Before I set up the context for this post, I am going to throw this out to you. Think of putting rocks on a scale to achieve the weight of, let’s say, 1,000 lb. And let’s say that you are required to use rocks of similar size. You have a bunch of bricks — these are your biggest “rocks,” and you have a bunch of pebbles like the ones I have in my driveway (perhaps you have them in yours too). In order to get to 1,000 lb, will you need more bricks or more pebbles? I am not trying to trick you.
Before I set up the context for this post, I am going to throw this out to you. Think of putting rocks on a scale to achieve the weight of, let’s say, 1,000 lb. And let’s say that you are required to use rocks of similar size. You have a bunch of bricks — these are your biggest “rocks,” and you have a bunch of pebbles like the ones I have in my driveway (perhaps you have them in yours too). In order to get to 1,000 lb, will you need more bricks or more pebbles? I am not trying to trick you. This is just an illustration of the fact that you can get to the same magnitude of a variable (in this case weight) by either using a smaller number of more weighty components (bricks) or a larger number of lighter ones (pebbles). Keep this in mind as you read on below.
I got an interesting comment from Brad F. on my post from yesterday regarding the 10% number for the premature death avoidance attributed to access to medical care. He pointed me to a blog post on the always-informative The Incidental Economist web site which called this a “zombie statistic.” Despite having a fifteen-year-old who is an avid fan of zombie fiction and film, I was not familiar with this term, but inferred its meaning pretty easily.
The gist was that when people started to look for the origins of this number, the evidence was difficult to find, and, when discovered, was at best shaky:
Thus, as Austin and Adrianna had found, the 35-year old CDC paper seems to be at the root of the often-cited 10% number; it’s “paper 0,” if you will. But those that continue to reference 10% as an estimate for health care’s contribution to health should know that the only evidence they are referencing is a survey of 40 people, done when Jimmy Carter was president. It’s not evidence-based except by the weakest notions of “evidence.” It’s really a zombie statistic.
My obvious next question was whether a more trustworthy estimate existed for the medical care’s contribution to life extension in the US. In my search for a better estimate, I continued to go down the rabbit hole of links, arriving here, the AcademyHealth Blog, landing on the article called “Half of longevity gains due to health care.” It was a summary of the attempt by the authors of The Incidental Economist to answer this very question. And what did they find? First, they quoted a NEJM citation from 2006, where it was claimed that 90% of the increases in life expectancy since the 1960s was due to reduction in cardiovascular and neonatal deaths. After meandering through several other sources, the authors concluded that we can attribute about 50% of the responsibility for extending our life to medical interventions.
And that’s when I really confused myself. I started thinking about whether premature death and longevity are related, and how they may be related, and are we even talking about the same thing when we invoke each of them.
Premature mortality can be quantified in several ways — 1). percentage of all deaths that are considered premature, or 2). proportion of people in a population whose death is considered premature (that would be so many cases per 100,000 population). Longevity, on the other hand, is a measure of the average life span of a population. The current life expectancy in the US is 78.8 years. This begs the question of how these two, premature deaths and life expectancy, are numerically related to each other. And can the latter go up without the former going down?
Well, if the language here is consistent with how we speak it, “premature” implies that we know what “timely” means. The definition of a “timely” death must be based on the average life expectancy in a population. This number varies according to certain characteristics of a population, of course, so different subgroups would have a different life expectancy. For example, at any given age, the life expectancy of a person with heart disease should be lower than that for a person who is perfectly healthy. If we can reduce the risk of a premature death in people with heart disease, their life expectancy should edge closer to that of a healthy individual. And, in fact, according to the literature, this has happened in cardiovascular patients, partly due to better treatment of blood pressure, and partly due to fewer people smoking and other healthful lifestyle modifications.
So, it’s clear that when death due to a disease is postponed, longevity increases and, ergo, premature deaths drop. It’s a bit circular, I know. But here is one interesting detail to consider. Longevity or life expectancy (I use them interchangeably) is an age average. So here is one question: Does the impact on the magnitude of life expectancy gains vary with the age of the population in which premature deaths are avoided? I know, its a clunky question. What I mean is, would you expect life expectancy to go up more, less or same amount if we manage to reduce premature deaths in infancy versus old age? If you consider that life expectancy is an average, then infant mortality attenuates this average severely (think adding a whole bunch of numbers into the denominator without contributing anything to the numerator). So you can imagine, if infant mortality goes down a lot (a big reduction in premature deaths), overall population life expectancy spikes decisively. Reducing premature deaths among the elderly, clearly, by this same calculation, will not result in nearly the same increase in life expectancy.
Another way of looking at this is to consider that a much larger reduction in premature deaths among the elderly (think driveway pebbles) than among infants (those sizable bricks) would be needed in order to reach a similar degree of longevity improvement. A less intuitive corollary of this is that we indeed can have an increase in premature mortality in a group that contributes little to longevity (the elderly) and still witness a large bump in life expectancy with a much smaller reduction in premature deaths within a group with an outsized contribution to longevity (infants). So that answers the second question I posed about these measures — they can diverge.
Now, on to the estimated contribution of medical care to either or both of these. We have, in fact, witnessed a dramatic reduction in infant mortality. I found this report from Health Resources and Services Administration that infant mortality has dropped from 55.7 per 1,000 live births in 1935 to 6.8 per 1,000 live births in 2007. And here is what the authors cite as reasons:
…dramatic declines in infant mortality rates over the long term were due to large declines in mortality from pneumonia and influenza, birth defects, prematurity and low birthweight, respiratory distress syndrome (RDS), sudden infant death syndrome (SIDS), and injuries. Improvements in living conditions, advances in neonatal medicine and infant heath care, reductions in smoking during pregnancy, and increased access to and use of prenatal care have been suggested as factors responsible for decreases in infant mortality over the past several decades…
And here is an interesting detail: the pace of this drop was a dizzying 3.1% per year on average between 1935 and 2000. However, between 2000 and 2007, the rate went down only from 6.9 to 6.8 per 1,000 live births, a staggering deceleration in this steep decline. A further detail indicates that “much of the statistically significant decline [occurred] in the neonatal period.” The implication of this is that the latest declines are due to technology use, most likely among the very premature infants upon delivery. This is the very definition of access to medical care, and falls completely outside of the domain of public health.
Just one more random thought. Reductions in infant and cardiovascular mortality, each a product of both medical and public health interventions, are one side of the life expectancy equation. The other, darker, side is the fact that in some groups and locations in the US, the overall longevity is waning. Much of this phenomenon can be attributed to poverty, environmental factors and poor health behaviors, or, in sum, a reflection of our dismal investment in public health. And, sure, there is a component of access here too. And what about this calculus: Between 1990 and 2010, mortality from cardiovascular disease dropped by about 150,000 per year. That would be an awesome contribution to increased longevity and reduced premature deaths, if it weren’t offset by all the deaths (presumably premature) related to the healthcare system itself.
I know that none of this gets to the crux of the matter: What is a reliable estimate of what proportion of the increases in life expectancy can be attributed to access to medical care? But what it does make me appreciate is the complexity of each and every term, every definition, every estimate that we confront daily. This devil, as always, is in the details.
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