predict the direction of the bias.
Further, "Theoretically, the impact of retirement on health is far from certain."  "Other mechanisms by which retirement can affect health appear equally ambiguous."  " observed correlation between retirement and health says nothing about causation."  "Overall, the most methodologically convincing research on the health effects of retirement is rather mixed. This is likely to be due to researchers employing different research strategies and data."

But, they do report, from interview data with 7000 - 9000 people after varying numbers of years of retirement, more self-reported mental illness, more prescription drug usage, more diagnosed physical problems, and so on among retired people than those still working, and finally conclude that retirement is harmful to health.  Indeed, the report is titled "Work Longer, Live Healthier" so there's no missing their point.

It's true that other studies have found positive effects of retirement, but the authors write, "The results have been cross-checked against the methodologies used in earlier research studies, and it has been found that the positive impact of retirement on health found in earlier studies is, at the very least, partly due to shortcomings in that research."

Well, in fact it's hard to know how to do a study that would properly answer the retirement/health question.  When poor health can 'cause' retirement and retirement can (says this report) 'cause' poor health, how do cause and effect get teased out? 

A study comparing cases and controls would be problematic; can 'controls' who are still working be assumed to match retired 'cases' if the variable being measured (health) can affect whether someone works or retires? And, aging and ill health are already highly correlated, as are retirement and aging.  So disentangling cause from effect is inherently difficult.  

And several other things.
The risks and histories clearly involve cultural and lifestyle factors.  These change all the time, and indeed are affected by stories like the current one that, in itself, might lead readers of the story not to retire, because they'll think they're committing suicide to do it.  And what about all sorts of other factors like smoking history, involvement in wars and economic crashes and their harmful effects, and who knows what else that affects our health and our attitudes on a daily basis?  One thing that is certain: our exposure to those things in the future, which would affect the issue of health after retirement, is uncertain, in principle: as any study that purports to project results into an unknown future environment, this study cannot have any easily knowable implications for years beyond the immediate future at best.

And, if you have a relative who died early from, say cancer or a coronary, you may be driven to retire early to have a chance at enjoying life before your number comes up, if you think your relative's experience reflects your own vulnerabilities.  Or conversely, if your father lived to 110, you might think you will too, so why not sock away a few extra years' pension funds, publish some more astonishing research papers, or whatever.  That is, what may be irrelevant or at least unmeasured factors can confound this type of study.  Even knowing that you don't have to retire, may affect what you decide.  Or seeing what happens to your peers as they drop out of the office and/or off their perch.

The analogy with quantum mechanics: the Heisenberg principle
In a sense, what we see here, at least potentially, is something like the phenomenon in quantum mechanics in which an electron or photon exists as a wave, until you measure it.  Then, it collapses to a point, but because you've measured, say, its location, you can no longer measure its momentum.  The reason is that the very act of observing and measuring it changes its behavior.  This, loosely speaking, is the Heisenberg uncertainty principle.

Here, too, there is a quite similar-seeming uncertainty principle:  the very act of doing the study and publishing its results will affect the future course of the very people whose future you're trying to predict with your data.  The relevant behavior of the people you studied, and others who read the research, is affected by the fact that you did the study.  How that alters behavior is uncertain and basically not knowable.

But, the bad news that retirement is harmful to people's health is good news for governments looking to save money. Raising the age at which people can begin to draw their pensions is one way to save a lot of money, because people will contribute to retirement funds for more years and draw it for fewer. We just wish the evidence were sturdier.


Jim Wood said...

A few years ago, the press reported on a study showing that famous orchestra conductors had longer lifespans than the general population (a difference of about five years, as I recall). Much speculation about the health benefits of conducting followed. Most centered on the beneficial effects of having a satisfying career. Jane Brody of the NYT, on the other hand, suggested that the upper body movement associated with vigorous conducting improved circulatory health. It was quite some time before someone pointed out that the study had compared life expectancy at birth in the general population to life expectancy conditional on surviving long enough to become a famous conductor in the comparison group (never mind all the other ways in which famous conductors might differ from the general population: wealth, ethnicity, better health BEFORE becoming a conductor, etc.). So it was a bit like reporting that "110-year-olds live longer than most people." And this stuff gets published and influences people's decisions about their lives.

Ken Weiss said...

I heard a recent radio program, on the BBC I think, that discussed this. I'd say that another effect on the inference is that the question was raised in the first place by someone who noticed the longevity of some famous conductors like Toscanini. So there is, to me, another instance in which the proper Null (in a properly designed sample!) would be extra longevity rather than none.

Bill said...

Life is correlated with death.

Ken Weiss said...

This is a difficult one, because a sample may entirely expire, but there can always be another sample in which one or more won't. Since NIH (and NSF) only fund limited studies (well, except for 'omics studies), one can't ever see if an exception will occur.

But if an exception does occur one would probably still be able to reject immortality with a very very low p-value.

Jim Wood said...

Yes, but how do you measure death? Self-report?

Ken Weiss said...

Sure! As of course you know, Jim, self-selected sampling is a widely accepted study design....