Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100896
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dc.contributorDepartment of Applied Social Sciencesen_US
dc.creatorLipnicki, DMen_US
dc.creatorMakkar, SRen_US
dc.creatorCrawford, JDen_US
dc.creatorThalamuthu, Aen_US
dc.creatorKochan, NAen_US
dc.creatorLima-Costa, MFen_US
dc.creatorCastro-Costa, Een_US
dc.creatorFerri, CPen_US
dc.creatorBrayne, Cen_US
dc.creatorStephan, Ben_US
dc.creatorLlibre-Rodriguez, JJen_US
dc.creatorLlibre-Guerra, JJen_US
dc.creatorValhuerdi-Cepero, AJen_US
dc.creatorLipton, RBen_US
dc.creatorKatz, MJen_US
dc.creatorDerby, CAen_US
dc.creatorRitchie, Ken_US
dc.creatorAncelin, MLen_US
dc.creatorCarrière, Ien_US
dc.creatorScarmeas, Nen_US
dc.creatorYannakoulia, Men_US
dc.creatorHadjigeorgiou, GMen_US
dc.creatorLam, Len_US
dc.creatorChan, WCen_US
dc.creatorFung, Aen_US
dc.creatorGuaita, Aen_US
dc.creatorVaccaro, Ren_US
dc.creatorDavin, Aen_US
dc.creatorKim, KWen_US
dc.creatorHan, JWen_US
dc.creatorSuh, SWen_US
dc.creatorRiedel-Heller, SGen_US
dc.creatorRoehr, Sen_US
dc.creatorPabst, Aen_US
dc.creatorvan Boxtel, Men_US
dc.creatorKöhler, Sen_US
dc.creatorDeckers, Ken_US
dc.creatorGanguli, Men_US
dc.creatorJacobsen, EPen_US
dc.creatorHughes, TFen_US
dc.creatorAnstey, KJen_US
dc.creatorCherbuin, Nen_US
dc.creatorHaan, MNen_US
dc.creatorAiello, AEen_US
dc.creatorDang, Ken_US
dc.creatorKumagai, Sen_US
dc.creatorChen, Ten_US
dc.creatorNarazaki, Ken_US
dc.creatorNg, TPen_US
dc.creatorGao, Qen_US
dc.creatorNyunt, MSZen_US
dc.creatorScazufca, Men_US
dc.creatorBrodaty, Hen_US
dc.creatorNumbers, Ken_US
dc.creatorTrollor, JNen_US
dc.creatorMeguro, Ken_US
dc.creatorYamaguchi, Sen_US
dc.creatorIshii, Hen_US
dc.creatorLobo, Aen_US
dc.creatorLopez-Anton, Ren_US
dc.creatorSantabárbara, Jen_US
dc.creatorLeung, Yen_US
dc.creatorLo, JWen_US
dc.creatorPopovic, Gen_US
dc.creatorSachdev, PSen_US
dc.date.accessioned2023-08-11T03:14:58Z-
dc.date.available2023-08-11T03:14:58Z-
dc.identifier.issn1549-1277en_US
dc.identifier.urihttp://hdl.handle.net/10397/100896-
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2019 Lipnicki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication Lipnicki DM, Makkar SR, Crawford JD, Thalamuthu A, Kochan NA, Lima-Costa MF, et al. (2019) Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study. PLoS Med 16 (7): e1002853 is available at https://doi.org/10.1371/journal.pmed.1002853.en_US
dc.titleDeterminants of cognitive performance and decline in 20 diverse ethno-regional groups : a COSMIC collaboration cohort studyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume16en_US
dc.identifier.issue7en_US
dc.identifier.doi10.1371/journal.pmed.1002853en_US
dcterms.abstractBackground: With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups.en_US
dcterms.abstractMethods and findings: We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54–105 (mean = 72.7) years and without dementia at baseline. Studies had 2–15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = −0.1, SE = 0.01), APOE*4 carriage (B = −0.31, SE = 0.11), depression (B = −0.11, SE = 0.06), diabetes (B = −0.23, SE = 0.10), current smoking (B = −0.20, SE = 0.08), and history of stroke (B = −0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = −0.07, SE = 0.01), APOE*4 carriage (B = −0.41, SE = 0.18), and diabetes (B = −0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = −0.24, SE = 0.12), and between diabetes and cognitive decline (B = −0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife.en_US
dcterms.abstractConclusions: These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPLOS medicine, July 2019, v. 16, no. 7, e1002853en_US
dcterms.isPartOfPLOS medicineen_US
dcterms.issued2019-07-
dc.identifier.scopus2-s2.0-85070472369-
dc.identifier.pmid31335910-
dc.identifier.eissn1549-1676en_US
dc.identifier.artne1002853en_US
dc.description.validate202305 bcwwen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberAPSS-0615-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextFunding for COSMIC comes from a National Health and Medical Research Council of Australia Program Grant (ID 1093083) (PSS, HB), the National Institute On Aging of the National Institutes of Health under Award Number RF1AG057531 (PSS, MG, RBL, KR, KWK, HB), and philanthropic contributions to The Dementia Momentum Fund (UNSW Project ID PS38235) (PSS, HB). Funding for each of the contributing studies is as follows: The Brazilian Ministry of Health (Department of Science and Technology), the Brazilian Ministry of Science and Technology (National Fund for Scientific and Technological Development, Funding of Studies, Brazilian National Research Council) and the Minas Gerais State Research Foundation (MFLC, ECC); Major awards from the Medical Research Council and the Department of Health, UK (CB); The Wellcome Trust Foundation (GR066133 and GR08002) and the Cuban Ministry of Public Health (JJLR); Supported in part by National Institutes of Health grants NIA 2 P01 AG03949, the Leonard and Sylvia Marx Foundation, and the Czap Foundation (RBL, MJK); Novartis (KR, MLA); IIRG-09133014 from the Alzheimer’s Association; 189 10276/8/9/2011 from the ESPA-EU program Excellence Grant (ARISTEIA), which is co-funded by the European Social Fund and Greek National resources, and ΔΥ2β/οικ.51657/14.4.2009 from the Ministry for Health and Social Solidarity (Greece) (NS); The Mei Family Trust (LL); Financed with own funds and supported in part by "Federazione Alzheimer Italia", Milan, Italy (AG); The Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea [Grant No. HI09C1379 (A092077)] (KWK); The Interdisciplinary Centre for Clinical Research at the University of Leipzig (Interdisziplinäres Zentrum für Klinische Forschung/IZKF; grant 01KS9504) (SGRH); Grant # R01AG07562 from the National Institute on Aging, National Institutes of Health, United States Department of Health and Human Services (MG); National Health and Medical Research Council of Australia grants 973302, 179805, 157125 and 1002160 (KA); NIH grants AG12975, T32 AG049663, ES023451 (MNH); Carolina Population Center (CPC) Funding: CPC Center grant (the P2C Center grant from NIH): P2C HD050924. CPC NICHD-NRSA Population Research Training (the T32 Training grant from NIH): T32 HD007168, Biosocial Training Grant: T32 HD091058 (AEA); JSPS KAKENHI Grant Number JP17K09146 (SK); Agency for Science Technology and Research (A*STAR) Biomedical Research Council (BMRC) [Grants: 03/1/21/17/214 and 08/1/21/19/567] and the National Medical Research Council [Grant: NMRC/1108/2007] (TPN); The Wellcome Trust Foundation and FAPESP, São Paulo, Brazill (MS); National Health & Medical Research Council of Australia Program Grant (ID 350833) (PSS, HB); Supported by grants from the Fondo de Investigación Sanitaria, Instituto de Salud Carlos III, Spanish Ministry of Economy and Competitiveness, Madrid, Spain (grants 94/1562, 97/1321E, 98/0103, 01/0255, 03/0815, 06/0617, G03/128), and the Fondo Europeo de Desarrollo Regional (FEDER) of the European Union and Gobierno de Aragón, Group #19 (AL).en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS20529684-
dc.description.oaCategoryCCen_US
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