Dataset Information

Contribution of chronic diseases to disability in elderly people in countries with low and middle incomes: a 10/66 Dementia Research Group population-based survey.

ABSTRACT:

Background

Disability in elderly people in countries with low and middle incomes is little studied; according to Global Burden of Disease estimates, visual impairment is the leading contributor to years lived with disability in this population. We aimed to assess the contribution of physical, mental, and cognitive chronic diseases to disability, and the extent to which sociodemographic and health characteristics account for geographical variation in disability.

Methods

We undertook cross-sectional surveys of residents aged older than 65 years (n=15 022) in 11 sites in seven countries with low and middle incomes (China, India, Cuba, Dominican Republic, Venezuela, Mexico, and Peru). Disability was assessed with the 12-item WHO disability assessment schedule 2.0. Dementia, depression, hypertension, and chronic obstructive pulmonary disease were ascertained by clinical assessment; diabetes, stroke, and heart disease by self-reported diagnosis; and sensory, gastrointestinal, skin, limb, and arthritic disorders by self-reported impairment. Independent contributions to disability scores were assessed by zero-inflated negative binomial regression and Poisson regression to generate population-attributable prevalence fractions (PAPF).

Findings

In regions other than rural India and Venezuela, dementia made the largest contribution to disability (median PAPF 25.1% [IQR 19.2-43.6]). Other substantial contributors were stroke (11.4% [1.8-21.4]), limb impairment (10.5% [5.7-33.8]), arthritis (9.9% [3.2-34.8]), depression (8.3% [0.5-23.0]), eyesight problems (6.8% [1.7-17.6]), and gastrointestinal impairments (6.5% [0.3-23.1]). Associations with chronic diseases accounted for around two-thirds of prevalent disability. When zero inflation was taken into account, between-site differences in disability scores were largely attributable to compositional differences in health and sociodemographic characteristics.

Interpretation

On the basis of empirical research, dementia, not blindness, is overwhelmingly the most important independent contributor to disability for elderly people in countries with low and middle incomes. Chronic diseases of the brain and mind deserve increased prioritisation. Besides disability, they lead to dependency and present stressful, complex, long-term challenges to carers. Societal costs are enormous.

Funding

Wellcome Trust; WHO; US Alzheimer's Association; Fondo Nacional de Ciencia Y Tecnologia, Consejo de Desarrollo Cientifico Y Humanistico, Universidad Central de Venezuela.

SUBMITTER: Sousa RM

PROVIDER: S-EPMC2854331 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Contribution of chronic diseases to disability in elderly people in countries with low and middle incomes: a 10/66 Dementia Research Group population-based survey.

Sousa Renata M RM Ferri Cleusa P CP Acosta Daisy D Albanese Emiliano E Guerra Mariella M Huang Yueqin Y Jacob K S KS Jotheeswaran A T AT Rodriguez Juan J Llibre JJ Pichardo Guillermina Rodriguez GR Rodriguez Marina Calvo MC Salas Aquiles A Sosa Ana Luisa AL Williams Joseph J Zuniga Tirso T Prince Martin M

Lancet (London, England) 20091101 9704

<h4>Background</h4>Disability in elderly people in countries with low and middle incomes is little studied; according to Global Burden of Disease estimates, visual impairment is the leading contributor to years lived with disability in this population. We aimed to assess the contribution of physical, mental, and cognitive chronic diseases to disability, and the extent to which sociodemographic and health characteristics account for geographical variation in disability.<h4>Methods</h4>We undertoo ...[more]

PMID: 19944863

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Project description:BackgroundLittle is known of the epidemiology of diabetes among older people in low and middle income countries. We aimed to study and compare prevalence, social patterning, correlates, detection, treatment and control of diabetes among older people in Latin America, India, China and Nigeria.MethodsCross-sectional surveys in 13 catchment area sites in nine countries. Diagnosed diabetes was assessed in all sites through self-reported diagnosis. Undiagnosed diabetes was assessed in seven Latin American sites through fasting blood samples (glucose > = 7 mmol/L).ResultsTotal diabetes prevalence in catchment sites in Cuba (prevalence 24.2%, SMR 116), Puerto Rico (43.4%, 197), and urban (27.0%, 125), and rural Mexico (23.7%, 111) already exceeds that in the USA, while that in Venezuela (20.9%, 100) is similar. Diagnosed diabetes prevalence varied very widely, between low prevalences in sites in rural China (0.9%), rural India (6.6%) and Nigeria (6.0%). and 32.1% in Puerto Rico, explained mainly by access to health services. Treatment coverage varied substantially between sites. Diabetes control (40 to 61% of those diagnosed) was modest in the Latin American sites where this was studied. Diabetes was independently associated with less education, but more assets. Hypertension, central obesity and hypertriglyceridaemia, but not hypercholesterolaemia were consistently associated with total diabetes.ConclusionsDiabetes prevalence is already high in most sites. Identifying undiagnosed cases is essential to quantify population burden, particularly in least developed settings where diagnosis is uncommon. Metabolic risk factors and associated lifestyles may play an important part in aetiology, but this requires confirmation with longitudinal data. Given the high prevalence among older people, more population research is indicated to quantify the impact of diabetes, and to monitor the effect of prevention and health system strengthening on prevalence, treatment and control.

Project description:To develop and evaluate a short version of the 10/66 dementia diagnostic schedule for use in low-income and middle-income countries.Split-half analysis for algorithm development and testing; cross-evaluation of short-schedule and standard-schedule algorithms in 12 community surveys.(1) The 10/66 pilot sample data set of people aged 60 years and over in 25 international centres each recruiting the following samples: (a) dementia; (b) depression, no dementia; (c) no dementia, high education and (d) no dementia, low education. (2) Cross-sectional surveys of people aged 65 years or more from 12 urban and rural sites in 8 countries (Cuba, Dominican Republic, Peru, Mexico, Venezuela, India, China and Puerto Rico).In the 10/66 pilot samples, the algorithm for the short schedule was developed in 1218 participants and tested in 1211 randomly selected participants; it was evaluated against the algorithm for the standard 10/66 schedule in 16 536 survey participants.The short diagnostic schedule was derived from the Community Screening Instrument for Dementia, the CERAD 10-word list recall task and the Euro-D depression screen; it was evaluated against clinically assigned groups in the pilot data and against the standard schedule (using the Geriatric Mental State (GMS) rather than Euro-D) in the surveys.In the pilot test sample, the short-schedule algorithm ascertained dementia with 94.2% sensitivity. Specificities were 80.2% in depression, 96.6% in the high-education group and 92.7% in the low-education group. In survey samples, it coincided with standard algorithm dementia classifications with over 95% accuracy in most sites. Estimated dementia prevalences in the survey samples were not consistently higher or lower using the short compared to standard schedule.For epidemiological studies of dementia in low-income and middle-income settings where the GMS interview (and/or interviewer training required) is not feasible, the short 10/66 schedule and algorithm provide an alternative with acceptable levels of performance.

Project description:Results of the few cohort studies from countries with low incomes or middle incomes suggest a lower incidence of dementia than in high-income countries. We assessed incidence of dementia according to criteria from the 10/66 Dementia Research Group and Diagnostic and Statistical Manual of Mental Disorders (DSM) IV, the effect of dementia at baseline on mortality, and the independent effects of age, sex, socioeconomic position, and indicators of cognitive reserve.We did a population-based cohort study of all people aged 65 years and older living in urban sites in Cuba, the Dominican Republic, and Venezuela, and rural and urban sites in Peru, Mexico, and China, with ascertainment of incident 10/66 and DSM-IV dementia 3-5 years after cohort inception. We used questionnaires to obtain information about age in years, sex, educational level, literacy, occupational attainment, and number of household assets. We obtained information about mortality from all sites. For participants who had died, we interviewed a friend or relative to ascertain the likelihood that they had dementia before death.12,887 participants were interviewed at baseline. 11,718 were free of dementia, of whom 8137 (69%) were reinterviewed, contributing 34,718 person-years of follow-up. Incidence for 10/66 dementia varied between 18·2 and 30·4 per 1000 person-years, and were 1·4-2·7 times higher than were those for DSM-IV dementia (9·9-15·7 per 1000 person-years). Mortality hazards were 1·56-5·69 times higher in individuals with dementia at baseline than in those who were dementia-free. Informant reports suggested a high incidence of dementia before death; overall incidence might be 4-19% higher if these data were included. 10/66 dementia incidence was independently associated with increased age (HR 1·67; 95% CI 1·56-1·79), female sex (0·72; 0·61-0·84), and low education (0·89; 0·81-0·97), but not with occupational attainment (1·04; 0·95-1·13).Our results provide supportive evidence for the cognitive reserve hypothesis, showing that in middle-income countries as in high-income countries, education, literacy, verbal fluency, and motor sequencing confer substantial protection against the onset of dementia.Wellcome Trust Health Consequences of Population Change Programme, WHO, US Alzheimer's Association, FONACIT/ CDCH/ UCV.

Project description:BackgroundTo date, dementia prediction models have been exclusively developed and tested in high-income countries (HICs). However, most people with dementia live in low-income and middle-income countries (LMICs), where dementia risk prediction research is almost non-existent and the ability of current models to predict dementia is unknown. This study investigated whether dementia prediction models developed in HICs are applicable to LMICs.MethodsData were from the 10/66 Study. Individuals aged 65 years or older and without dementia at baseline were selected from China, Cuba, the Dominican Republic, Mexico, Peru, Puerto Rico, and Venezuela. Dementia incidence was assessed over 3-5 years, with diagnosis according to the 10/66 Study diagnostic algorithm. Discrimination and calibration were tested for five models: the Cardiovascular Risk Factors, Aging and Dementia risk score (CAIDE); the Study on Aging, Cognition and Dementia (AgeCoDe) model; the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI); the Brief Dementia Screening Indicator (BDSI); and the Rotterdam Study Basic Dementia Risk Model (BDRM). Models were tested with use of Cox regression. The discriminative accuracy of each model was assessed using Harrell's concordance (c)-statistic, with a value of 0·70 or higher considered to indicate acceptable discriminative ability. Calibration (model fit) was assessed statistically using the Grønnesby and Borgan test.Findings11 143 individuals without baseline dementia and with available follow-up data were included in the analysis. During follow-up (mean 3·8 years [SD 1·3]), 1069 people progressed to dementia across all sites (incidence rate 24·9 cases per 1000 person-years). Performance of the models varied. Across countries, the discriminative ability of the CAIDE (0·52≤c≤0·63) and AgeCoDe (0·57≤c≤0·74) models was poor. By contrast, the ANU-ADRI (0·66≤c≤0·78), BDSI (0·62≤c≤0·78), and BDRM (0·66≤c≤0·78) models showed similar levels of discriminative ability to those of the development cohorts. All models showed good calibration, especially at low and intermediate levels of predicted risk. The models validated best in Peru and poorest in the Dominican Republic and China.InterpretationNot all dementia prediction models developed in HICs can be simply extrapolated to LMICs. Further work defining what number and which combination of risk variables works best for predicting risk of dementia in LMICs is needed. However, models that transport well could be used immediately for dementia prevention research and targeted risk reduction in LMICs.FundingNational Institute for Health Research, Wellcome Trust, WHO, US Alzheimer's Association, and European Research Council.

Dataset Information

Contribution of chronic diseases to disability in elderly people in countries with low and middle incomes: a 10/66 Dementia Research Group population-based survey.

Background

Methods

Findings

Interpretation

Funding

Publications

Contribution of chronic diseases to disability in elderly people in countries with low and middle incomes: a 10/66 Dementia Research Group population-based survey.

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