Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study
Darren Lipnicki
(1)
,
Steve R Makkar
(1)
,
John D. Crawford
(1)
,
Anbupalam Thalamuthu
(1)
,
Nicole Kochan
(1)
,
Maria Fernanda Lima-Costa
(2)
,
Erico Castro-Costa
(2)
,
Cleusa Pinheiro Ferri
(3)
,
Carol Brayne
(4)
,
Blossom Stephan
(5)
,
Juan J Llibre-Rodriguez
(6)
,
Jorge Llibre-Guerra
(7)
,
Adolfo J Valhuerdi-Cepero
(8)
,
Richard Lipton
(9)
,
Mindy Katz
(9)
,
Carol Derby
(9)
,
Karen A. Ritchie
(10, 11, 12)
,
Marie-Laure Ancelin
(10, 11)
,
Isabelle Carrière
(10, 11)
,
Nikolaos Scarmeas
(13, 14)
,
Mary Yannakoulia
(15)
,
Georgios M. Hadjigeorgiou
(16)
,
Linda Lam
(17)
,
Wai-Chi Chan
(18)
,
Ada Fung
(19)
,
Antonio Guaita
,
Roberta Vaccaro
,
Annalisa Davin
,
Ki Woong Kim
(20)
,
Ji Won Han
(20)
,
Seung Wan Suh
(20)
,
Steffi Riedel-Heller
(21)
,
Susanne Roehr
(21)
,
Alexander Pabst
(21)
,
Martin van Boxtel
(22)
,
Sebastian Köhler
(22)
,
Kay Deckers
(22)
,
Mary Ganguli
(23)
,
Erin Jacobsen
(23)
,
Tiffany Hughes
(24)
,
Kaarin Anstey
(1, 25)
,
Nicolas Cherbuin
(25)
,
Mary Haan
(7)
,
Allison Aiello
(26)
,
Kristina Dang
(7)
,
Shuzo Kumagai
(27)
,
Tao Chen
(27)
,
Kenji Narazaki
(28)
,
Tze Pin Ng
(29)
,
Qi Gao
(29)
,
Ma Shwe Zin Nyunt
(29)
,
Marcia Scazufca
(30)
,
Henry Brodaty
(1)
,
Katya Numbers
(1)
,
Julian N Trollor
(1)
,
Kenichi Meguro
(31)
,
Satoshi Yamaguchi
(31)
,
Hiroshi Ishii
(31)
,
Antonio Lobo
(32, 33)
,
Raúl Lopez-Anton
(32, 33)
,
Javier Santabárbara
(32, 33)
,
Yvonne Leung
(1)
,
Jessica Lo
(1)
,
Gordana Popovic
(1)
,
Perminder Sachdev
(1)
1
UNSW -
University of New South Wales [Sydney]
2 FIOCRUZ - Fundação Oswaldo Cruz / Oswaldo Cruz Foundation
3 Unifesp - Federal University of Sao Paulo
4 CAM - University of Cambridge [UK]
5 Newcastle University [Newcastle]
6 UH - University of Havana (Universidad de la Habana)
7 UC - University of California
8 Universidad de Matanzas
9 Albert Einstein College of Medicine [New York]
10 PSNREC - Neuropsychiatrie : recherche épidémiologique et clinique
11 CHRU Montpellier - Centre Hospitalier Régional Universitaire [Montpellier]
12 Edin. - University of Edinburgh
13 NKUA - National and Kapodistrian University of Athens
14 Columbia University [New York]
15 Harokopio University of Athens
16 UCY - University of Cyprus [Nicosia]
17 CUHK - The Chinese University of Hong Kong [Hong Kong]
18 HKU - The University of Hong Kong
19 POLYU - The Hong Kong Polytechnic University [Hong Kong]
20 SNU - Seoul National University [Seoul]
21 Leipzig University / Universität Leipzig
22 MUMC - Maastricht University Medical Centre
23 University of Pittsburgh School of Medicine
24 YSU - Youngstown State University
25 ANU - Australian National University
26 UNC - University of North Carolina [Chapel Hill]
27 Kyushu University
28 FIT - Fukuoka Institute of Technology
29 NUS - National University of Singapore
30 USP - Universidade de São Paulo = University of São Paulo
31 Tohoku University [Sendai]
32 CIBER-SAM - Centro de Investigación Biomédica en Red Salud Mental [Madrid]
33 Universidad de Zaragoza = University of Zaragoza [Saragossa University] = Université de Saragosse
2 FIOCRUZ - Fundação Oswaldo Cruz / Oswaldo Cruz Foundation
3 Unifesp - Federal University of Sao Paulo
4 CAM - University of Cambridge [UK]
5 Newcastle University [Newcastle]
6 UH - University of Havana (Universidad de la Habana)
7 UC - University of California
8 Universidad de Matanzas
9 Albert Einstein College of Medicine [New York]
10 PSNREC - Neuropsychiatrie : recherche épidémiologique et clinique
11 CHRU Montpellier - Centre Hospitalier Régional Universitaire [Montpellier]
12 Edin. - University of Edinburgh
13 NKUA - National and Kapodistrian University of Athens
14 Columbia University [New York]
15 Harokopio University of Athens
16 UCY - University of Cyprus [Nicosia]
17 CUHK - The Chinese University of Hong Kong [Hong Kong]
18 HKU - The University of Hong Kong
19 POLYU - The Hong Kong Polytechnic University [Hong Kong]
20 SNU - Seoul National University [Seoul]
21 Leipzig University / Universität Leipzig
22 MUMC - Maastricht University Medical Centre
23 University of Pittsburgh School of Medicine
24 YSU - Youngstown State University
25 ANU - Australian National University
26 UNC - University of North Carolina [Chapel Hill]
27 Kyushu University
28 FIT - Fukuoka Institute of Technology
29 NUS - National University of Singapore
30 USP - Universidade de São Paulo = University of São Paulo
31 Tohoku University [Sendai]
32 CIBER-SAM - Centro de Investigación Biomédica en Red Salud Mental [Madrid]
33 Universidad de Zaragoza = University of Zaragoza [Saragossa University] = Université de Saragosse
Darren Lipnicki
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- PersonId : 948379
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Erico Castro-Costa
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- PersonId : 798923
- ORCID : 0000-0003-0792-5439
Blossom Stephan
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- PersonId : 778033
- ORCID : 0000-0002-1235-360X
Marie-Laure Ancelin
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- PersonId : 181466
- IdHAL : marie-laure-ancelin
- ORCID : 0000-0002-1149-4320
- IdRef : 031912168
Isabelle Carrière
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Nikolaos Scarmeas
- Fonction : Auteur
- PersonId : 761369
- ORCID : 0000-0001-6453-8908
Antonio Guaita
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Roberta Vaccaro
- Fonction : Auteur
Annalisa Davin
- Fonction : Auteur
Ji Won Han
- Fonction : Auteur
- PersonId : 798924
- ORCID : 0000-0003-2418-4257
Alexander Pabst
- Fonction : Auteur
- PersonId : 794546
- ORCID : 0000-0003-0432-5681
Kaarin Anstey
- Fonction : Auteur
- PersonId : 948406
Tze Pin Ng
- Fonction : Auteur
- PersonId : 798951
- ORCID : 0000-0001-9585-855X
Yvonne Leung
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- PersonId : 798952
- ORCID : 0000-0001-9110-7054
Perminder Sachdev
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Résumé
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.
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