Have we reached peak longevity?

The July 4 episode of the excellent BBC Radio 4 program, More or Less, addressed a question that demographers and public health researchers have been pondering in recent years: Will upcoming generations be the first to die at younger ages than their parents?  It has been accepted wisdom for a long time that each generation is healthier than the previous one, and life expectancies have risen for generations.  This was largely the result of declining infant and childhood mortality rates until perhaps the 1950's, but in most wealthy countries infant and childhood mortality are now so low that further decreases can't make very much difference in life expectancy; if life expectancy is to continue to improve, it will have to come from improved health at later ages.

But now, given the increasing prevalence of obesity in so many populations, more specifically childhood obesity, the concern is that we're eating ourselves right out of these life expectancy gains.  So More or Less took a look at the numbers.

It turns out that, yes, the obesity rate is higher, but the death rates from obesity related conditions such as heart attacks and stroke have been going down steeply.  Sir Richard Peto, Professor of Medical Statistics and Epidemiology at Oxford, said that while obesity has been rising sharply in Britain, the chances of dying from coronary heart disease-related conditions 30 years ago was 16%, at 1980 death rates, but 4% at 2010 death rates.  That is, it has declined by a factor of 4.

[1] 2009 rates; http://www.worldobesity.org/what-we-do/policy-prevention/ via Wikipedia

The trend is the same globally, the program notes.  Mexico is now the fattest country in the world but the probability of dying from obesity-related conditions at age 70 or younger in 1970 was 50%, but it is now 25%.  This is what's called the Obesity Paradox -- the fatter we get, the less likely it is to kill us.

What's responsible for this?  Well, obesity causes cardiovascular conditions but, so the thinking goes, treatment is better than it was 30 or 40 years ago, so while obese people may have chronic illnesses, they aren't as likely to die from them.  Perhaps they are getting medical care for heart or renal failure, or hypertension and type 2 diabetes, conditions associated with obesity, while thinner people don't see their doctors for anything, and thus are more likely to die.

By this reasoning, though, it's healthier to be ill!  And while the obesity paradox looks real, there's some question as to whether it is instead a statistical artifact.  The sample sizes were small in the studies that showed a benefit to being chronically ill and obese; the diagnoses of heart failure don't all match; the thin controls may be sicker than the obese subjects; when the effects of chronic conditions of obesity become life-threatening, the patient may have lost a lot of weight and no longer be obese (thus, obesity and weight gain themselves may indicate better health); BMI and fat patterning, two measures of obesity, may not be measuring the same thing, and so forth.  (See Habbu et al., e.g., for consideration of the obesity paradox.)

Whether or not the obesity paradox is real, the drop in death rates certainly is.  As Peto said, unless your country is chronically at war, or suffering an HIV epidemic, or you drink gallons of vodka, your probability of dying before age 50 is half what it was 40 years ago.  Or better -- in Iran the probability has fallen from 36% to 6%.

Death rates have fallen in rich countries -- by 1 or 2 percent a year since 1900, according to the National Bureau of Economic Research -- because of clean water, vaccination, antibiotics and other life-saving drugs, safer vehicles, the drop in smoking, improved obstetrics, safer food.  Public health measures, by and large.

Still, if half or more of the population of many countries is overweight or obese, and obesity is the cause of many chronic illnesses, what's going on?  Perhaps it's that it's not actually so risky to be overweight, as a paper in the Journal of the American Medical Association by Flegal et al. reported last year.  This was a meta-analysis of papers reporting the relative mortality risks associated with normal weight, overweight, and obesity, as defined by body mass index (BMI).  The authors found that obesity was associated with higher risk of mortality relative to normal weight, while overweight was associated with significantly lower risk.  It is healthier to be a bit fat than it is to be thin or obese. Perhaps the reserve energy is good when one is ill.

The paper was the subject of much controversy (e.g., discussed here), largely because everyone knows that being overweight is bad for your health.  But apparently there are many ways to be thin and unhealthy, and many ways to be "overweight" and healthy.  Does this answer the question of whether death rates will continue to decline, even as we get fatter?  No, because we haven't solved the looming antibiotic resistance problem, we can't predict which emerging infectious diseases will become pandemic but it's likely that something will, we don't yet know the health or agricultural consequences of climate change, though we can predict there will be some, and so on.

Measures of longevity
Life expectancy is the average age at death at a given age, and that's important, and must be stipulated.  Life expectancy at birth is affected by infant mortality rates.  Life expectancy at age 12 (say, beginning of adolescence) is average age at death of those who have escaped childhood mortality.  And so on.  So we must be aware of more than just chance of dying, but of dying after a specified age as the starting point.

Another important fact is that when we remove one trait -- say, obesity -- as a cause of disease and that disease becomes later or rarer, we automatically increase the risk of death (though perhaps at later ages) from other causes.  That's because if you escape, say, heart disease, you live to get cancer or dementia or arthritis -- or perhaps in the not so distant future, strep throat or gonorrhea.  So all of these health vs longevity statistics need to be viewed with care.

But at least we do know that smoking is still bad for you.

Biomedical Research: A View From the Deep Past

By Jim Wood

A recurrent theme of this bog has been about how best to invest the limited resources available for biomedical research.  I have a peculiar (but I think useful) perspective on this question that grows out of my professional interest in long-term population history.

I study the population dynamics of preindustrial societies.  Some of my work involves historical demography, some of it involves working with traditional farming communities in remote parts of the developing world, all of it involves asking questions about the relationship between the ecology of food production and health/morbidity/mortality, especially among the very young.  So my view of the contemporary scene in the U.S. tends to be that of someone peering out from the Neolithic or some other long-dead period of the past.  And from that point of view, my take on the modern health care crisis in the developed world is:  “Crisis?!  We should only have such crises!”  Let me explain.

Since the eighteenth century, average human life span (or rather life expectancy at birth, which is not necessarily the same thing) in the Western World has roughly doubled – that is, it’s increased by about 40 years.  How can we now achieve a comparable, further increase in U.S. life span based on the kinds of new medical research that are currently being touted?  My answer:  We can’t.  And we probably shouldn’t even try.

The dramatic increase in life expectancy in European and European-derived populations during the nineteenth and the first half of the twentieth centuries had to do almost exclusively with a decrease in early childhood mortality.  It had very little to do with health and survival among the elderly or what we would now (fashionably) call “life span extension”.  In addition, the historical decline in mortality was attributable entirely to changes in environmental conditions, especially exposure to infectious diseases and the ability to fight off such diseases, reflecting (among other things) the immunological effects of under-nutrition and thus the sufficiency and reliability of the food supply.  (In America today we may have lousy diets from many points of view, but nobody can claim that most of us ever go hungry.)  Past medical advances had surprisingly limited effects on this dramatic drop in mortality at the aggregate (population) level.  The “wonder drugs” of my youth – penicillin, streptomycin, etc. – certainly saved lives, but most of the historical decline in mortality had already occurred by the time those antibiotics and most vaccines came onto the scene.  (Note: I am not disparaging vaccines, which I think are a blessing.)  Thanks in part to the evolution of drug-resistant strains of pathogens, infectious diseases are making a bit of a comeback these days, but they are very far indeed from dominating human mortality patterns the way they once did – except, of course, in parts of the present-day developing world.

Since the 1950s, there have certainly been improvements in life expectancy in the West, mostly having to do with the ongoing campaign against smoking and, probably, with a better understanding of the role of dietary factors in cardiovascular disease (again, environmental exposures).  But the improvements have been small, and they have been getting smaller and smaller – despite the ever-spiraling costs of medical research and health care.

But now we are entering (supposedly) a Brave New World of genomic medicine and life span extension – a Brave and Unbelievably Expensive New World in terms of both research dollars and medical care costs.  This investment will, we are reliably informed, lead to our living active, healthy lives until age 120 or older.  In the future, 120-year olds will be hard to distinguish from present-day 45-year olds.  And much of this advance will come from research on the genetics of life span.

As is frequently pointed out on this blog, there are a few major genetic diseases having substantial effects on mortality, and these diseases have long been known and have mostly already been mapped, at least approximately, using what would now be regarded as pretty old-fashioned, low-tech methods.  While treating these diseases can certainly improve individual health and survival, they are mostly so rare that even the most effective treatments would have little effect at the demographic level.  And, because they’re so rare, there’s little economic incentive to invest in their further study.  There’s something else worth noting about these major genetic diseases: they mostly kill at comparatively young ages, so even their total elimination would have basically zero effect on the overall human life span.

Beyond that, genomic medicine has, as Anne Buchanan and Ken Weiss regularly point out here on MT, contributed pretty much nothing to aggregate human health and is unlikely to do so in the future.  I would say the same is true of gerontological science (hang on to those telomeres, kids!).  Recent increases in life expectancy at birth, while real, have been nugatory compared to the historical shift in rates and causes of death.  The idea that we can achieve another 40-year increase in life expectancy is delusional.

Interestingly, a new Pew Charitable Trust poll shows that most Americans are not particularly attracted by the idea of living to 120, even if they are assured of being active, healthy, and alert at that age.  As it happens, I am only one degree of separation from the world’s only well-documented case of human survival past age 120 – Jeanne Louise Calment, who died in southern France about fifteen years ago aged 122.  My colleague Jim Vaupel, who was part of the team of demographers who verified the paper trail linking Madame Calment to her birth records, was invited to her 120^th birthday party.  Afterwards I asked how she was.  His reply: “REALLY OLD!!!”  She sure as hell didn’t look 45.  She was blind and deaf, slipping into dementia, and in general extremely decrepit.  As is the case of most of the oldest old today, her extraordinary longevity had doomed her to years of physical disability and severely impaired functionality.  For my part, I’ll pass on such a medical miracle.

From my Neolithic point of view, only a few pieces of health advice have ever made much difference at the population level: eat as much food as you can (as Michael Pollan would add, mostly plant material), avoid famines and plagues, don’t smoke tobacco (or at least don’t inhale), and keep your latrines as far away from your sources of drinking water as you reasonably can.  Oh yeah, and think about maybe using mosquito nets if they’re available.  “Don’t live in swamps” is also pretty good advice.  Everything else is hype.

My overall conclusion is that the only truly important – and potentially solvable – health problems in the world today are found overwhelmingly in developing countries.  Genomics and gerontology are not going to help solve those problems.  Mind you, the right kind of medical research can certainly contribute toward finding solutions, but only if it can attract funding in today’s market.  And much good work can be done on the cheap.  Think of what would happen if we diverted the money currently invested in, say, genome-wide association studies and used it to buy mosquito nets or oral rehydration packs for the tropics.  Why, then, are we investing all our resources in the kinds of “modern” ailments that only affect the well-off and already long-lived?  As my Neolithic (or Third World) farmer would say, “Crisis?!  We should only have such crises!”

Disease driven poverty

In a few of my previous blog posts I’ve discussed the relationship between poverty and infectious disease.  Many of the most prevalent and severe infectious diseases in the world disproportionately affect the world’s poor.  Part of the reason is that the necessary resources aren’t available for tackling such diseases.  A lot of money is currently spent (wasted?) on designing biomedical ‘cures’ for diseases that persist in some places (usually economically poor places) while having already been eradicated in other places (usually economically rich).  It is my position that diseases such as malaria and tuberculosis remain major threats to some populations simply because of the way that financial resources are allocated in our extremely heterogeneous world.

But there is another angle to this story.

Not only does poverty lead to poor health, but poor health can also lead to poverty.  Quite frequently, that is, the arrows point both ways and the reality is a system in which there are “positive” feedback loops.  There is a growing literature on this type of system which is frequently referred to as a “poverty trap.”  Much of this literature has been in economics, where mathematical models have indicated that populations with infectious diseases are less able to ‘develop’ economically.

With economic development at the population level, e.g. with the growth of average income levels, we tend to see an increase in overall life expectancy at age 0.  Most likely this indicates a relationship between improved health and increased wealth.  However, most of the models that actually look at this relationship are either ecological (they are looking at the entire population and frequently assume homogeneity within the population) or at an individual level.  A few models have also looked at community or household levels.

One major problem with models of all types is that results can change when we change our unit of scale.  The effects of poverty on disease, for example, might be different if we look at a community level rather than a province/state level or even consider an entire nation to be a single population.  This is a problem known as the ecological fallacy (and is closely related to the modifiable areal unit problem) in which causal relationships at the population level don’t explain what is happening at, say, the individual level.  

Regardless of these problems and issues, there does appear to be a feedback loop between poverty and disease.

And this is an interesting thing from an anthropological view.  First off, poverty can mean different things to different people.  For example, to some, poverty means “not modern.”  Some indigenous groups actually choose to live in a traditional house rather than a more modern one.  In my opinion, “traditional” (or not modern) does not equal poverty, but it does get mistaken as poverty.  Poverty can also be a relative thing; something that becomes apparent when you don’t have as much stuff as the people with whom you are coming into contact.  Clearly this may lead to psychological and sociological issues, but it might also explain gradients in outcomes (relative health?)  Finally, there is a type of poverty that exists where people are simply unable to put food on the table.  While there can be some argument about the effects of modernization and relative poverty, I would suggest that this final type of poverty is unambiguous and its negative effects are less debatable.  

In poverty trap models we are frequently interested in investigating and understanding threshold levels under or above which equilibria are reached.  (There are quite a few relatively new papers out that are excellent references (see: Bonds, Keenan, Rohani, & Sachs, 2010; Plucinski, Ngonghala, Getz, & Bonds, 2013; Wood, n.d.)).  Perhaps it is easiest to consider at the unit of the household.

An already poor or marginally poor household in which the major breadwinner is afflicted by severe disease is plagued with multiple problems.  For example, aside from the risk of infection for other household members, if that person is afflicted by malaria or dengue fever, they may not be able to work for several weeks.  A house on the margin of poverty may then fall just enough behind in household money and/or food to fall into true poverty.  Households that are already poor may fall even further.

And an important aspect of this situation is that not only is the person who is actually infected met with further troubles; the entire house is also afflicted.  Furthermore, there tends to be heterogeneity in these effects even within households.  That is, poor households may see things such as greater infant mortality, and this effect may be exacerbated when there is a shortage of food or resources in the household.

In poverty trap models, there are usually equilibrium points in poverty levels that, once reached, are quite difficult to break.  From Bonds et al. (2010):

What may be most important in these debates is therefore not whether the effect of health on poverty is more significant than that of poverty on health, but whether the combined effect is powerful enough to generate self-perpetuating patterns of development or the persistence of poverty.  

Children who grow up in households with frequent food shortages may not have the same physical or cognitive abilities as others.  Their immune systems, already taxed by years of exposure to pathogens, may not be able to fight off diseases as well as their healthy counterparts.  Therefore, when they begin their own households, they are already behind in the nutrition, health, and economic game.  And once again, when adults in the new household fall ill and cannot put food on the table, the children will be disproportionately affected.  

This cyclical pattern, where disease leads to poverty and poverty can lead to disproportionate disease, provides a perfect storm in which there aren’t enough resources to keep from getting sick, where once sick you are likely to fall further into poverty, and once you fall further into poverty you are even further away from pulling yourself and your family out.  This leads to the maintenance of poverty and sickness across the generations.

And this story could perhaps get even more complicated when we consider some evolutionary implications.  For example, populations that have historically been afflicted with malaria also tend to have high proportions of blood and blood-related disorders that seem to protect against malaria.  Almost all of these disorders are harmful in some cases (for example, in homozygotes).  Therefore the evolutionary history of disease can lead to a situation where some individuals are actually plagued with sickness from the very beginning of life.  Paradoxically, under situations of heavy malaria burden, some people with these disorders will apparently be healthier than their non-affected counterparts.  I don’t know whether the side effects of these disorders are enough to lead to poverty traps on their own.

Finally, in an age when many scientists appear to be looking “for the gene for (fill in your favorite thing to study)”, poverty traps and households are an interesting thing to ponder.  Poverty and the apparent predisposition of household members toward succumbing to disease can look like a genetic effect.  If it runs in families, and certainly both poverty and sickness do, then it can look a whole lot like there is a genetic reason for it.  I think that poverty trap models are therefore a nice illustration of how we could arrive at the same phenotype (poverty and sickness) from purely socio-economic and ecological factors.  

REFERENCES:

Bonds, M. H., Keenan, D. C., Rohani, P., & Sachs, J. D. (2010). Poverty trap formed by the ecology of infectious diseases. Proceedings of the Royal Society B: Biological Sciences, 277(1685), 1185–92. doi:10.1098/rspb.2009.1778

Plucinski, M. M., Ngonghala, C. N., Getz, W. M., & Bonds, M. H. (2013). Clusters of poverty and disease emerge from feedbacks on an epidemiological network. Journal of The Royal Society Interface, 10(80), doi: 10.1098/rsif.2012.0656.

Wood, J. (in press). The Biodemography of Subsistence Farming: Population, Food and Family. Cambridge University Press.