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      "The contribution of chronic diseases to the prevalence of dependence among older people in Latin America, China and India: a 10/66 Dementia Research Group population-based survey"

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          Abstract

          Background

          The number of older people is set to increase dramatically worldwide. Demographic changes are likely to result in the rise of age-related chronic diseases which largely contribute to years lived with a disability and future dependence. However dependence is much less studied although intrinsically linked to disability. We investigated the prevalence and correlates of dependence among older people from middle income countries.

          Methods

          A one-phase cross-sectional survey was carried out at 11 sites in seven countries (urban sites in Cuba, Venezuela, and Dominican Republic, urban and rural sites in Peru, Mexico, China and India). All those aged 65 years and over living in geographically defined catchment areas were eligible. In all, 15,022 interviews were completed with an informant interview for each participant. The full 10/66 Dementia Research Group survey protocol was applied, including ascertainment of depression, dementia, physical impairments and self-reported diagnoses. Dependence was interviewer-rated based on a key informant's responses to a set of open-ended questions on the participant's needs for care. We estimated the prevalence of dependence and the independent contribution of underlying health conditions. Site-specific prevalence ratios were meta-analysed, and population attributable prevalence fractions (PAPF) calculated.

          Results

          The prevalence of dependence increased with age at all sites, with a tendency for the prevalence to be lower in men than in women. Age-standardised prevalence was lower in all sites than in the USA. Other than in rural China, dementia made the largest independent contribution to dependence, with a median PAPF of 34% (range 23%-59%). Other substantial contributors were limb impairment (9%, 1%-46%), stroke (8%, 2%-17%), and depression (8%, 1%-27%).

          Conclusion

          The demographic and health transitions will lead to large and rapid increases in the numbers of dependent older people particularly in middle income countries (MIC). The prevention and control of chronic neurological and neuropsychiatric diseases and the development of long-term care policies and plans should be urgent priorities.

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          Most cited references31

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          Alzheimer's disease and vascular dementia in developing countries: prevalence, management, and risk factors.

          Despite mortality due to communicable diseases, poverty, and human conflicts, dementia incidence is destined to increase in the developing world in tandem with the ageing population. Current data from developing countries suggest that age-adjusted dementia prevalence estimates in 65 year olds are high (>or=5%) in certain Asian and Latin American countries, but consistently low (1-3%) in India and sub-Saharan Africa; Alzheimer's disease accounts for 60% whereas vascular dementia accounts for approximately 30% of the prevalence. Early-onset familial forms of dementia with single-gene defects occur in Latin America, Asia, and Africa. Illiteracy remains a risk factor for dementia. The APOE epsilon4 allele does not influence dementia progression in sub-Saharan Africans. Vascular factors, such as hypertension and type 2 diabetes, are likely to increase the burden of dementia. Use of traditional diets and medicinal plant extracts might aid prevention and treatment. Dementia costs in developing countries are estimated to be US$73 billion yearly, but care demands social protection, which seems scarce in these regions.
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            Dementia diagnosis in developing countries: a cross-cultural validation study.

            Research into dementia is needed in developing countries. Assessment of variations in disease frequency between regions might enhance our understanding of the disease, but methodological difficulties need to be addressed. We aimed to develop and test a culturally and educationally unbiased diagnostic instrument for dementia. In a multicentre study, the 10/66 Dementia Research Group interviewed 2885 people aged 60 years and older in 25 centres, most in Universities, in India, China and southeast Asia, Latin America and the Caribbean, and Africa. 729 had dementia and three groups were free of dementia: 702 had depression, 694 had high education (as defined by each centre), and 760 had low education (as defined by each centre). Local clinicians diagnosed dementia and depression. An interviewer, masked to dementia diagnosis, administered the geriatric mental state, the community screening instrument for dementia, and the modified Consortium to Establish a Registry of Alzheimer's Disease (CERAD) ten-word list-learning task. Each measure independently predicted a diagnosis of dementia. In an analysis of half the sample, an algorithm derived from all three measures gave better results than any individual measure. Applied to the other half of the sample, this algorithm identified 94% of dementia cases with false-positive rates of 15%, 3%, and 6% in the depression, high education, and low education groups, respectively. Our algorithm is a sound basis for culturally and educationally sensitive dementia diagnosis in clinical and population-based research, supported by translations of its constituent measures into most languages used in the developing world.
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              Predicting nursing home admission in the U.S: a meta-analysis

              Background While existing reviews have identified significant predictors of nursing home admission, this meta-analysis attempted to provide more integrated empirical findings to identify predictors. The present study aimed to generate pooled empirical associations for sociodemographic, functional, cognitive, service use, and informal support indicators that predict nursing home admission among older adults in the U.S. Methods Studies published in English were retrieved by searching the MEDLINE, PSYCINFO, CINAHL, and Digital Dissertations databases using the keywords: "nursing home placement," "nursing home entry," "nursing home admission," and "predictors/institutionalization." Any reports including these key words were retrieved. Bibliographies of retrieved articles were also searched. Selected studies included sampling frames that were nationally- or regionally-representative of the U.S. older population. Results Of 736 relevant reports identified, 77 reports across 12 data sources were included that used longitudinal designs and community-based samples. Information on number of nursing home admissions, length of follow-up, sample characteristics, analysis type, statistical adjustment, and potential risk factors were extracted with standardized protocols. Random effects models were used to separately pool the logistic and Cox regression model results from the individual data sources. Among the strongest predictors of nursing home admission were 3 or more activities of daily living dependencies (summary odds ratio [OR] = 3.25; 95% confidence interval [CI], 2.56–4.09), cognitive impairment (OR = 2.54; CI, 1.44–4.51), and prior nursing home use (OR = 3.47; CI, 1.89–6.37). Conclusion The pooled associations provided detailed empirical information as to which variables emerged as the strongest predictors of NH admission (e.g., 3 or more ADL dependencies, cognitive impairment, prior NH use). These results could be utilized as weights in the construction and validation of prognostic tools to estimate risk for NH entry over a multi-year period.
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                Author and article information

                Journal
                BMC Geriatr
                BMC Geriatrics
                BioMed Central
                1471-2318
                2010
                6 August 2010
                : 10
                : 53
                Affiliations
                [1 ]King's College London, Institute of Psychiatry, Health Services and Population Research Department, Centre for Public Mental Health, De Crespigny Park, Po Box 60, SE5 8AF, London, UK
                [2 ]Universidad Nacional Pedro Henriquez Ureña (UNPHU), Internal Medicine Department, Geriatric Section, Santo Domingo, Dominican Republic
                [3 ]Psychogeriatric Unit, National Institute of Mental Health "Honorio Delgado Hideyo Noguchi", Lima, Peru
                [4 ]Peking University, Institute of Mental Health, Beijing, China
                [5 ]Christian Medical College, Vellore, India
                [6 ]Institute of Community Health, Voluntary Health Services, Chennai, India
                [7 ]Policlinico Universitario 27 de Noviembre, Marianao Ciudad Habana, Cuba
                [8 ]Colegio Dominicano de Estadisticos y Demografos (CODE), Santo Domingo, Dominican Republic
                [9 ]Facultad de Medicina Finlay-Albarran, Medical University of Havana, Havana, Cuba
                [10 ]Medicine Department, Caracas University Hospital, Faculty of Medicine, Universidad Central de Venezuela, Caracas, Venezuela
                [11 ]National Institute of Neurology and Neurosurgery of Mexico, National University Autonomous of Mexico, Mexico City, Mexico
                Article
                1471-2318-10-53
                10.1186/1471-2318-10-53
                2923155
                20691064
                88c02a55-df54-4abd-98c7-e42c80bcc6c9
                Copyright ©2010 Sousa et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 January 2010
                : 6 August 2010
                Categories
                Research Article

                Geriatric medicine
                Geriatric medicine

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