IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/13181.html
   My bibliography  Save this paper

Current and Future Prevalence of Obesity and Severe Obesity in the United States

Author

Listed:
  • Christopher J. Ruhm

Abstract

The prevalence of obesity has increased rapidly since the mid-1970s, following a period of relative stability. This study examines past patterns and projects future prevalence rates of obesity and severe obesity among US adults through 2020. Trends in body mass index (BMI), overweight (BMI 25), obesity (BMI 30), class 2 obesity (BMI 35), class 3 obesity (BMI 40) and class 4 obesity (BMI 45) of 20-74 year olds are obtained using data from the first National Health Examination Survey and the Nutrition Health and Nutrition Examination Surveys. Quantile regression methods are then used to forecast future prevalence rates through 2020. By that year, 77.6% of men are predicted to be overweight and 40.2% obese, with class 2, 3 and 4 obesity prevalence rates projected at 16.4%, 6.3% and 3.1%. The corresponding forecasts for women are 71.1%, 43.3%, 25.3%, 12.8% and 5.8%. The large growth predicted for severe obesity represents a major public health challenge, given the accompanying high medical expenditures and elevated risk of mortality and morbidity. Combating severe obesity is likely to require strategies targeting the particularly large weight gains of the heaviest individuals.

Suggested Citation

  • Christopher J. Ruhm, 2007. "Current and Future Prevalence of Obesity and Severe Obesity in the United States," NBER Working Papers 13181, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:13181
    Note: EH PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w13181.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Patricia M. Anderson & Kristin F. Butcher & Phillip B. Levine, 2003. "Economic perspectives on childhood obesity," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 27(Q III), pages 30-48.
    2. Henderson, R. Max, 2005. "The bigger the healthier: Are the limits of BMI risk changing over time?," Economics & Human Biology, Elsevier, vol. 3(3), pages 339-366, December.
    3. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    4. Burkhauser, Richard V. & Cawley, John, 2008. "Beyond BMI: The value of more accurate measures of fatness and obesity in social science research," Journal of Health Economics, Elsevier, vol. 27(2), pages 519-529, March.
    5. Manning, Willard G. & Blumberg, Linda & Moulton, Lawrence H., 1995. "The demand for alcohol: The differential response to price," Journal of Health Economics, Elsevier, vol. 14(2), pages 123-148, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pieroni, Luca & Salmasi, Luca, 2010. "Body weight and socio-economic determinants: quantile estimations from the British Household Panel Survey," ISER Working Paper Series 2010-41, Institute for Social and Economic Research.
    2. Dodd, Mark C., 2014. "Intertemporal discounting as a risk factor for high BMI: Evidence from Australia, 2008," Economics & Human Biology, Elsevier, vol. 12(C), pages 83-97.
    3. Brunello, Giorgio & Fabbri, Daniele & Fort, Margherita, 2009. "Years of Schooling, Human Capital and the Body Mass Index of European Females," IZA Discussion Papers 4667, Institute of Labor Economics (IZA).
    4. RAMDANI, Dendi & VAN WITTELOOSTUIJN, Arjen, 2009. "Board independence, CEO duality and firm performance: A quantile regression analysis for Indonesia, Malaysia, South Korea and Thailand," ACED Working Papers 2009003, University of Antwerp, Faculty of Business and Economics.
    5. Xiao, Yue & Wen, Haizhen & Hui, Eddie C.M. & Zhou, Ganghua, 2022. "Dynamic capitalization effects of educational facilities during different market stages: An empirical study in Hangzhou, China," Land Use Policy, Elsevier, vol. 122(C).
    6. Stephen Mak & Lennon Choy & Winky Ho, 2010. "Quantile Regression Estimates of Hong Kong Real Estate Prices," Urban Studies, Urban Studies Journal Limited, vol. 47(11), pages 2461-2472, October.
    7. Classen, Timothy J., 2010. "Measures of the intergenerational transmission of body mass index between mothers and their children in the United States, 1981-2004," Economics & Human Biology, Elsevier, vol. 8(1), pages 30-43, March.
    8. Jacinta C. Nwachukwu, 2017. "Tenure and Spending Within UK Households at the End of the Recent Recession," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 1075-1104, September.
    9. Stifel, David C. & Averett, Susan L., 2009. "Childhood overweight in the United States: A quantile regression approach," Economics & Human Biology, Elsevier, vol. 7(3), pages 387-397, December.
    10. Robert Pryce & Bruce Hollingsworth & Ian Walker, 2019. "Alcohol quantity and quality price elasticities: quantile regression estimates," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 439-454, April.
    11. Andrew M. Jones & Ángel López-Nicolás, 2002. "The importance of individual heterogeneity in the decomposition of measures of socioeconomic inequality in health: An approach based on quantile regression," Working Papers, Research Center on Health and Economics 626, Department of Economics and Business, Universitat Pompeu Fabra.
    12. Odelia Rosin, 2008. "The Economic Causes Of Obesity: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 617-647, September.
    13. RAMDANI, Dendi & VAN WITTELOOSTUIJN, Arjen, 2009. "Board independence, CEO duality and firm performance: A quantile regression analysis for Indonesia, Malaysia, South Korea and Thailand," Working Papers 2009004, University of Antwerp, Faculty of Business and Economics.
    14. Bijan J. Borah & Anirban Basu, 2013. "Highlighting Differences Between Conditional And Unconditional Quantile Regression Approaches Through An Application To Assess Medication Adherence," Health Economics, John Wiley & Sons, Ltd., vol. 22(9), pages 1052-1070, September.
    15. Maclean, Johanna Catherine & Xu, Haiyong & French, Michael T. & Ettner, Susan L., 2014. "Personality disorders and body weight," Economics & Human Biology, Elsevier, vol. 12(C), pages 153-171.
    16. Vinish Shrestha, 2018. "Do young adults substitute cigarettes for alcohol? Learning from the master settlement agreement," Review of Economics of the Household, Springer, vol. 16(2), pages 297-321, June.
    17. Alan C. Monheit & Jessica P. Vistnes & Jeannette A. Rogowski, 2007. "Overweight in Adolescents: Implications for Health Expenditures," NBER Working Papers 13488, National Bureau of Economic Research, Inc.
    18. Fang, Hai & Ali, Mir M. & Rizzo, John A., 2009. "Does smoking affect body weight and obesity in China?," Economics & Human Biology, Elsevier, vol. 7(3), pages 334-350, December.
    19. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    20. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.

    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:13181. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.