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P E R S P E C T I V E
F U T U R E  E L D E R L Y 

26 September 2005  
  

Projecting The Future Of 
U.S. Health And Longevity

Two papers address the nation’s future health
in different ways; both add substance to the debate.

By S. Jay Olshansky

ABSTRACT:

Is the health of the U.S. population improving or getting worse, and how are health and medical costs influenced by obesity? How will anticipated advances in the biomedical sciences influence life expectancy and the cost of health care? The paper by Dana Goldman and colleagues is a daring speculation on the life-extending effects of possible future technologies—a valuable exercise given the speed of technological advances. Darius Lakdawalla and colleagues provide a methodologically solid basis for concluding that not only does obesity kill, it also takes an alarming toll on health and health care spending at levels that require immediate intervention.

What will the future of U.S. health and longevity be? This is a question that scientists, pundits, and authors of science fiction novels have written about for centuries. Given the inevitable demographic wave of population aging now approaching the shoreline, estimating its magnitude and impact on the size of the beneficiary population and health care costs is of critical public policy importance. Papers in this Health Affairs online collection are focused squarely on this topic; here I discuss those by Dana Goldman and colleagues and by Darius Lakdawalla and colleagues.

Goldman and colleagues. The paper by Goldman and colleagues is an economist’s view of how to model the future hazards of death and the financial costs of efforts to keep people alive using hypothetical technologies not yet in existence.¹ Think about this for a moment: This is not an easy exercise. First one has to come up with a list of technologies that do not yet exist but that might, and then one must estimate the impact these nonexistent technologies could have on the health and risk of death of today’s younger generation when they are old enough to use them. To make such estimates, one has to pile one assumption upon another until what looks like a house of cards has been constructed. Is the result worth the risk of constructing such fragile models? In this case, I would have to say that it is.

It is important to remember that this paper was not written as a projection model intended as a serious attempt to predict the future, but rather as a way to estimate the effect of hypothetical life-extending technologies on death rates and health care costs. If this were a genuine attempt to forecast the future, then the model and assumptions would have had to be extended to include other forces that could simultaneously increase the risk of death, such as the reemergence of infectious diseases and the serious obesity epidemic now plaguing younger generations.

The value of the model developed by Goldman and colleagues is that it provides readers with conceptual boundaries within which hypothetical life-extending technologies might influence the extension of life and health care costs. The microsimulation model used is based on data about Medicare beneficiaries from a 1992–1999 survey, hypothetically aging this cohort forward using observed single-year death probabilities from the same survey and then eliciting “consensus from several panels of distinguished experts” on what new technologies might be forthcoming and how they might influence death rates. The question I find myself asking is this: How believable are the results?

The ability of forecasting models to accurately predict the future is evaluated not on how well they predict the future, because for obvious reasons this cannot be known until the projection time frame has expired, but on how well they predict the present from the past. The forecasting models developed by these authors were never evaluated in this way, so it is not possible to assess their past performance. Furthermore, the hypothesized effects of nonexistent technologies on future death rates simply appear as if by magic. For example, the authors assume that a “mythical compound” (this is the phrase the authors use to describe this intervention) that extends life by mimicking the life-extending effect of caloric restriction on other animals will be developed for humans; it is assumed that the percentage increase in life expectancy from caloric restriction will be the same for humans as it is now observed for some other species (25 percent); only people age sixty-five and older will take this compound, at a cost of a dollar per day for thirty years; and it is projected to increase life expectancy at birth by ten years. All of the gain must come from reductions in death rates among those age sixty-five and older.

Where do these assumptions come from? The vast literature on caloric restriction is never referenced, so the casual reader will not know that serious obstacles remain in developing and applying such findings to humans; contrary to the authors’ assumptions, there is reason to suspect that the life-extending effect observed in other mammals would not have the same life-extending effect on humans.² Why would people only age sixty-five and older take the mythical compound? Where did the cost estimate of a dollar a day come from (this seems rather low for any life-extending technology)? And how did the authors come up with an estimated ten-year increase in life expectancy at birth? The lack of answers to these questions should make any reader skeptical. Similar questions may be raised about all of the other hypothetical life-extending technologies modeled in this paper.

If questions about the methodology and assumptions are not enough, the main issue, as I see it, is the model’s underlying premise that the best way to peer into the future is to observe and extrapolate from the past—a methodology that has been popular among mathematical demographers for forecasting life expectancy.³ This may be a useful approach for forecasting the weather or cyclical trends in the stock market, but when it comes to human health and longevity, it makes more sense to try first to understand the biology of aging and death, the limiting structure of human body design, and the presence of younger generations that are already facing the prospect of much higher adult mortality than previous generations have had to face.⁴

Lakdawalla and colleagues. The paper by Lakdawalla and colleagues addresses one of the hottest issues now being debated in the public health arena: the health effects of obesity.⁵ Scientists have been debating what methods and assumptions to use when calculating the number of annual deaths attributable to obesity; the result has been a range from 112,000 to 300,000.⁶ Such variation is the product of relatively minor differences in assumptions rather than differences in methodology, although in one instance, a clerical error led to an overestimate of deaths due to obesity.⁷ However, the public health message is the same, regardless of which estimate is eventually found to be closer to the truth: Obesity is harmful. As is always the case with such public health conclusions, the usual caveat applies that the harmful effects are not equally distributed in the population.

What Ladkawalla and colleagues have done is put their finger right on the most important issue to come out of this literature. The bottom-line message in all of the research on the health effects of obesity is consistent: Not only does obesity increase the risk of death for most people at most ages, it consistently leads to a much higher level of disability and disease at all ages. Researchers can fight internally within scientific journals about the methodological nuances that lead to varying estimates of obesity-induced deaths. However, the fact remains that all of these numbers are too high; most of these deaths can be delayed by encouraging people to adopt healthier lifestyles based on reduced caloric intake and increased exercise; and the important, definitive take-away message is that obesity accelerates disease, increases disability, and greatly increases the cost of medical care.

An article recently published by Edward Gregg and colleagues demonstrated that the risk of cardiovascular disease (CVD) associated with obesity at all levels of body mass index (BMI) has declined in recent years.⁸ Medicine has become more efficient at extending the lives of the obese by treating some of its complications more effectively, but such “improvements” are occurring during a time when the prevalence and severity of obesity, especially among children, continue to worsen. According to Gregg and colleagues, “The net result of these phenomena may be a population that is, paradoxically, more obese, diabetic, arthritic, disabled, and medicated, but with lower overall CVD risk.”⁹ These findings are now echoed and confirmed by Lakdawalla and colleagues: Carrying extra weight at BMI levels of 30 or more might not always kill (although it does so often enough to warrant intervention), but it consistently leads to a much higher risk of lethal and disabling health problems. Most important of all, it has now been confirmed that obesity dramatically increases the number of years lived with disability.

Readers should be aware of the fact that the findings from Lakdawalla and colleagues, and those of Gregg and colleagues, are based on the prevalence of obesity and its health effects observed during about the past fifteen years in the United States. The people sampled in these surveys were born at the beginning and middle of the twentieth century and exhibited their obesity-induced morbidity and mortality in the latter part of that century. Future generations will be far different from those upon whom such estimates are made, and studies of this kind cannot account for this difference. The prevalence of obesity among today’s younger generation is much higher than that of previous generations, and young people today carry much more weight at an earlier age than any preceding generation has done.¹⁰ We have already witnessed the rise of Type II diabetes among children in many developed countries today—a severe health problem never seen before 1980.¹¹ My colleagues and I have estimated that in the absence of interventions that attenuate the obesity epidemic among children, the negative effect of obesity on the life expectancy of the U.S. population could rise from current levels of under one year to more than five years within the next half-century.¹² This says nothing of the negative effect of today’s childhood obesity epidemic on the prevalence of disability among cohorts of middle-aged and older people in the coming decades—which would be expected to rise well beyond the estimates provided by Lakdawalla and colleagues.

Concluding comments. Both papers are valuable contributions to the literature for different reasons. The paper by Goldman and colleagues is useful at one level because the authors dare to speculate on the life-extending effects of possible future technologies. This kind of speculation needs to be done to help inform the debate about the future of human life expectancy, and it is clear that the authors have given considerable thought to the topic. Although I have problems with many of their assumptions, the results at least provide a useful frame of reference.

The paper by Lakdawalla and colleagues focuses our attention on the most important issue in the obesity debate: the observed health and well-being of the population as measured by trends in health expectancy. Shifting the focus from death to health is the crystallizing message here, and the authors provide a methodologically solid basis for concluding that not only does obesity kill, it already takes an alarming toll on health and health care spending in this country at levels that require immediate intervention.

NOTES

1. D.P. Goldman et al., “Consequences of Health Trends and Medical Innovation for the Future Elderly,” Health Affairs, 26 September 2005, content.healthaffairs.org/cgi/content/abstract/hlthaff.w5.r5.
2. L. Demetrius, “Caloric Restriction, Metabolic Rate, and Entropy,” Journals of Gerontology, Series A: Biological Sciences and Medical Sciences 59, no. 9 (2004): B902–B915.
3. J. Oeppen and J. Vaupel, “Demography: Broken Limits to Life Expectancy,” Science 296, no. 5570 (2002): 1029–1031.
4. See B.A. Carnes, S.J. Olshansky, and D. Grahn, “Biological Evidence for Limits to the Duration of Life,” Biogerontology 4, no. 1 (2003): 31–45; S.J. Olshansky, B.A. Carnes, and R. Butler, “If Humans Were Built to Last,” Scientific American (May 2003): 94–100; J.P. Koplan, C.T. Liverman, and V.I. Kraak, eds., Preventing Childhood Obesity: Health in the Balance (Washington: National Academies Press, 2004); and C.B. Ebbeling, D.B. Pawlak, and D.S. Ludwig, “Childhood Obesity: Public-Health Crisis, Common Sense Cure,” Lancet 360, no. 9331 (2002): 473–482.
5. D.N. Lakdawalla, D.P. Goldman, and B. Shang, “The Health and Cost Consequences of Obesity among the Future Elderly,” Health Affairs, 26 September 2006, content.healthaffairs.org/cgi/content/abstract/hlthaff.w5.r30.
6. K.M. Flegal et al., “Excess Deaths Associated with Underweight, Overweight, and Obesity,” Journal of the American Medical Association 293, no. 15 (2005): 1861–1867; and D.B. Allison et al., “Annual Deaths Attributable to Obesity in the United States,” Journal of the American Medical Association 282, no. 16 (1999): 1530–1538.
7. A.H. Mokdad et al., “Actual Causes of Death in the United States, 2000,” Journal of the American Medical Association 291, no. 10 (2004): 1238–1245.
8. E.W. Gregg et al., “Secular Trends in Cardiovascular Disease Risk Factors According to Body Mass Index in U.S. Adults,” Journal of the American Medical Association 293, no. 15 (2005): 1868–1874.
9. Ibid., 1873.
10. C.L. Ogden et al., “Prevalence and Trends in Overweight among U.S. Children and Adolescents, 1999–2000,” Journal of the American Medical Association 288, no. 14 (2002): 1728–1732.
11. D.S. Ludwig and C.B. Ebbeling, “Type 2 Diabetes Mellitus in Children: Primary Cary and Public Health Considerations,” Journal of the American Medical Association 286, no. 12 (2001): 1427–1430.
12. S.J. Olshansky et al., “A Potential Decline in Life Expectancy in the United States in the Twenty-first Century,” New England Journal of Medicine 352, no. 11 (2005): 1138–1145.

S. Jay Olshansky (sjayo{at}uic.edu) is a professor at the School of Public Health, University of Illinois at Chicago, and a research associate at the Center on Aging, University of Chicago, and the London School of Hygiene and Tropical Medicine.

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DOI: 10.1377/hlthaff.W5.R86
©2005 Project HOPE–The People-to-People Health Foundation, Inc.