biostudies-literatureGBD 2019 Dementia CollaboratorsNIA NIH HHSMedical Research CouncilBill and Melinda Gates Foundationgates venturesWellcome Trust241https://www.ebi.ac.uk/biostudies/studies/S-EPMC8356410biostudies-literatureUnknown21(1)<h4>Background</h4>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.<h4>Methods</h4>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 regressiBMC medical informatics and decision makingUse 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.PMC8356410OPP1152504MR/R024227221854/Z/20/ZR01 AG025533G0601022R01 AG056477MR/S011676Mohammed SEdvardsson DBaune BTBijani AKalani RAkinyemi ROMokdad AHYesiltepe MPottoo FHRashedi VSkryabina AAIlic MDSingh JABanach MEl-Jaafary SIVacante MYadollahpour AHwang BFHankey GJYonemoto NKhader YSOwolabi MORezaei NShiri RSzoeke CEICerin ETsegaye GWBurugina Nagaraja SBiswas AAlipour VAshraf-Ganjouei AHeidari GKhatib MNBrayne CGolechha MIacoviello LGhashghaee AWang YPVlassov VBrenner HMadhava Kunjathur SNaveed MBarboza MAFischer FVu GTRoshandel GPatel UKTaddele BWIrvani SSNSaylan MWimo AAbu-Gharbieh EAyano GNguyen HLTDai XSkryabin VYWeldemariam AHde Sa-Junior ARAyuso-Mateos JLBurkart KKoyanagi AGebremeskel GGTabares-Seisdedos RAbd-Allah FNunez-Samudio VLi BNichols EDjalalinia SGupta RIlic IMZastrozhina AChu DTHamiduzzaman MKhan EAShibuya KCherbuin NKarch AMehndiratta MMRadfar AAfshin ASha FCastro-de-Araujo LFSZhang ZJEskandarieh SYu CMenezes RGSotoudeh HMoni MAOstroff SMNagel GFaro AKisa SBoloor AWu CKumar MSinghal DBhagavathula ASMurray CJLIwagami MMohammad YGialluisi AKisa AJha RPSamaei MShigematsu MSpurlock EEVenketasubramanian NWinkler ASRana JHay SIVos TBarker-Collo SLPrada SIFarzadfar FAbdoli ARawaf DLFerrara PTovani-Palone MRFernandes EOtstavnov NRezapour ALasrado SSahraian MARenzaho AMNLim SSBaig AAFilip IHo HCVidale SSoheili AGalluzzo LNguyen CTHachinski VLandires ISachdev PSHouseh MArabloo JKivimaki MNayak VCBhattacharyya KFeigin VLAlanezi FMGBD 2019 Dementia CollaboratorsDouiri ALiu XWeiss JShin JIHaile TGPond CDWesterman RKim YJHeidari-Soureshjani RSilva DASPashazadeh Kan FShaikh MARawaf SSahebkar AGaidhane SPhillips MRHaider MRMalik POlagunju ATReinig NZastrozhin MSRomoli MRahim FCarvalho FIyamu IOCatala-Lopez FPiradov MAGnedovskaya EVIlesanmi OSAlmasi-Hashiani AKasa ASFereshtehnejad SMMajeed AAbualhasan AfalseUse 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.<h4>Background</h4>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.<h4>Methods</h4>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 regressi2021-01-01T00:00:00Z2021 Aug2025-05-18T13:26:58.143Z2022-02-11T06:52:24.511ZS-EPMC83564103438048510.1186/s12911-021-01590-y