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The benefits of risk factor prevention in Americans aged 51 years and older

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Listed:
  • Goldman, D.P.
  • Zheng, Y.
  • Girosi, F.
  • Michaud, P.-C.
  • Olshansky, S.J.
  • Cutler, D.
  • Rowe, J.W.

Abstract

Objectives. We assessed the potential health and economic benefits of reducing common risk factors in older Americans. Methods. A dynamic simulation model tracked a national cohort of persons 51 and 52 years of age to project their health and medical spending in prevention scenarios for diabetes, hypertension, obesity, and smoking. Results. The gain in life span from successful treatment of a person aged 51 or 52 years for obesity would be 0.85 years; for hypertension, 2.05 years; and for diabetes, 3.17 years. A 51- or 52-year-old person who quit smoking would gain 3.44 years. Despite living longer, those successfully treated for obesity, hypertension, or diabetes would have lower lifetime medical spending, exclusive of prevention costs. Smoking cessation would lead to increased lifetime spending. We used traditional valuations for a life-year to calculate that successful treatments would be worth, per capita, $198018 (diabetes), $137964 (hypertension), $118946 (smoking), and $51750 (obesity). Conclusions. Effective prevention could substantially improve the health of older Americans, and-despite increases in longevity-such benefits could be achieved with little or no additional lifetime medical spending.

Suggested Citation

  • Goldman, D.P. & Zheng, Y. & Girosi, F. & Michaud, P.-C. & Olshansky, S.J. & Cutler, D. & Rowe, J.W., 2009. "The benefits of risk factor prevention in Americans aged 51 years and older," American Journal of Public Health, American Public Health Association, vol. 99(11), pages 2096-2101.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2009.172627_3
    DOI: 10.2105/AJPH.2009.172627
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    Cited by:

    1. Vincenzo Atella & Federico Belotti & Daejung Kim & Dana Goldman & Tadeja Gracner & Andrea Piano Mortari & Bryan Tysinger, 2021. "The future of the elderly population health status: Filling a knowledge gap," Health Economics, John Wiley & Sons, Ltd., vol. 30(S1), pages 11-29, November.
    2. Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018. "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 100-121.
    3. Daniel Bauer & Darius Lakdawalla & Julian Reif, 2018. "Mortality Risk, Insurance, and the Value of Life," NBER Working Papers 25055, National Bureau of Economic Research, Inc.
    4. Michaud, Pierre-Carl & Goldman, Dana P. & Lakdawalla, Darius N. & Zheng, Yuhui & Gailey, Adam H., 2012. "The value of medical and pharmaceutical interventions for reducing obesity," Journal of Health Economics, Elsevier, vol. 31(4), pages 630-643.
    5. Jinjing Li & Cathal O'Donoghue, 2013. "A survey of dynamic microsimulation models: uses, model structure and methodology," International Journal of Microsimulation, International Microsimulation Association, vol. 6(2), pages 3-55.
    6. Julia Thornton Snider & Jeffrey Sullivan & Emma van Eijndhoven & Michael K Hansen & Nobel Bellosillo & Cheryl Neslusan & Ellen O’Brien & Ralph Riley & Seth Seabury & Bertram L Kasiske, 2019. "Lifetime benefits of early detection and treatment of diabetic kidney disease," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-13, May.
    7. Datta Gupta, Nabanita & Kleinjans, Kristin J. & Larsen, Mona, 2011. "The Effect of an Acute Health Shock on Work Behavior: Evidence from Different Health Care Regimes," IZA Discussion Papers 5843, Institute of Labor Economics (IZA).
    8. Michaud, Pierre-Carl & Goldman, Dana & Lakdawalla, Darius & Gailey, Adam & Zheng, Yuhui, 2011. "Differences in health between Americans and Western Europeans: Effects on longevity and public finance," Social Science & Medicine, Elsevier, vol. 73(2), pages 254-263, July.

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