The Benefits of Risk Factor Prevention in Americans Aged 51 Years and Older

Dana P. Goldman, PhD; Yuhui Zheng, PhD; Federico Girosi, PhD; Pierre-Carl Michaud, PhD; S. Jay Olshansky, PhD; David Cutler, PhD; John W. Rowe, MD


Am J Public Health. 2009;99(11):2096 

In This Article


Research suggests that anticipated treatments for cardiovascular disease, neurologic disorders, and cancer[16] could make us live longer but could carry a substantial price tag.[4] Our data indicate that primary prevention could improve the health and longevity of future cohorts of elderly persons in the United States at a relatively low cost.

These improvements in health and quality of life would be even larger if the interventions we evaluated were adopted at earlier ages (before 51 years), a scenario we were unable to model because of data limitations. Although the complete elimination of the risk factors we studied is not realistically achievable, our results suggest that even partial success would extend life expectancy as much as would be gained by elimination of major fatal diseases such as cancer and ischemic heart disease.

We focused only on the benefits to society from intervention and did not consider the costs of implementing our 10%, 25%, 50%, and 100% scenarios. Rather, we proposed a threshold for how costly and efficacious a prevention intervention should be to justify its implementation. Still, universal cures would generate large economic gains, ranging from $33287 per person (smoking) to $117015 (hypertension) for each person aged 51 or 52 years, according to a conservative valuation of $100000 per QALY. Prevention costs would reduce these gains, but the interventions are likely to be worthwhile if costs are not prohibitive. Another interpretation is that if lifetime prevention costs were less than $117015 per person, society would benefit from intervening to prevent hypertension in a person aged 51 or 52 years. Diabetes prevention, in particular, would be a highly valuable intervention for both patients and society.

How feasible are these prevention scenarios? Some may be attainable with existing prevention methods. A recent meta-analysis found that several efficacious treatments can prevent or delay the onset of type 2 diabetes.[17] The pooled hazard ratios were 0.51 for lifestyle interventions (diet, exercise, or both) versus standard advice; 0.70 for oral diabetes drugs versus control; and 0.44 for Orlistat versus control. For hypertension, the Trials of Hypertension Prevention found that a 3-year program of group meetings and individual counseling focused on dietary change, physical activity, and social support reduced the incidence of hypertension among middle-aged participants. The risk ratio for developing hypertension after 6 months was 0.58 relative to usual care.[18] For smoking reduction, the latest guideline by the US Department of Health and Human Services affirms that pharmacotherapy, physician advice, and psychosocial treatments (self-help, individual counseling, group counseling, and telephone counseling) have all been shown to be effective in treating tobacco use in adults aged 50 years and older; the combination of counseling and medication was found to be most effective.[19]

For obesity, however, existing interventions are not as promising. Clinical trials of low-calorie diets (1000–1200 kilocalories/day) resulted in an 8% weight loss over 3 to 12 months.[20] Increases in physical activity, primarily aerobic exercise, lowered weight by approximately 3%, and combinations of caloric reduction and increased physical activity were more effective than either intervention alone.[20] Data from the HRS show that among individuals aged 50 years and older in 2004, a 5% weight loss among obese individuals would reduce the prevalence of obesity by 27%.[9]


Because of the complexity of our model, we assumed that health conditions followed a Markovian process. That is, the last period's risk factors and health conditions were sufficient to determine future health, mortality, and functional outcomes. Although the model fit well in our sample for simulations during 1992 to 2004, it is unclear whether this would be sustained over a different and longer period. Furthermore, we were limited to 2-year incidence rates and summary measures of each condition (diagnosis). These might have limited our ability to accurately describe disease dynamics. Further research on the duration dependence of diseases, and how they affect our findings, is surely warranted but beyond the scope of this article.

Although the microsimulation was designed to control for competing risks, the model did not adjust for differential spending near the end of life. Each individual in our model was tracked until death, and we observed increases in the prevalence of other diseases when we controlled for cardiovascular risk factors. Thus, a person was allowed to develop diseases and disabilities that might be more or less expensive than the conditions for which we were intervening and to live longer with them. For example, reducing hypertension in our model led to an increase in the prevalence of cancer in our model and the costs associated with it. However, because data on the cause of death were not available—and distinguishing which disease is driving spending at the end of life is difficult even with such data—we modeled end-of-life spending with a binary indicator for the year of death.

Reductions in other cardiovascular risk factors, including cholesterol, blood pressure, and physical activity, have been shown to have contributed to recent declines in cardiovascular mortality.[21] Because of data limitations (the HRS does not collect biometric data and the physical activity questions have changed over time), we were unable to include them. Behavioral change has economic costs usually not accounted for in public health discussions. Restrictions on diet and smoking and compliance with prevention regimens would result in some loss of utility, and we did not account for these. D.C. estimated the cost of behavior change to be half the value of prevention (data not shown).


Our findings indicate that primary prevention could generate significant health and longevity benefits among existing cohorts, perhaps at considerably lower cost than for the disease-specific interventions now being pursued. Greater attention should be paid to the development and implementation of more effective prevention strategies as a way to immediately address demographic shifts that are about to transform the landscape of human health and longevity.


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