Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The economic value of reducing avoidable mortality

Nature Medicine (2024)Cite this article

Subjects

Abstract

Living longer and healthier boosts individual and family welfare. As part of the World Bank’s Healthy Longevity Initiative, we quantified the economic value of achieving the highest possible life span. We estimated the economic value of reducing avoidable mortality, defined as the difference between observed (or projected) mortality and lowest achieved (or projected) mortality, by world regions, sex, and age, between 2000 and 2021, with projection to 2050. In 2019, 69% of mortality, or 40 million deaths, was avoidable. The economic value of avoidable mortality globally was 23% of annual income, meaning that, globally, populations would be willing to give up about one-fifth of their current income in exchange for a year living at the lowest achieved mortality rate. This value ranges from 19% in China to 34% in sub-Saharan Africa. Under the rapid-progress scenario, in which countries experience fast but plausible mortality reductions from 2019 to 2050, we would expect globally the gap between projected and frontier life expectancy to be halved by 2050, and the economic value after achieving this scenario is equivalent to 14% of annual income. Our work provides supportive evidence on the high economic value placed on improving health.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Avoidable mortality globally and by region, year and age group.
Fig. 2: Differences between observed/projected life expectancy, life expectancy under the rapid progress scenario, and the frontier life expectancy, by region.
Fig. 3: Economic value of avoidable mortality by year and region.
Fig. 4: Sensitivity analysis.

Similar content being viewed by others

Data availability

This study uses publicly available data, including World Population Prospects 2022 (https://population.un.org/wpp/Download/Standard/CSV), the Human Mortality Database (https://www.mortality.org/), World Bank GNI per capita (PPP constant 2017 international dollars) (https://data.worldbank.org/indicator/NY.GNP.PCAP.PP.KD), and the OECD’s projected country-specific growth rates (https://www.oecd.org/economic-outlook.html).

Code availability

Replication code is available on GitHub: https://github.com/achangdias/HLI_evam

References

  1. Jha, P., Al-Tuwaijri, S. & Veillard, J. Unlocking the Power of Healthy Longevity: Demographic Change, Noncommunicable Diseases, and Human Capital (World Bank, 2024).

  2. OECD. Avoidable Mortality: OECD/Eurostat Lists Of Preventable And Treatable Causes Of Death (Organization for Economic Co-operation and Development, 2019).

  3. Alkire, B. C., Peters, A. W., Shrime, M. G. & Meara, J. G. The economic consequences of mortality amenable to high-quality health care in low- and middle-income countries. Health Aff. 37, 988–996 (2018).

    Article  Google Scholar 

  4. Kruk, M. E. et al. High-quality health systems in the Sustainable Development Goals era: time for a revolution. Lancet Glob. Health 6, e1196–e1252 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  5. WHO. HEARTS: Technical Package for Cardiovascular Disease Management in Primary Health Care: Risk-based CVD Management (World Health Organization, 2020).

  6. WHO. Tackling NCDs Best Buys and Recommended Interventions for the Prevention and Control Of NCDs Report No. WHO/NMH/NVI/17.9 (World Health Organization, 2017).

  7. Stenberg, K. et al. Guide posts for investment in primary health care and projected resource needs in 67 low-income and middle-income countries: a modelling study. Lancet Glob. Health 7, e1500–e1510 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Jamison, D. T. et al. Universal health coverage and intersectoral action for health: key messages from Disease Control Priorities. Lancet 391, 1108–1120 (2018).

    Article  PubMed  Google Scholar 

  9. Watkins, D. A. et al. Resource requirements for essential universal health coverage: a modelling study based on findings from Disease Control Priorities. Lancet Glob. Health 8, e829–e839 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  10. United Nations Department of Economic and Social Affairs, Population Division. World Population Prospects 2022. https://population.un.org/wpp/Download/Standard/CSV/ (accessed 4 October 2023).

  11. Cardoso, D. S. & Dahis, R. Calculating the economic value of non-marginal mortality risk reductions. Econ. Lett. 237, 111673 (2024).

    Article  Google Scholar 

  12. Rutstein, D. D. et al. Measuring the quality of medical care. A clinical method. N. Engl. J. Med. 294, 582–588 (1976).

    Article  PubMed  CAS  Google Scholar 

  13. Nolte, E. & McKee, M. Measuring the health of nations: analysis of mortality amenable to health care. J. Epidemiol. Community Health 58, 326–326 (2004).

    PubMed Central  Google Scholar 

  14. World Health Organization. Global Health Estimates 2020. https://www.who.int/data/global-health-estimates (accessed 29 July 2021).

  15. Mathers, C. D., Stevens, G. A., Boerma, T., White, R. A. & Tobias, M. I. Causes of international increases in older age life expectancy. Lancet 385, 540–548 (2015).

    Article  PubMed  Google Scholar 

  16. Robinson, L. A., Hammitt, J. K., Jamison, D. T. & Walker, D. G. Conducting benefit–cost analysis in low- and middle-income countries: introduction to the special issue. J. Benefit Cost Anal. 10, 1–14 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Robinson, L. A. et al. Reference case guidelines for benefit–cost analysis in global health and development. https://www.hsph.harvard.edu/wp-content/uploads/sites/2447/2019/05/BCA-Guidelines-May-2019.pdf (2019).

  18. Hammitt, J. K. Valuing mortality risk in the time of COVID-19. J. Risk Uncertain. 61, 129–154 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Herrera-Araujo, D., Rheinberger, C. M. & Hammitt, J. K. Valuing non-marginal changes in mortality and morbidity risk. J. Health Econ. 84, 102627 (2022).

    Article  PubMed  Google Scholar 

  20. World Bank. Current Health Expenditure (% of GDP) (World Bank Group, accessed 7 July 2022); https://data.worldbank.org/indicator/SH.XPD.CHEX.GD.ZS

  21. Stenberg, K. et al. Financing transformative health systems towards achievement of the health Sustainable Development Goals: a model for projected resource needs in 67 low-income and middle-income countries. Lancet Glob. Health 5, e875–e887 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Verguet, S., Bolongaita, S., Chang, A. Y., Cardoso, D. S. & Stevens, G. A. The economic value of reducing mortality due to noncommunicable diseases and injuries. Nat. Med. https://doi.org/10.1038/s41591-024-03248-4 (2024).

  23. Watkins, D., Ahmed, S. & Pickersgill, S. Best investments in chronic, noncommunicable disease prevention and control in low- and lower–middle-income countries. J. Benefit Cost. Anal. 14, 255–271 (2023).

    Article  Google Scholar 

  24. Watkins, D. A. et al. NCD Countdown 2030: efficient pathways and strategic investments to accelerate progress towards the Sustainable Development Goal target 3.4 in low-income and middle-income countries. Lancet 399, 1266–1278 (2022).

    Article  Google Scholar 

  25. WHO. CureAll Framework: WHO Global Initiative for Childhood Cancer (World Health Organization, 2021).

  26. WHO. Global Strategy to Accelerate the Elimination of Cervical Cancer as A Public Health Problem (World Health Organization, 2020).

  27. WHO Global Malaria Team. Global Technical Strategy for Malaria 2016–2030, 2021 Update (World Health Organization, 2021).

  28. OECD. Health at a Glance 2021: OECD Indicators (Organization for Economic Co-operation and Development, 2021).

  29. GBD 2019 Diseases and Injuries Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1223–1249 (2020).

  30. Viscusi, W. K. & Aldy, J. E. The value of a statistical life: a critical review of market estimates throughout the world. J. Risk Uncertain. 27, 5–76 (2003).

    Article  Google Scholar 

  31. Keller, E., Newman, J. E., Ortmann, A., Jorm, L. R. & Chambers, G. M. How much is a human life worth? A systematic review. Value Health 24, 1531–1541 (2021).

    Article  PubMed  Google Scholar 

  32. Patenaude, B. N., Semali, I., Killewo, J. & Bärnighausen, T. The value of a statistical life-year in sub-Saharan Africa: evidence from a large population-based survey in Tanzania. Value Health Reg. Issues 19, 151–156 (2019).

    Article  PubMed  Google Scholar 

  33. Trautmann, S. T. et al. Value of statistical life year in extreme poverty: a randomized experiment of measurement methods in rural Burkina Faso. Popul. Health Metr. 19, 45 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Barbieri, M. et al. Data resource profile: the human mortality database (HMD). Int J. Epidemiol. 44, 1549–1556 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Wilmoth, J. R., Andreev, K., Jdanov, D., Glei, D. A. & Riffe, T. Methods Protocol for The Human Mortality Database https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf (2021).

  36. Human Mortality Database (accessed 23 March 2023);https://www.mortality.org

  37. Oeppen, J. & Vaupel, J. W. Broken limits to life expectancy. Science 296, 1029–1031 (2002).

    Article  PubMed  CAS  Google Scholar 

  38. Vaupel, J. W., Villavicencio, F. & Bergeron-Boucher, M. P. Demographic perspectives on the rise of longevity. Proc. Natl Acad. Sci. USA 118, e2019536118 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Luy, M. in Gender-Specific Life Expectancy in Europe 1850–2010 Vol. 58 (eds. Dinges, M. & Weigl, A.) 17–46 (Franz Steiner Verlag, 2016).

  40. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1223–1249 (2020).

    Article  Google Scholar 

  41. Bressler, R. D. & Heal, G. Valuing Excess Deaths Caused by Climate Change. National Bureau of Economic Research. Working Paper 30648 (National Bureau of Economic Research, 2022).

  42. OECD. OECD Economic Outlook, Volume 2023 Issue 1: A long unwinding road (OECD Publishing, 2023).

Download references

Acknowledgements

A.Y.C., G.A.S., D.S.C., and D.T.J. received funding from The World Bank’s Healthy Longevity Initiative. We thank P. Jha, G. Alleyne, P. Isenman, S. Verguet, S. Bolongaita, and the members of the HLI team who participated in workshops in Mexico City (May 2022) and Washington DC (October 2022) for their feedback. We dedicate this paper to J. W. Vaupel (1945–2022), who inspired us and many others with his intellect, vision, and passion for great research.

Author information

Author notes

  1. These authors contributed equally: Angela Y. Chang, Gretchen A. Stevens.

Authors and Affiliations

  1. Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark

    Angela Y. Chang

  2. Danish Centre for Health Economics, University of Southern Denmark, Odense, Denmark

    Angela Y. Chang

  3. The Interdisciplinary Centre on Population Dynamics (CPop), University of Southern Denmark, Odense, Denmark

    Angela Y. Chang

  4. Independent researcher, Los Angeles, CA, USA

    Gretchen A. Stevens

  5. Department of Agricultural and Consumer Economics, University of Illinois Urbana-Champaign, Champaign, IL, USA

    Diego S. Cardoso

  6. World Health Organization, Geneva, Switzerland

    Bochen Cao

  7. Department of Epidemiology and Biostatistics and Institute for Global Health Sciences, University of California, San Francisco, CA, USA

    Dean T. Jamison

Authors
  1. Angela Y. Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gretchen A. Stevens
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Diego S. Cardoso
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bochen Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dean T. Jamison
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: A.Y.C., G.A.S., D.T.J. Methodology development: A.Y.C., G.A.S., D.S.C., B.C., D.T.J. Analysis: A.Y.C., G.A.S., D.S.C. Original draft preparation: A.Y.C., G.A.S., D.S.C. Reviewing and editing: A.Y.C., G.A.S., D.S.C., B.C., D.T.J.

Corresponding author

Correspondence to Angela Y. Chang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Medicine thanks Philip Clarke, Owen O’Donnell and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor Ming Yang, in collaboration with the Nature Medicine team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Frontier life expectancy, by method.

Alternative projections of the frontier are shown: linear projection of life expectancy (red) and linear projection of the natural log of age-specific frontier mortality (blue, the baseline method used in this study). Estimated/projected life expectancy from WPP2022 for Japanese females is shown for comparison.

Extended Data Fig. 2 Distribution of avoidable mortality, year 2019.

Proportion of deaths that are avoidable.

Extended Data Fig. 3 Age-group contributions to the total value of avoidable mortality and population composition by age in year 2019.

The first bar is the age-group contribution to economic value of avoidable mortality; the second bar is the population composition.

Extended Data Fig. 4 Annual rate of change of country-level mortality rates by age between 2000–2019.

The red line is the mean annual rate of change (AARC) of all countries, the yellow line is the 20th percentile AARC and the blue line is the 10th percentile AARC.

Extended Data Fig. 5 Sensitivity analysis: Avoidable mortality as a percentage of all deaths, 2019.

(A) baseline methods, (B) sex-specific frontier.

Extended Data Fig. 6 One-way sensitivity analyses.

VSL decay methods, discount rate, income elasticity and base VSL.

Extended Data Table 1 Frontier countries and mortality rates (deaths per 10,000 per year) in each period and age group
Full size table
Extended Data Table 2 Total mortality and percentage of mortality that is avoidable in 2019, globally and by region, for all ages and by age
Full size table
Extended Data Table 3 Total mortality and percentage of mortality that is avoidable in 2019, globally and by region, for all ages and by age
Full size table
Extended Data Table 4 Number of deaths in 2050 for the baseline and rapid progress scenarios. In millions (% difference from the WPP2022 projections (column 1) in parenthesis)
Full size table

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chang, A.Y., Stevens, G.A., Cardoso, D.S. et al. The economic value of reducing avoidable mortality. Nat Med (2024). https://doi.org/10.1038/s41591-024-03253-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41591-024-03253-7

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing