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Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study

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  • معلومة اضافية
    • Contributors:
      Psychiatrie & Neuropsychologie; Section Neuropsychology; RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience; RS: FPN NPPP I; Hadjigeorgiou, Georgios M. [0000-0001-5386-4273]; Yannakoulia, Mary [0000-0003-2171-7337]; Scarmeas, Nikolaos [0000-0001-6453-8908]; Herrada, Anthony; University of New South Wales [Sydney] (UNSW); Fundação Oswaldo Cruz (FIOCRUZ); Réseau International des Instituts Pasteur (RIIP); Federal University of Sao Paulo (Unifesp); University of Cambridge [UK] (CAM); Newcastle University [Newcastle]; University of Havana (Universidad de la Habana) (UH); University of California (UC); Universidad de Matanzas; Albert Einstein College of Medicine [New York]; Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC); Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM); Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier); University of Edinburgh; National and Kapodistrian University of Athens (NKUA); Columbia University [New York]; Harokopio University of Athens; University of Cyprus [Nicosia] (UCY); The Chinese University of Hong Kong [Hong Kong]; The University of Hong Kong (HKU); The Hong Kong Polytechnic University [Hong Kong] (POLYU); Seoul National University [Seoul] (SNU); Universität Leipzig [Leipzig]; Maastricht University Medical Centre (MUMC); Maastricht University [Maastricht]; University of Pittsburgh School of Medicine; Pennsylvania Commonwealth System of Higher Education (PCSHE); Youngstown State University (YSU); Australian National University (ANU); University of North Carolina [Chapel Hill] (UNC); University of North Carolina System (UNC); Kyushu University; Fukuoka Institute of Technology (FIT); National University of Singapore (NUS); Universidade de São Paulo = University of São Paulo (USP); Tohoku University [Sendai]; Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM); University of Zaragoza - Universidad de Zaragoza [Zaragoza]; Funding 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). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other funders.; Tsai, Alexander C; University of California; University of Cyprus [Nicosia]; Kyushu University [Fukuoka]; Universidade de São Paulo (USP); Lipnicki, Darren M [0000-0002-1684-3577]; Kochan, Nicole A [0000-0002-8630-6398]; Ferri, Cleusa Pinheiro [0000-0002-1815-7685]; Brayne, Carol [0000-0001-5307-663X]; Stephan, Blossom [0000-0002-1235-360X]; Llibre-Guerra, Jorge J [0000-0002-2137-7750]; Ritchie, Karen [0000-0002-0688-8982]; Chan, Wai-Chi [0000-0002-7324-0553]; Fung, Ada [0000-0001-7439-3503]; Guaita, Antonio [0000-0003-3954-5932]; Kim, Ki Woong [0000-0002-1103-3858]; Han, Ji Won [0000-0003-2418-4257]; Riedel-Heller, Steffi G [0000-0003-4321-6090]; Roehr, Susanne [0000-0001-9385-0669]; van Boxtel, Martin [0000-0002-3221-2150]; Köhler, Sebastian [0000-0002-2398-0609]; Deckers, Kay [0000-0003-1339-2974]; Ganguli, Mary [0000-0003-2762-7105]; Jacobsen, Erin P [0000-0002-4599-6214]; Anstey, Kaarin J [0000-0002-9706-9316]; Cherbuin, Nicolas [0000-0001-6481-0748]; Haan, Mary N [0000-0001-9312-4501]; Aiello, Allison E [0000-0001-7029-2537]; Ng, Tze Pin [0000-0001-9585-855X]; Gao, Qi [0000-0002-1965-7411]; Scazufca, Marcia [0000-0002-4545-006X]; Numbers, Katya [0000-0002-7009-2401]; Ishii, Hiroshi [0000-0001-9829-7743]; Lopez-Anton, Raul [0000-0002-3360-7015]; Leung, Yvonne [0000-0001-9110-7054]; Lo, Jessica W [0000-0003-4778-8360]; Popovic, Gordana [0000-0002-1376-1058]; Sachdev, Perminder S [0000-0002-9595-3220]; Apollo - University of Cambridge Repository
    • بيانات النشر:
      Public Library of Science, 2019.
    • الموضوع:
      2019
    • نبذة مختصرة :
      Background 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. Methods 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. Conclusions 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.
      Darren Lipnicki and the Sydney COSMIC team analysed cognitive performance and risk factor data from older people from 15 countries to assess associations between risk factors and late-life cognition
      Author summary Why was this study done? There is a growing global burden associated with cognitive decline and dementia. Evidence for modifiable risk factors that could be targeted to reduce this burden needs to be improved. Risk factors for cognitive decline and dementia might differ between ethno-regional groups. What did the researchers do and find? We analyzed cognitive performance and risk factor data from 48,522 older individuals, provided by 20 studies of aging representing 15 countries (Australia, Brazil, Cuba, France, Germany, Greece, Hong Kong, Italy, Japan, Singapore, Spain, South Korea, The Netherlands, the United Kingdom, and the United States). Cognitive performance was measured as Mini-Mental State Examination (MMSE) and global cognition scores. When controlling for confounding risk factors, the apolipoprotein E ε4 allele (APOE*4), depression, diabetes, current smoking, and history of stroke were associated with poorer cognitive performance, and higher levels of education and vigorous physical activity were associated with better performance. Age, APOE*4, and diabetes were associated with faster cognitive decline. Compared to white people, Asian people showed stronger associations between having ever smoked and cognitive performance, and between diabetes and cognitive decline. What do these findings mean? Modifiable risk factors associated with cognitive decline include education, smoking, physical activity, diabetes, and stroke. If these associations are determined to be causal, interventions targeting these factors may help reduce the global burden of cognitive decline and dementia. Interventions may require tailoring to particular ethno-regional groups.
    • File Description:
      application/pdf
    • ISSN:
      1549-1676
      1549-1277
    • Rights:
      OPEN
    • الرقم المعرف:
      edsair.doi.dedup.....a1499f1097e0132538a97d8acd73e471