IDEAS home Printed from https://ideas.repec.org/a/spr/demogr/v57y2020i2d10.1007_s13524-020-00858-8.html
   My bibliography  Save this article

Multidimensional Mortality Selection: Why Individual Dimensions of Frailty Don’t Act Like Frailty

Author

Listed:
  • Elizabeth Wrigley-Field

    (University of Minnesota)

Abstract

Theoretical models of mortality selection have great utility in explaining otherwise puzzling phenomena. The most famous example may be the Black-White mortality crossover: at old ages, Blacks outlive Whites, presumably because few frail Blacks survive to old ages while some frail Whites do. Yet theoretical models of unidimensional heterogeneity, or frailty, do not speak to the most common empirical situation for mortality researchers: the case in which some important population heterogeneity is observed and some is not. I show that, when one dimension of heterogeneity is observed and another is unobserved, neither the observed nor the unobserved dimension need behave as classic frailty models predict. For example, in a multidimensional model, mortality selection can increase the proportion of survivors who are disadvantaged, or “frail,” and can lead Black survivors to be more frail than Whites, along some dimensions of disadvantage. Transferring theoretical results about unidimensional heterogeneity to settings with both observed and unobserved heterogeneity produces misleading inferences about mortality disparities. The unusually flexible behavior of individual dimensions of multidimensional heterogeneity creates previously unrecognized challenges for empirically testing selection models of disparities, such as models of mortality crossovers.

Suggested Citation

  • Elizabeth Wrigley-Field, 2020. "Multidimensional Mortality Selection: Why Individual Dimensions of Frailty Don’t Act Like Frailty," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 747-777, April.
  • Handle: RePEc:spr:demogr:v:57:y:2020:i:2:d:10.1007_s13524-020-00858-8
    DOI: 10.1007/s13524-020-00858-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13524-020-00858-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13524-020-00858-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Scott Lynch & J. Brown, 2001. "Reconsidering mortality compression and deceleration: an alternative model of mortality rates," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 79-95, February.
    2. Bert Kestenbaum, 1992. "A description of the extreme aged population based on improved medicare enrollment data," Demography, Springer;Population Association of America (PAA), vol. 29(4), pages 565-580, November.
    3. Väinö Kannisto, 2000. "Measuring the compression of mortality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 3(6).
    4. Andrei Rogers, 1992. "Heterogeneity and selection in multistate population analysis," Demography, Springer;Population Association of America (PAA), vol. 29(1), pages 31-38, February.
    5. Matthew Dupre & Alexis Franzese & Emilio Parrado, 2006. "Religious attendance and mortality: Implications for the black-white mortality crossover," Demography, Springer;Population Association of America (PAA), vol. 43(1), pages 141-164, February.
    6. Finkelstein, Maxim & Esaulova, Veronica, 2008. "On asymptotic failure rates in bivariate frailty competing risks models," Statistics & Probability Letters, Elsevier, vol. 78(10), pages 1174-1180, August.
    7. James Vaupel, 1988. "Inherited frailty and longevity," Demography, Springer;Population Association of America (PAA), vol. 25(2), pages 277-287, May.
    8. Sautter, J.M. & Thomas, P.A. & Dupre, M.E. & George, L.K., 2012. "Socioeconomic status and the black-white mortality crossover," American Journal of Public Health, American Public Health Association, vol. 102(8), pages 1566-1571.
    9. Finkelstein, Maxim, 2012. "On ordered subpopulations and population mortality at advanced ages," Theoretical Population Biology, Elsevier, vol. 81(4), pages 292-299.
    10. Andrew Fenelon, 2013. "An examination of black/white differences in the rate of age-related mortality increase," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(17), pages 441-472.
    11. R. Henderson & P. Oman, 1999. "Effect of frailty on marginal regression estimates in survival analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 367-379, April.
    12. David Steinsaltz & Kenneth Wachter, 2006. "Understanding Mortality Rate Deceleration and Heterogeneity," Mathematical Population Studies, Taylor & Francis Journals, vol. 13(1), pages 19-37.
    13. Elizabeth Wrigley-Field, 2014. "Mortality Deceleration and Mortality Selection: Three Unexpected Implications of a Simple Model," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 51-71, February.
    14. Andreas Wienke & Paul Lichtenstein & Anatoli I. Yashin, 2003. "A Bivariate Frailty Model with a Cure Fraction for Modeling Familial Correlations in Diseases," Biometrics, The International Biometric Society, vol. 59(4), pages 1178-1183, December.
    15. Elizabeth Wrigley-Field, 2013. "Mortality deceleration is not informative of unobserved heterogeneity in open groups," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 11(1), pages 15-36.
    16. Yi Zeng & James W. Vaupel, 2003. "Oldest Old Mortality in China," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 8(7), pages 215-244.
    17. Michal Engelman & Vladimir Canudas‐Romo & Emily M. Agree, 2010. "The Implications of Increased Survivorship for Mortality Variation in Aging Populations," Population and Development Review, The Population Council, Inc., vol. 36(3), pages 511-539, September.
    18. Shiro Horiuchi & John Wilmoth, 1998. "Deceleration in the age pattern of mortality at olderages," Demography, Springer;Population Association of America (PAA), vol. 35(4), pages 391-412, November.
    19. Bowleg, L., 2012. "The problem with the phrase women and minorities: Intersectionality-an important theoretical framework for public health," American Journal of Public Health, American Public Health Association, vol. 102(7), pages 1267-1273.
    20. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    21. Lisa Berkman & Burton Singer & Kenneth Manton, 1989. "Black/White Differences in Health Status and Mortality Among the Elderly," Demography, Springer;Population Association of America (PAA), vol. 26(4), pages 661-678, November.
    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. Elizabeth Wrigley-Field, 2014. "Mortality Deceleration and Mortality Selection: Three Unexpected Implications of a Simple Model," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 51-71, February.
    2. Dan A. Black & Yu-Chieh Hsu & Seth G. Sanders & Lynne Steuerle Schofield & Lowell J. Taylor, 2017. "The Methuselah Effect: The Pernicious Impact of Unreported Deaths on Old-Age Mortality Estimates," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2001-2024, December.
    3. Dennis M. Feehan, 2018. "Separating the Signal From the Noise: Evidence for Deceleration in Old-Age Death Rates," Demography, Springer;Population Association of America (PAA), vol. 55(6), pages 2025-2044, December.
    4. Andrew Fenelon, 2013. "An examination of black/white differences in the rate of age-related mortality increase," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(17), pages 441-472.
    5. Elizabeth Wrigley-Field, 2013. "Mortality deceleration is not informative of unobserved heterogeneity in open groups," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 11(1), pages 15-36.
    6. Dalkhat M. Ediev, 2013. "Decompression of Period Old-Age Mortality: When Adjusted for Bias, the Variance in the Ages at Death Shows Compression," Mathematical Population Studies, Taylor & Francis Journals, vol. 20(3), pages 137-154, July.
    7. Lucia Zanotto & Vladimir Canudas-Romo & Stefano Mazzuco, 2021. "A Mixture-Function Mortality Model: Illustration of the Evolution of Premature Mortality," European Journal of Population, Springer;European Association for Population Studies, vol. 37(1), pages 1-27, March.
    8. Hartemink, Nienke & Missov, Trifon I. & Caswell, Hal, 2017. "Stochasticity, heterogeneity, and variance in longevity in human populations," Theoretical Population Biology, Elsevier, vol. 114(C), pages 107-116.
    9. Anna Zajacova & Sarah Burgard, 2013. "Healthier, Wealthier, and Wiser: A Demonstration of Compositional Changes in Aging Cohorts Due to Selective Mortality," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 32(3), pages 311-324, June.
    10. Cha, Ji Hwan & Finkelstein, Maxim, 2016. "Justifying the Gompertz curve of mortality via the generalized Polya process of shocks," Theoretical Population Biology, Elsevier, vol. 109(C), pages 54-62.
    11. Glenn Firebaugh & Francesco Acciai & Aggie Noah & Christopher Prather & Claudia Nau, 2014. "Why Lifespans Are More Variable Among Blacks Than Among Whites in the United States," Demography, Springer;Population Association of America (PAA), vol. 51(6), pages 2025-2045, December.
    12. Kenneth Manton & Igor Akushevich & Alexander Kulminski, 2008. "Human Mortality at Extreme Ages: Data from the NLTCS and Linked Medicare Records," Mathematical Population Studies, Taylor & Francis Journals, vol. 15(3), pages 137-159.
    13. Il Do Ha & Maengseok Noh & Youngjo Lee, 2010. "Bias Reduction of Likelihood Estimators in Semiparametric Frailty Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 307-320, June.
    14. Carlos Díaz-Venegas, 2014. "Identifying the Confounders of Marginalization and Mortality in Mexico, 2003–2007," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(2), pages 851-875, September.
    15. Annamaria Olivieri & Ermanno Pitacco, 2016. "Frailty and Risk Classification for Life Annuity Portfolios," Risks, MDPI, vol. 4(4), pages 1-23, October.
    16. Yoram Halevy, 2004. "Diminishing Impatience: Disentangling Time Preference from Uncertain Lifetime," Levine's Bibliography 122247000000000185, UCLA Department of Economics.
    17. Ting Li & Yang Yang & James Anderson, 2013. "Mortality Increase in Late-Middle and Early-Old Age: Heterogeneity in Death Processes as a New Explanation," Demography, Springer;Population Association of America (PAA), vol. 50(5), pages 1563-1591, October.
    18. Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," Working Papers halshs-02871927, HAL.
    19. Jonas Šiaulys & Rokas Puišys, 2022. "Survival with Random Effect," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    20. Claudia Nau & Glenn Firebaugh, 2012. "A New Method for Determining Why Length of Life is More Unequal in Some Populations Than in Others," Demography, Springer;Population Association of America (PAA), vol. 49(4), pages 1207-1230, November.

    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:spr:demogr:v:57:y:2020:i:2:d:10.1007_s13524-020-00858-8. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.springer.com .

    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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.