IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v109y2014i505p24-35.html
   My bibliography  Save this article

Estimating the Lifetime Risk of Dementia in the Canadian Elderly Population Using Cross-Sectional Cohort Survival Data

Author

Listed:
  • Marco Carone
  • Masoud Asgharian
  • Nicholas P. Jewell

Abstract

Dementia is one of the world's major public health challenges. The lifetime risk of dementia is the proportion of individuals who ever develop dementia during their lifetime. Despite its importance to epidemiologists and policy-makers, this measure does not seem to have been estimated in the Canadian population. Data from a birth cohort study of dementia are not available. Instead, we must rely on data from the Canadian Study of Health and Aging, a large cross-sectional study of dementia with follow-up for survival. These data present challenges because they include substantial loss to follow-up and are not representatively drawn from the target population because of structural sampling biases. A first bias is imparted by the cross-sectional sampling scheme, while a second bias is a result of stratified sampling. Estimation of the lifetime risk and related quantities in the presence of these biases has not been previously addressed in the literature. We develop and study nonparametric estimators of the lifetime risk, the remaining lifetime risk, and cumulative risk at specific ages, accounting for these complexities. In particular, we reveal the fact that estimation of the lifetime risk is invariant to stratification by current age at sampling. We present simulation results validating our methodology, and provide novel facts about the epidemiology of dementia in Canada using data from the Canadian Study of Health and Aging. Supplementary materials for this article are available online.

Suggested Citation

  • Marco Carone & Masoud Asgharian & Nicholas P. Jewell, 2014. "Estimating the Lifetime Risk of Dementia in the Canadian Elderly Population Using Cross-Sectional Cohort Survival Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 24-35, March.
  • Handle: RePEc:taf:jnlasa:v:109:y:2014:i:505:p:24-35
    DOI: 10.1080/01621459.2013.859076
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2013.859076
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01621459.2013.859076?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. M. Mandel & R. Fluss, 2009. "Nonparametric estimation of the probability of illness in the illness-death model under cross-sectional sampling," Biometrika, Biometrika Trust, vol. 96(4), pages 861-872.
    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. Paul Gerrans & Anthony Asher & Joanne Kaa Earl, 2022. "Cognitive functioning, financial literacy, and judgment in older age," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1637-1674, April.
    2. Ezra Fishman, 2017. "Risk of Developing Dementia at Older Ages in the United States," Demography, Springer;Population Association of America (PAA), vol. 54(5), pages 1897-1919, October.

    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. Mei-Cheng Wang & Yuxin Zhu, 2022. "Bias correction via outcome reassignment for cross-sectional data with binary disease outcome," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(4), pages 659-674, October.
    2. Micha Mandel & Yosef Rinott, 2012. "Cross-Sectional Sampling, Bias, Dependence, and Composite Likelihood," Discussion Paper Series dp614, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.

    More about this item

    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:taf:jnlasa:v:109:y:2014:i:505:p:24-35. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    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.