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

Cohort Studies of Memory in an International Consortium (COSMIC)

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Article numbere1002853
JournalPLoS Medicine
Volume16
Issue number7
DOIs
StatePublished - Jul 2019

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Cohort Studies
Apolipoproteins E
Smoking
Stroke
Alleles
Exercise
Dementia
Depression
Blood Pressure
Education
Intelligence Tests
Sex Education
Peripheral Vascular Diseases
Alcohol Drinking
Atrial Fibrillation
Cognition
Meta-Analysis
Cognitive Dysfunction
Linear Models
Body Mass Index

ASJC Scopus subject areas

  • Medicine(all)

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Determinants of cognitive performance and decline in 20 diverse ethno-regional groups : A COSMIC collaboration cohort study. / Cohort Studies of Memory in an International Consortium (COSMIC).

In: PLoS Medicine, Vol. 16, No. 7, e1002853, 07.2019.

Research output: Contribution to journalArticle

Cohort Studies of Memory in an International Consortium (COSMIC). / Determinants of cognitive performance and decline in 20 diverse ethno-regional groups : A COSMIC collaboration cohort study. In: PLoS Medicine. 2019 ; Vol. 16, No. 7.
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title = "Determinants of cognitive performance and decline in 20 diverse ethno-regional groups: A COSMIC collaboration cohort study",
abstract = "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.",
author = "{Cohort Studies of Memory in an International Consortium (COSMIC)} and Lipnicki, {Darren M.} and Makkar, {Steve R.} and Crawford, {John D.} and Anbupalam Thalamuthu and Kochan, {Nicole A.} and Lima-Costa, {Maria Fernanda} and Erico Castro-Costa and Ferri, {Cleusa Pinheiro} and Carol Brayne and Blossom Stephan and Llibre-Rodriguez, {Juan J.} and Llibre-Guerra, {Jorge J.} and Valhuerdi-Cepero, {Adolfo J.} and Lipton, {Richard B.} and Katz, {Mindy J.} and Derby, {Carol A.} and Karen Ritchie and Ancelin, {Marie Laure} and Isabelle Carri{\`e}re and Nikolaos Scarmeas and Mary Yannakoulia and Hadjigeorgiou, {Georgios M.} and Linda Lam and Chan, {Wai Chi} and Ada Fung and Antonio Guaita and Roberta Vaccaro and Annalisa Davin and Kim, {Ki Woong} and Han, {Ji Won} and Suh, {Seung Wan} and Riedel-Heller, {Steffi G.} and Susanne Roehr and Alexander Pabst and {van Boxtel}, Martin and Sebastian K{\"o}hler and Kay Deckers and Mary Ganguli and Jacobsen, {Erin P.} and Hughes, {Tiffany F.} and Anstey, {Kaarin J.} and Nicolas Cherbuin and Haan, {Mary N.} and Aiello, {Allison E.} and Kristina Dang and Shuzo Kumagai and Tao Chen and Kenji Narazaki and Ng, {Tze Pin} and Qi Gao",
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TY - JOUR

T1 - Determinants of cognitive performance and decline in 20 diverse ethno-regional groups

T2 - A COSMIC collaboration cohort study

AU - Cohort Studies of Memory in an International Consortium (COSMIC)

AU - Lipnicki, Darren M.

AU - Makkar, Steve R.

AU - Crawford, John D.

AU - Thalamuthu, Anbupalam

AU - Kochan, Nicole A.

AU - Lima-Costa, Maria Fernanda

AU - Castro-Costa, Erico

AU - Ferri, Cleusa Pinheiro

AU - Brayne, Carol

AU - Stephan, Blossom

AU - Llibre-Rodriguez, Juan J.

AU - Llibre-Guerra, Jorge J.

AU - Valhuerdi-Cepero, Adolfo J.

AU - Lipton, Richard B.

AU - Katz, Mindy J.

AU - Derby, Carol A.

AU - Ritchie, Karen

AU - Ancelin, Marie Laure

AU - Carrière, Isabelle

AU - Scarmeas, Nikolaos

AU - Yannakoulia, Mary

AU - Hadjigeorgiou, Georgios M.

AU - Lam, Linda

AU - Chan, Wai Chi

AU - Fung, Ada

AU - Guaita, Antonio

AU - Vaccaro, Roberta

AU - Davin, Annalisa

AU - Kim, Ki Woong

AU - Han, Ji Won

AU - Suh, Seung Wan

AU - Riedel-Heller, Steffi G.

AU - Roehr, Susanne

AU - Pabst, Alexander

AU - van Boxtel, Martin

AU - Köhler, Sebastian

AU - Deckers, Kay

AU - Ganguli, Mary

AU - Jacobsen, Erin P.

AU - Hughes, Tiffany F.

AU - Anstey, Kaarin J.

AU - Cherbuin, Nicolas

AU - Haan, Mary N.

AU - Aiello, Allison E.

AU - Dang, Kristina

AU - Kumagai, Shuzo

AU - Chen, Tao

AU - Narazaki, Kenji

AU - Ng, Tze Pin

AU - Gao, Qi

PY - 2019/7

Y1 - 2019/7

N2 - 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.

AB - 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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U2 - 10.1371/journal.pmed.1002853

DO - 10.1371/journal.pmed.1002853

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C2 - 31335910

AN - SCOPUS:85070472369

VL - 16

JO - PLoS Medicine

JF - PLoS Medicine

SN - 1549-1277

IS - 7

M1 - e1002853

ER -