IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v22y2013i4p517-534.html
   My bibliography  Save this article

Estimating health expectancy in presence of missing data: an application using HID survey

Author

Listed:
  • Cristina Giudici
  • Maria Arezzo
  • Nicolas Brouard

Abstract

In this article we estimate health transition probabilities using longitudinal data collected in France for the survey on handicaps, disabilities and dependencies from 1998 to 2001. Life expectancies with and without disabilities are estimated using a Markov-based multi-state life table approach with two non-absorbing states: able to perform all activities of daily living (ADLs) and unable or in need of help to perform one or more ADLs, and the absorbing state of death. The loss of follow-up between the two waves induces biases in the probabilities estimates: mortality estimates were biased upwards; also the incidence of recovery and the onset of disability seemed to be biased. Since individuals were not missing completely at random, we correct this bias by estimating health status for drop-outs using a non parametric model. After imputation, we found that at the age of 70 disability-free life expectancy decreases by 0.5 years, whereas the total life expectancy increases by 1 year. The slope of the stable prevalence increases, but it remains lower than the slope of the cross sectional prevalence. The gender differences on life expectancy did not change significantly after imputation. Globally, there is no evidence of a general reduction in ADL disability, as defined in our study. The added value of the study is the reduction of the bias induced by sample attrition. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Cristina Giudici & Maria Arezzo & Nicolas Brouard, 2013. "Estimating health expectancy in presence of missing data: an application using HID survey," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(4), pages 517-534, November.
    • Handle: RePEc:spr:stmapp:v:22:y:2013:i:4:p:517-534
    DOI: 10.1007/s10260-013-0233-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10260-013-0233-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10260-013-0233-8?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. Scheuren, Fritz, 2005. "Multiple Imputation: How It Began and Continues," The American Statistician, American Statistical Association, vol. 59, pages 315-319, November.
    2. Vanessa Yong & Yasuhiko Saito, 2012. "Are There Education Differentials in Disability and Mortality Transitions and Active Life Expectancy Among Japanese Older Adults? Findings From a 10-Year Prospective Cohort Study," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 67(3), pages 343-353.
    3. Flávia C. D. Andrade, 2010. "Measuring the Impact of Diabetes on Life Expectancy and Disability-Free Life Expectancy Among Older Adults in Mexico," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 65(3), pages 381-389.
    4. repec:dau:papers:123456789/449 is not listed on IDEAS
    5. Agnes Lievre & Nicolas Brouard & Christopher Heathcote, 2003. "The Estimation Of Health Expectancies From Cross-Longitudinal Surveys," Mathematical Population Studies, Taylor & Francis Journals, vol. 10(4), pages 211-248.
    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. Cristina Giudici & Silvia Polettini & Alessandra Rose & Nicolas Brouard, 2019. "Which Aspects of Elderly Living Conditions are Important to Predict Mortality? The Complex Role of Family Ties at Home and in Institutions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 1255-1283, April.

    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. Cristina Giudici & Silvia Polettini & Alessandra Rose & Nicolas Brouard, 2019. "Which Aspects of Elderly Living Conditions are Important to Predict Mortality? The Complex Role of Family Ties at Home and in Institutions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 1255-1283, April.
    2. Nancy, Jane Y. & Khanna, Nehemiah H. & Arputharaj, Kannan, 2017. "Imputing missing values in unevenly spaced clinical time series data to build an effective temporal classification framework," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 63-79.
    3. Michel Guillot & Yan Yu, 2009. "Estimating health expectancies from two cross-sectional surveys," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 21(17), pages 503-534.
    4. Timothy Riffe & Iñaki Permanyer & Rustam Tursun-Zade & Magdalena Muszynska-Spielauer, 2024. "Calculating the joint distribution of years lived in good and poor health," MPIDR Working Papers WP-2024-013, Max Planck Institute for Demographic Research, Rostock, Germany.
    5. Yu, Dandan & Lu, Bei & Piggott, John, 2022. "Alcohol consumption as a predictor of mortality and life expectancy: Evidence from older Chinese males," The Journal of the Economics of Ageing, Elsevier, vol. 22(C).
    6. Chia-Chun Liang & Wei-Chung Hsu & Yao-Te Tsai & Shao-Jen Weng & Ho-Pang Yang & Shih-Chia Liu, 2020. "Healthy Life Expectancies by the Effects of Hypertension and Diabetes for the Middle Aged and Over in Taiwan," IJERPH, MDPI, vol. 17(12), pages 1-9, June.
    7. Hal Caswell & Silke van Daalen, 2021. "Healthy longevity from incidence-based models: More kinds of health than stars in the sky," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(13), pages 397-452.
    8. Florian Meinfelder, 2014. "Multiple Imputation: an attempt to retell the evolutionary process," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(4), pages 249-267, November.
    9. Kilic, Talip & Zezza, Alberto & Carletto, Calogero & Savastano, Sara, 2017. "Missing(ness) in Action: Selectivity Bias in GPS-Based Land Area Measurements," World Development, Elsevier, vol. 92(C), pages 143-157.
    10. Hua Yun Chen & Hui Xie & Yi Qian, 2011. "Multiple Imputation for Missing Values through Conditional Semiparametric Odds Ratio Models," Biometrics, The International Biometric Society, vol. 67(3), pages 799-809, September.
    11. Holendro Singh Chungkham & Robin S. Högnäs & Jenny Head & Paola Zaninotto & Hugo Westerlund, 2023. "Estimating Working Life Expectancy: A Comparison of Multistate Models," SAGE Open, , vol. 13(2), pages 21582440231, May.
    12. Matthews, Ruth J. & Jagger, Carol & Hancock, Ruth M., 2006. "Does socio-economic advantage lead to a longer, healthier old age?," Social Science & Medicine, Elsevier, vol. 62(10), pages 2489-2499, May.
    13. Md Ismail Tareque & Sharifa Begum & Yasuhiko Saito, 2014. "Inequality in Disability in Bangladesh," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-10, July.
    14. Emmanuelle Cambois & Caroline Laborde & Isabelle Romieu & Jean-Marie Robine, 2011. "Occupational inequalities in health expectancies in France in the early 2000s: Unequal chances of reaching and living retirement in good health," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(12), pages 407-436.
    15. William Lim & Gaurav Khemka & David Pitt & Bridget Browne, 2019. "A method for calculating the implied no-recovery three-state transition matrix using observable population mortality incidence and disability prevalence rates among the elderly," Journal of Population Research, Springer, vol. 36(3), pages 245-282, September.
    16. Takaku, Reo, 2020. "Reversal pattern of health inequality: New evidence from a large-scale national survey in Japan," Health Policy, Elsevier, vol. 124(11), pages 1254-1262.
    17. Liming Cai & Mark D. Hayward & Yasuhiko Saito & James Lubitz & Aaron Hagedorn & Eileen Crimmins, 2010. "Estimation of multi-state life table functions and their variability from complex survey data using the SPACE Program," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 22(6), pages 129-158.
    18. Stuart R. Lipsitz & Garrett M. Fitzmaurice & Roger D. Weiss, 2020. "Using Multiple Imputation with GEE with Non-monotone Missing Longitudinal Binary Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 890-904, December.
    19. Benedetta Pongiglione & Bianca L De Stavola & George B Ploubidis, 2015. "A Systematic Literature Review of Studies Analyzing Inequalities in Health Expectancy among the Older Population," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-21, June.
    20. Yang Zhao & Meng Liu, 2021. "Unified approach for regression models with nonmonotone missing at random data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(1), pages 87-101, March.

    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:stmapp:v:22:y:2013:i:4:p:517-534. 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: 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. RePEc uses bibliographic data supplied by the respective publishers.