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Healthy ageing and the prediction of mortality and incidence dependence in low- and middle- income countries: a 10/66 population-based cohort study.

ABSTRACT: BACKGROUND:In the absence of a consensus on definition and measurement of healthy ageing, we created a healthy ageing index tallying with the functional ability framework provided by the World Health Organization. To create this index, we employed items of functional ability and intrinsic capacity. The current study aims to establish the predictive validity and discrimination properties of this healthy ageing index in settings in Latin American, part of the 10/66 cohort. METHODS:Population-based cohort studies including 12,865 people ?65?years old in catchment areas of Cuba, Dominican Republic, Venezuela, Mexico and Peru. We employed latent variable modelling to estimate the healthy ageing scores of each participant. We grouped participants according to the quintiles of the healthy ageing score distribution. Cox's proportional hazard models for mortality and sub-hazard (competing risks) models for incident dependence (i.e. needing care) were calculated per area after a median of 3.9?years and 3.7?years, respectively. Results were pooled together via fixed-effects meta-analysis. Our findings were compared with those obtained from self-rated health. RESULTS:Participants with lowest levels, compared to participants with highest level of healthy ageing, had increased risk of mortality and incident dependence, even after adjusting for sociodemographic and health conditions (HR: 3.25, 95%CI: 2.63-4.02; sub-HR: 5.21, 95%CI: 4.02-6.75). Healthy ageing scores compared to self-rated health had higher population attributable fractions (PAFs) for mortality (43.6% vs 19.3%) and incident dependence (58.6% vs 17.0%), and better discriminative power (Harrell's c-statistic: mortality 0.74 vs 0.72; incident dependence 0.76 vs 0.70). CONCLUSION:These results provide evidence that our healthy ageing index could be a valuable tool for prevention strategies as it demonstrated predictive and discriminative properties. Further research in other cultural settings will assist moving from a theoretical conceptualisation of healthy ageing to a more practical one.

SUBMITTER: Daskalopoulou C

PROVIDER: S-EPMC6894213 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Healthy ageing and the prediction of mortality and incidence dependence in low- and middle- income countries: a 10/66 population-based cohort study.

Daskalopoulou Christina C Prince Martin M Koukounari Artemis A Haro Josep Maria JM Panagiotakos Demosthenes B DB Prina A Matthew AM

BMC medical research methodology 20191205 1

<h4>Background</h4>In the absence of a consensus on definition and measurement of healthy ageing, we created a healthy ageing index tallying with the functional ability framework provided by the World Health Organization. To create this index, we employed items of functional ability and intrinsic capacity. The current study aims to establish the predictive validity and discrimination properties of this healthy ageing index in settings in Latin American, part of the 10/66 cohort.<h4>Methods</h4>P ...[more]

PMID: 31801461

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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.

Project description:BackgroundOur population is ageing and in 2050 more than one out of five people will be 60 years or older; 80% of whom will be living in a low-and-middle income country. Living longer does not entail living healthier; however, there is not a widely accepted measure of healthy ageing hampering policy and research. The World Health Organization defines healthy ageing as the process of developing and maintaining functional ability that will enable well-being in older age. We aimed to create a healthy ageing index (HAI) in a subset of six low-and-middle income countries, part of the 10/66 study, by using items of functional ability and intrinsic capacity.MethodsThe study sample included residents 65-years old and over (n = 12,865) from catchment area sites in Cuba, Dominican Republic, Peru, Venezuela, Mexico and Puerto Rico. Items were collected by interviewing participants or key informants between 2003 and 2010. Two-stage factor analysis was employed and we compared one-factor, second-order and bifactor models. The psychometric properties of the index, including reliability, replicability, unidimensionality and concurrent convergent validity as well as measurement invariance per ethnic group and gender were further examined in the best fit model.ResultsThe bifactor model displayed superior model fit statistics supporting that a general factor underlies the various items but other subdomain factors are also needed. The HAI indicated excellent reliability (ω = 0.96, ωΗ = 0.84), replicability (H = 0.96), some support for unidimensionality (Explained Common Variance = 0.65) and some concurrent convergent validity with self-rated health. Scalar measurement invariance per ethnic group and gender was supported.ConclusionsA HAI with excellent psychometric properties was created by using items of functional ability and intrinsic capacity in a subset of six low-and-middle income countries. Further research is needed to explore sub-population differences and to validate this index to other cultural settings.

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.

Dataset Information

Healthy ageing and the prediction of mortality and incidence dependence in low- and middle- income countries: a 10/66 population-based cohort study.

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Healthy ageing and the prediction of mortality and incidence dependence in low- and middle- income countries: a 10/66 population-based cohort study.

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