IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v119y2018icp83-90.html
   My bibliography  Save this article

Projections of health indicators for chronic disease under a semi-Markov assumption

Author

Listed:
  • Wanneveich, Mathilde
  • Jacqmin-Gadda, Hélène
  • Dartigues, Jean-François
  • Joly, Pierre

Abstract

Chronic diseases are a growing public health problem due to the population aging. Their economic, social and demographic burden will worsen in years to come. Up to now, the method used to provide projections and assess the future disease burden makes a non-homogeneous Markov assumption in an illness–death model. Both age and calendar year have been taken into account in all parameter estimations, but the time spent with the disease was not considered.

Suggested Citation

  • Wanneveich, Mathilde & Jacqmin-Gadda, Hélène & Dartigues, Jean-François & Joly, Pierre, 2018. "Projections of health indicators for chronic disease under a semi-Markov assumption," Theoretical Population Biology, Elsevier, vol. 119(C), pages 83-90.
    • Handle: RePEc:eee:thpobi:v:119:y:2018:i:c:p:83-90
    DOI: 10.1016/j.tpb.2017.11.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580917301077
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2017.11.006?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. Daniel Commenges & Pierre Joly & Anne Gégout‐Petit & Benoit Liquet, 2007. "Choice between Semi‐parametric Estimators of Markov and Non‐Markov Multi‐state Models from Coarsened Observations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(1), pages 33-52, March.
    2. Pierre Joly & Célia Touraine & Aurore Georget & Jean-François Dartigues & Daniel Commenges & Hélène Jacqmin-Gadda, 2013. "Prevalence Projections of Chronic Diseases and Impact of Public Health Intervention," Biometrics, The International Biometric Society, vol. 69(1), pages 109-117, March.
    3. Ardo Van Den Hout & Fiona E. Matthews, 2010. "Estimating stroke‐free and total life expectancy in the presence of non‐ignorable missing values," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 331-349, April.
    4. Touraine, Célia & Gerds, Thomas A. & Joly, Pierre, 2017. "SmoothHazard: An R Package for Fitting Regression Models to Interval-Censored Observations of Illness-Death Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i07).
    5. Brinks, Ralph & Landwehr, Sandra, 2014. "Age- and time-dependent model of the prevalence of non-communicable diseases and application to dementia in Germany," Theoretical Population Biology, Elsevier, vol. 92(C), pages 62-68.
    6. Brookmeyer, R. & Gray, S. & Kawas, C., 1998. "Projections of Alzheimer's disease in the United States and the public health impact of delaying disease onset," American Journal of Public Health, American Public Health Association, vol. 88(9), pages 1337-1342.
    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. Pierre Joly & Célia Touraine & Aurore Georget & Jean-François Dartigues & Daniel Commenges & Hélène Jacqmin-Gadda, 2013. "Prevalence Projections of Chronic Diseases and Impact of Public Health Intervention," Biometrics, The International Biometric Society, vol. 69(1), pages 109-117, March.
    2. Touraine, Célia & Gerds, Thomas A. & Joly, Pierre, 2017. "SmoothHazard: An R Package for Fitting Regression Models to Interval-Censored Observations of Illness-Death Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i07).
    3. Susanne Weber & Martin Wolkewitz & on behalf of COMBACTE‐MAGNET Consortium, 2020. "Accounting for length of hospital stay in regression models in clinical epidemiology," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(1), pages 24-37, February.
    4. Boumezoued, Alexandre & Karoui, Nicole El & Loisel, Stéphane, 2017. "Measuring mortality heterogeneity with multi-state models and interval-censored data," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 67-82.
    5. Li, Jinqing & Ma, Jun, 2019. "Maximum penalized likelihood estimation of additive hazards models with partly interval censoring," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 170-180.
    6. James F Burke & Kenneth M Langa & Rodney A Hayward & Roger L Albin, 2014. "Modeling Test and Treatment Strategies for Presymptomatic Alzheimer Disease," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-20, December.
    7. Jamal B. Williams & Qing Cao & Wei Wang & Young-Ho Lee & Luye Qin & Ping Zhong & Yong Ren & Kaijie Ma & Zhen Yan, 2023. "Inhibition of histone methyltransferase Smyd3 rescues NMDAR and cognitive deficits in a tauopathy mouse model," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    8. Zarish Noreen & Jessica DeJesus & Attya Bhatti & Christopher A. Loffredo & Peter John & Jahangir S. Khan & Gail Nunlee-Bland & Somiranjan Ghosh, 2018. "Epidemiological Investigation of Type 2 Diabetes and Alzheimer’s Disease in a Pakistani Population," IJERPH, MDPI, vol. 15(8), pages 1-10, July.
    9. Daniel Commenges & Benoit Liquet & Cécile Proust-Lima, 2012. "Choice of Prognostic Estimators in Joint Models by Estimating Differences of Expected Conditional Kullback–Leibler Risks," Biometrics, The International Biometric Society, vol. 68(2), pages 380-387, June.
    10. Li, Chenxi, 2016. "Cause-specific hazard regression for competing risks data under interval censoring and left truncation," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 197-208.
    11. Masataka Kikuchi & Soichi Ogishima & Tadashi Miyamoto & Akinori Miyashita & Ryozo Kuwano & Jun Nakaya & Hiroshi Tanaka, 2013. "Identification of Unstable Network Modules Reveals Disease Modules Associated with the Progression of Alzheimer’s Disease," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
    12. Daniel Commenges, 2019. "Dealing with death when studying disease or physiological marker: the stochastic system approach to causality," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 381-405, July.
    13. Luis Miguel Bello-Lujan & Jose Antonio Serrano-Sanchez & Juan Jose Gonzalez-Henriquez, 2022. "Stable Gender Gap and Similar Gender Trend in Chronic Morbidities between 1997–2015 in Adult Canary Population," IJERPH, MDPI, vol. 19(15), pages 1-19, July.
    14. Ralph Brinks & Annika Hoyer, 2018. "Illness-death model: statistical perspective and differential equations," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(4), pages 743-754, October.
    15. Commenges Daniel & Proust-Lima Cécile & Samieri Cécilia & Liquet Benoit, 2015. "A Universal Approximate Cross-Validation Criterion for Regular Risk Functions," The International Journal of Biostatistics, De Gruyter, vol. 11(1), pages 51-67, May.

    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:eee:thpobi:v:119:y:2018:i:c:p:83-90. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.