Prevalence, Distribution, and Impact of Mild Cognitive Impairment in Latin America, China, and India: A 10/66 Population-Based Study
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{"title"=>"Prevalence, Distribution, and Impact of Mild Cognitive Impairment in Latin America, China, and India: A 10/66 Population-Based Study", "type"=>"journal", "authors"=>[{"first_name"=>"Ana Luisa", "last_name"=>"Sosa"}, {"first_name"=>"Emiliano", "last_name"=>"Albanese"}, {"first_name"=>"Blossom C. M.", "last_name"=>"Stephan"}, {"first_name"=>"Michael", "last_name"=>"Dewey"}, {"first_name"=>"Daisy", "last_name"=>"Acosta"}, {"first_name"=>"Cleusa P.", "last_name"=>"Ferri"}, {"first_name"=>"Mariella", "last_name"=>"Guerra"}, {"first_name"=>"Yueqin", "last_name"=>"Huang"}, {"first_name"=>"K. S.", "last_name"=>"Jacob"}, {"first_name"=>"Ivonne Z.", "last_name"=>"Jiménez-Velázquez"}, {"first_name"=>"Juan J.", "last_name"=>"Llibre Rodriguez"}, {"first_name"=>"Aquiles", "last_name"=>"Salas"}, {"first_name"=>"Joseph", "last_name"=>"Williams"}, {"first_name"=>"Isaac", "last_name"=>"Acosta"}, {"first_name"=>"Maribella", "last_name"=>"González-Viruet"}, {"first_name"=>"Milagros A.", "last_name"=>"Guerra Hernandez"}, {"first_name"=>"Li", "last_name"=>"Shuran"}, {"first_name"=>"Martin J.", "last_name"=>"Prince"}, {"first_name"=>"Robert", "last_name"=>"Stewart"}], "year"=>2012, "source"=>"PLoS Medicine", "identifiers"=>{"doi"=>"10.1371/journal.pmed.1001170", "issn"=>"1549-1676", "isbn"=>"1549-1676 (Electronic)\\r1549-1277 (Linking)", "pmid"=>"22346736"}, "id"=>"26cf0403-44b8-37cb-a54e-56474580fbb9", "abstract"=>"BACKGROUND: Rapid demographic ageing is a growing public health issue in many low- and middle-income countries (LAMICs). Mild cognitive impairment (MCI) is a construct frequently used to define groups of people who may be at risk of developing dementia, crucial for targeting preventative interventions. However, little is known about the prevalence or impact of MCI in LAMIC settings. METHODS AND FINDINGS: Data were analysed from cross-sectional surveys established by the 10/66 Dementia Research Group and carried out in Cuba, Dominican Republic, Peru, Mexico, Venezuela, Puerto Rico, China, and India on 15,376 individuals aged 65+ without dementia. Standardised assessments of mental and physical health, and cognitive function were carried out including informant interviews. An algorithm was developed to define Mayo Clinic amnestic MCI (aMCI). Disability (12-item World Health Organization disability assessment schedule [WHODAS]) and informant-reported neuropsychiatric symptoms (neuropsychiatric inventory [NPI-Q]) were measured. After adjustment, aMCI was associated with disability, anxiety, apathy, and irritability (but not depression); between-country heterogeneity in these associations was only significant for disability. The crude prevalence of aMCI ranged from 0.8% in China to 4.3% in India. Country differences changed little (range 0.6%-4.6%) after standardization for age, gender, and education level. In pooled estimates, aMCI was modestly associated with male gender and fewer assets but was not associated with age or education. There was no significant between-country variation in these demographic associations. CONCLUSIONS: An algorithm-derived diagnosis of aMCI showed few sociodemographic associations but was consistently associated with higher disability and neuropsychiatric symptoms in addition to showing substantial variation in prevalence across LAMIC populations. Longitudinal data are needed to confirm findings-in particular, to investigate the predictive validity of aMCI in these settings and risk/protective factors for progression to dementia; however, the large number affected has important implications in these rapidly ageing settings.", "link"=>"http://www.mendeley.com/research/prevalence-distribution-impact-mild-cognitive-impairment-latin-america-china-india-1066-populationba-2", "reader_count"=>114, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>7, "Researcher"=>22, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>23, "Student > Postgraduate"=>11, "Student > Master"=>16, "Other"=>5, "Student > Bachelor"=>7, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>7, "Researcher"=>22, "Student > Doctoral Student"=>10, "Student > Ph. D. Student"=>23, "Student > Postgraduate"=>11, "Student > Master"=>16, "Other"=>5, "Student > Bachelor"=>7, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>16, "Agricultural and Biological Sciences"=>11, "Arts and Humanities"=>1, "Computer Science"=>1, "Decision Sciences"=>2, "Engineering"=>1, "Nursing and Health Professions"=>3, "Medicine and Dentistry"=>50, "Neuroscience"=>2, "Sports and Recreations"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Psychology"=>19, "Social Sciences"=>4, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>50}, "Social Sciences"=>{"Social Sciences"=>4}, "Decision Sciences"=>{"Decision Sciences"=>2}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Psychology"=>{"Psychology"=>19}, "Unspecified"=>{"Unspecified"=>16}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>1}, "Neuroscience"=>{"Neuroscience"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>11}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}}, "reader_count_by_country"=>{"Lebanon"=>1, "Colombia"=>1, "Venezuela"=>1, "Puerto Rico"=>1, "United States"=>1, "Ireland"=>1, "Mexico"=>2, "United Kingdom"=>1, "India"=>2, "Spain"=>1}, "group_count"=>8}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/684995"], "description"=>"<p>MV, missing values; NPI-Q severity: total severity in neuro-psychiatric inventory.</p>", "links"=>[], "tags"=>["characteristics"], "article_id"=>355461, "categories"=>["Mental Health", "Biotechnology", "Neuroscience"], "users"=>["Ana Luisa Sosa", "Emiliano Albanese", "Blossom C. M. Stephan", "Michael Dewey", "Daisy Acosta", "Cleusa P. Ferri", "Mariella Guerra", "Yueqin Huang", "K. S. Jacob", "Ivonne Z. Jiménez-Velázquez", "Juan J. Llibre Rodriguez", "Aquiles Salas", "Joseph Williams", "Isaac Acosta", "Maribella González-Viruet", "Milagros A. Guerra Hernandez", "Li Shuran", "Martin J. Prince", "Robert Stewart"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001170.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sociodemographic_characteristics_of_participants_by_country_/355461", "title"=>"Sociodemographic characteristics of participants by country.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 09:15:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/685063"], "description"=>"<p><b>Association between aMCI and disability</b> is measured by exponentiated coefficients from a zero inflated binomial model and representing the increase in disability of aMCI participants compared to normal. Zero inflation fitted using age, gender, educational level, number of household assets, depression, arthritis, visual problems, hearing problems, cough and breathing problems, heart problems, gastrointestinal problems, fainting, limb and skin problems, hypertension and stroke. <b>The association between aMCI and neuropsychiatric symptomsis</b> measured by the risk ratio from a regression using a Poisson working model and model robust standard errors, and representing the risk for having the symptom in aMCI participants compared to normal.</p>a<p>Adjusted for age, gender, and educational level, number of household assets and of physical limiting impairments, psychosis, and stroke.</p>b<p>Depression and irritability were additionally adjusted for pain. The four NPI–Q symptoms are all associated but in the four models presented in the table we have not adjusted each of them for the other three.</p>c<p>China was not adjusted for psychosis</p>d<p>The pooled fixed-effect model meta-analytical estimate for depression and anxiety were done without China.</p><p>NC, not calculable due to zero cell sizes.</p>", "links"=>[], "tags"=>["amci", "neuropsychiatric", "symptoms"], "article_id"=>355527, "categories"=>["Mental Health", "Biotechnology", "Neuroscience"], "users"=>["Ana Luisa Sosa", "Emiliano Albanese", "Blossom C. M. Stephan", "Michael Dewey", "Daisy Acosta", "Cleusa P. Ferri", "Mariella Guerra", "Yueqin Huang", "K. S. Jacob", "Ivonne Z. Jiménez-Velázquez", "Juan J. Llibre Rodriguez", "Aquiles Salas", "Joseph Williams", "Isaac Acosta", "Maribella González-Viruet", "Milagros A. Guerra Hernandez", "Li Shuran", "Martin J. Prince", "Robert Stewart"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001170.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_aMCI_and_disability_WHODAS_12_and_the_association_between_aMCI_and_neuropsychiatric_symptoms_NPI_8211_Q_depression_anxiety_apathy_and_irritability_/355527", "title"=>"Association between aMCI and disability (WHODAS-12), and the association between aMCI and neuropsychiatric symptoms (NPI–Q; depression, anxiety, apathy, and irritability).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 09:15:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/685116"], "description"=>"a<p>Direct standardization for age gender and educational level using the whole sample as the standard population.</p>", "links"=>[], "tags"=>["amci"], "article_id"=>355586, "categories"=>["Mental Health", "Biotechnology", "Neuroscience"], "users"=>["Ana Luisa Sosa", "Emiliano Albanese", "Blossom C. M. Stephan", "Michael Dewey", "Daisy Acosta", "Cleusa P. Ferri", "Mariella Guerra", "Yueqin Huang", "K. S. Jacob", "Ivonne Z. Jiménez-Velázquez", "Juan J. Llibre Rodriguez", "Aquiles Salas", "Joseph Williams", "Isaac Acosta", "Maribella González-Viruet", "Milagros A. Guerra Hernandez", "Li Shuran", "Martin J. Prince", "Robert Stewart"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001170.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prevalence_of_aMCI_by_country_gender_and_age_group_/355586", "title"=>"Prevalence of aMCI by country, gender, and age group.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 09:15:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/685175"], "description"=>"a<p>Mutually adjusted for age, educational level, gender, and number of assets as appropriate.</p>", "links"=>[], "tags"=>["adjusted", "assets", "amci"], "article_id"=>355639, "categories"=>["Mental Health", "Biotechnology", "Neuroscience"], "users"=>["Ana Luisa Sosa", "Emiliano Albanese", "Blossom C. M. Stephan", "Michael Dewey", "Daisy Acosta", "Cleusa P. Ferri", "Mariella Guerra", "Yueqin Huang", "K. S. Jacob", "Ivonne Z. Jiménez-Velázquez", "Juan J. Llibre Rodriguez", "Aquiles Salas", "Joseph Williams", "Isaac Acosta", "Maribella González-Viruet", "Milagros A. Guerra Hernandez", "Li Shuran", "Martin J. Prince", "Robert Stewart"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001170.t004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mutually_adjusted_95_CI_for_the_independent_effects_of_age_gender_education_and_assets_on_aMCI_prevalence_/355639", "title"=>"Mutually adjusted (95% CI) for the independent effects of age, gender, education, and assets on aMCI prevalence.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 09:16:03"}

PMC Usage Stats | Further Information

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Relative Metric

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