Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

GBD 2019 Dementia Collaborators

Research output: Contribution to journalArticlepeer-review


Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys.

Original languageEnglish
Article number241
JournalBMC Medical Informatics and Decision Making
Issue number1
Publication statusPublished - 2021 Dec

Bibliographical note

Funding Information:
This work was funded by the Bill and Melinda Gates foundation [Grant No. OPP1152504] and Gates Ventures. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or the writing of the report.

Funding Information:
Rufus Olusola Akinyemi is supported by the FLAIR fellowship of the UK Royal Society/African Academic of Sciences and the US National Institutes of Health (U01HG010273). Felix Carvalho and Eduarda Fernandes acknowledge UID/MULTI/04378/2019 and UID/QUI/50006/2019 support with funding from FCT/MCTES through national funds. Luis Castro-de-Araujo has been awarded an MRC Grant (No. MR/T03355X/1). Abdel Douiri acknowledges funding support from the National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) South London at King’s College Hospital NHS Foundation Trust and the Royal College of Physicians, as well as the support from the NIHR Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. Andre Faro acknowledges the National Council for Scientific and Technological Development (Brazil). Alessandro Gialluisi was supported by Fondazione Umberto Veronesi. Mohammad Rifat Haider has been supported by Ohio University Research Council (OURC) Spring 2020 Grant. Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia [No.: XMUMRF/2020-C6/ITCM/0004]. Mika Kivimäki reports Grants from the Medical Research Council (MR/S011676, MR/R024227), US National Institute on Aging (R01AG062553, R01AG056477) and NordForsk (75021), during the conduct of the study. Manasi Kumar would like to acknowledge FIC/NIH K43TW 010716-03. Iván Landires is member of the Sistema Nacional de Investigación (SNI), supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panama. Michael R. Phillips acknowledges support from the Global Alliance for Chronic Diseases-National Natural Science Foundation of China (NSFC. No. 81761128031). Sergio I Prada acknowledges support from the Fundación Valle del Lili, Cali, Colombia. Feng Sha was supported by the Shenzhen Science and Technology Program (Grant No. KQTD20190929172835662). Cassandra E I Szoeke is supported by the National Health and Medical Research Council. Naohiro Yonemoto was supported by a Grant-in-Aid for Scientific Research (KAKEN), 20K10337, Japan.

Funding Information:
Graeme J Hankey reports personal honoraria from the American Heart Association (for serving as an associate editor of Circulation), and from AC Immune (for serving as Chair, Data Safety Monitoring Committee, of ACI-24-701 and AC-35-1201 trials of an immune therapy for Alzheimer’s disease). Mika Kivimäki reports Grants from Medical Research Council (MR/S011676, MR/R024227), US National Institute on Aging (R01AG062553, R01AG056477), and NordForsk (75021), outside the submitted work. Constance Dimity Pond reports personal fees from Nutricia, outside the submitted work, and received Grants from the National Medical Research council in relation to dementia, and travel Grants and remuneration related to education of primary care professionals in relation to dementia. Perminder S Sachdev reports Grants from National Health and Medical Research Council, and NIA/NIH, during the conduct of the study, and personal fees from Biogen Australia, outside the submitted work. Mete Saylan reports being an employee of Bayer AG. Jasvinder A Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Trio health, Medscape, WebMD, Clinical Care options, Clearview healthcare partners, Putnam associates, Focus forward, Navigant consulting, Spherix, Practice Point communications, the National Institutes of Health and the American College of Rheumatology, and from Simply Speaking; owning stock options in Amarin, Viking, Moderna and Vaxart pharmaceuticals and Charlotte’s Web Holdings; membership in the FDA Arthritis Advisory Committee, the Steering committee of OMERACT, an international organization that develops measures for clinical trials and receives arm’s length funding from 12 pharmaceutical companies, and the Veterans Affairs Rheumatology Field Advisory Committee, and acting as Editor and the Director of the UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis, all outside the submitted work. Anders Wimo reports personal fees from WHO, and non-financial support from ADI, during the conduct of the study; Grants from MSD, and personal fees from Biogen, outside the submitted work.

Publisher Copyright:
© 2021, The Author(s).

All Science Journal Classification (ASJC) codes

  • Health Policy
  • Health Informatics
  • Computer Science Applications


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