[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/16252.html
   My bibliography  Save this paper

The Trend of BMI Values of US Adults by Centiles, birth cohorts 1882-1986

Author

Listed:
  • John Komlos
  • Marek Brabec
Abstract
Trends in BMI values are estimated by centiles of the US adult population by birth cohorts 1886-1986 stratified by ethnicity. The highest centile increased by some 18 to 22 units in the course of the century while the lowest ones increased by merely 1 to 3 units. Hence, the BMI distribution became increasingly right skewed as the distance between the centiles became increasingly larger. The rate of change of BMI centile curves varied considerably over time. The BMI of white men and women experienced upsurges after the two World Wars and downswings during the Great Depression and again after 1970. However, among blacks the pattern is different during the first half of the century with men's rate of increase in BMI values decreasing substantially and that of females remaining unchanged at a relatively high level until the Second World War. However, after the war the rate of change of BMI values of blacks resembled that of the whites with an accelerating phase followed by a slow down around the 1970s. In sum, the creeping nature of the obesity epidemic is evident, as the technological and lifestyle changes of the 20th century affected various segments of the population quite differently.

Suggested Citation

  • John Komlos & Marek Brabec, 2010. "The Trend of BMI Values of US Adults by Centiles, birth cohorts 1882-1986," NBER Working Papers 16252, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:16252
    Note: DAE EH
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w16252.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
    2. John Komlos & Marek Brabec, 2010. "The Trend of Mean BMI Values of US Adults, Birth Cohorts 1882-1986 Indicates that the Obesity Epidemic Began Earlier than Hitherto Thought," NBER Working Papers 15862, National Bureau of Economic Research, Inc.
    3. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    4. T. J. Cole, 1988. "Fitting Smoothed Centile Curves to Reference Data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(3), pages 385-406, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Elsayyad, May & Konrad, Kai A., 2012. "Fighting multiple tax havens," Journal of International Economics, Elsevier, vol. 86(2), pages 295-305.
    2. John Komlos & Marek Brabec, 2010. "The Trend of BMI Values by Centiles of US Adults, Birth Cohorts 1882-1986," CESifo Working Paper Series 3132, CESifo.
    3. Scott A. Carson, 2021. "Nineteenth Century Body Mass, Height, and Weight: Inequality across Quantiles," CESifo Working Paper Series 9135, CESifo.
    4. Trüb, Fabienne P & Wells, Jonathan CK & Rühli, Frank J & Staub, Kaspar & Floris, Joël, 2020. "Filling the weight gap: Estimating body weight and BMI using height, chest and upper arm circumference of Swiss conscripts in the first half of the 20th century," Economics & Human Biology, Elsevier, vol. 38(C).
    5. Jolliffe, Dean, 2011. "Overweight and poor? On the relationship between income and the body mass index," Economics & Human Biology, Elsevier, vol. 9(4), pages 342-355.
    6. Mary A. Burke & Frank Heiland, 2011. "Explaining gender-specific racial differences in obesity using biased self-reports of food intake," Working Papers 11-2, Federal Reserve Bank of Boston.
    7. Liczbińska, Grażyna & Czapla, Zbigniew & Nowak, Oskar & Piontek, Janusz, 2016. "Body mass index values of conscripts in the Polish lands under Prussian rule in the late 19th and early 20th centuries," Economics & Human Biology, Elsevier, vol. 21(C), pages 75-83.
    8. Kelly, Inas R. & Doytch, Nadia & Dave, Dhaval, 2019. "How does body mass index affect economic growth? A comparative analysis of countries by levels of economic development," Economics & Human Biology, Elsevier, vol. 34(C), pages 58-73.

    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. John Komlos & Marek Brabec, 2010. "The Trend of BMI Values by Centiles of US Adults, Birth Cohorts 1882-1986," CESifo Working Paper Series 3132, CESifo.
    2. Komlos, John & Brabec, Marek, 2011. "The trend of BMI values of US adults by deciles, birth cohorts 1882-1986 stratified by gender and ethnicity," Economics & Human Biology, Elsevier, vol. 9(3), pages 234-250, July.
    3. Angela Noufaily & M. C. Jones, 2013. "Parametric quantile regression based on the generalized gamma distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(5), pages 723-740, November.
    4. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    5. Panayi, Efstathios & Peters, Gareth W. & Danielsson, Jon & Zigrand, Jean-Pierre, 2018. "Designating market maker behaviour in limit order book markets," Econometrics and Statistics, Elsevier, vol. 5(C), pages 20-44.
    6. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    7. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    8. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    9. Tong, Edward N.C. & Mues, Christophe & Thomas, Lyn, 2013. "A zero-adjusted gamma model for mortgage loan loss given default," International Journal of Forecasting, Elsevier, vol. 29(4), pages 548-562.
    10. D. Chiru Naik & Sagar Rohidas Chavan & P. Sonali, 2023. "Incorporating the climate oscillations in the computation of meteorological drought over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 2617-2646, July.
    11. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    12. I. Gijbels & I. Prosdocimi & G. Claeskens, 2010. "Nonparametric estimation of mean and dispersion functions in extended generalized linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 580-608, November.
    13. Groll, Andreas & Hambuckers, Julien & Kneib, Thomas & Umlauf, Nikolaus, 2019. "LASSO-type penalization in the framework of generalized additive models for location, scale and shape," Computational Statistics & Data Analysis, Elsevier, vol. 140(C), pages 59-73.
    14. Westgate, Bradford S. & Woodard, Dawn B. & Matteson, David S. & Henderson, Shane G., 2016. "Large-network travel time distribution estimation for ambulances," European Journal of Operational Research, Elsevier, vol. 252(1), pages 322-333.
    15. Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
    16. Luis Vanegas & Gilberto Paula, 2015. "A semiparametric approach for joint modeling of median and skewness," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 110-135, March.
    17. Jianzhu Li & Yuming Lei & Senming Tan & Colin D. Bell & Bernard A. Engel & Yixuan Wang, 2018. "Nonstationary Flood Frequency Analysis for Annual Flood Peak and Volume Series in Both Univariate and Bivariate Domain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4239-4252, October.
    18. Uddameri, Venkatesh & Ghaseminejad, Ali & Hernandez, E. Annette, 2020. "A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels," Agricultural Water Management, Elsevier, vol. 238(C).
    19. Zhao, Weihua & Lian, Heng & Song, Xinyuan, 2017. "Composite quantile regression for correlated data," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 15-33.
    20. Alexander Sohn & Nadja Klein & Thomas Kneib, 2014. "A New Semiparametric Approach to Analysing Conditional Income Distributions," SOEPpapers on Multidisciplinary Panel Data Research 676, DIW Berlin, The German Socio-Economic Panel (SOEP).

    More about this item

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General

    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:16252. 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.