SummaryBackgroundStudies have suggested that the prevalence of dementia is lower in developing than in developed regions. We investigated the prevalence and severity of dementia in sites in low-income and middle-income countries according to two definitions of dementia diagnosis.MethodsWe undertook one-phase cross-sectional surveys of all residents aged 65 years and older (n=14 960) in 11 sites in seven low-income and middle-income countries (China, India, Cuba, Dominican Republic, Venezuela, Mexico, and Peru). Dementia diagnosis was made according to the culturally and educationally sensitive 10/66 dementia diagnostic algorithm, which had been prevalidated in 25 Latin American, Asian, and African centres; and by computerised application of the dementia criterion from the Diagnostic and Statistical Manual of Mental Disorders (DSM IV). We also compared prevalence of DSM-IV dementia in each of the study sites with that from estimates in European studies.FindingsThe prevalence of DSM-IV dementia varied widely, from 0·3% (95% CI 0·1–0·5) in rural India to 6·3% (5·0–7·7) in Cuba. After standardisation for age and sex, DSM-IV prevalence in urban Latin American sites was four-fifths of that in Europe (standardised morbidity ratio 80 [95% CI 70–91]), but in China the prevalence was only half (56 [32–91] in rural China), and in India and rural Latin America a quarter or less of the European prevalence (18 [5–34] in rural India). 10/66 dementia prevalence was higher than that of DSM-IV dementia, and more consistent across sites, varying between 5·6% (95% CI 4·2–7·0) in rural China and 11·7% (10·3–13·1) in the Dominican Republic. The validity of the 847 of 1345 cases of 10/66 dementia not confirmed by DSM-IV was supported by high levels of associated disability (mean WHO Disability Assessment Schedule II score 33·7 [SD 28·6]).InterpretationAs compared with the 10/66 dementia algorithm, the DSM-IV dementia criterion might underestimate dementia prevalence, especially in regions with low awareness of this emerging public-health problem.FundingWellcome Trust (UK); WHO; the US Alzheimer's Association; and Fondo Nacional De Ciencia Y Tecnologia, Consejo De Desarrollo Cientifico Y Humanistico, and Universidad Central De Venezuela (Venezuela).

SummaryBackgroundResults 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.MethodsWe 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.Findings12 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).InterpretationOur 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.FundingWellcome Trust Health Consequences of Population Change Programme, WHO, US Alzheimer's Association, FONACIT/ CDCH/ UCV

A set of cross-sectional surveys carried out in Cuba, Dominican Republic, Peru, Mexico, Venezuela, Puerto Rico, China, and India reveal the prevalence and between-country variation in mild cognitive impairment at a population level.

BackgroundIn countries with high incomes, frailty indicators predict adverse outcomes in older people, despite a lack of consensus on definition or measurement. We tested the predictive validity of physical and multidimensional frailty phenotypes in settings in Latin America, India, and China.MethodsPopulation-based cohort studies were conducted in catchment area sites in Cuba, Dominican Republic, Venezuela, Mexico, Peru, India, and China. Seven frailty indicators, namely gait speed, self-reported exhaustion, weight loss, low energy expenditure, undernutrition, cognitive, and sensory impairment were assessed to estimate frailty phenotypes. Mortality and onset of dependence were ascertained after a median of 3.9 years.ResultsOverall, 13,924 older people were assessed at baseline, with 47,438 person-years follow-up for mortality and 30,689 for dependence. Both frailty phenotypes predicted the onset of dependence and mortality, even adjusting for chronic diseases and disability, with little heterogeneity of effect among sites. However, population attributable fractions (PAF) summarising etiologic force were highest for the aggregate effect of the individual indicators, as opposed to either the number of indicators or the dichotomised frailty phenotypes. The aggregate of all seven indicators provided the best overall prediction (weighted mean PAF 41.8 % for dependence and 38.3 % for mortality). While weight loss, underactivity, slow walking speed, and cognitive impairment predicted both outcomes, whereas undernutrition predicted only mortality and sensory impairment only dependence. Exhaustion predicted neither outcome.ConclusionsSimply assessed frailty indicators identify older people at risk of dependence and mortality, beyond information provided by chronic disease diagnoses and disability. Frailty is likely to be multidimensional. A better understanding of the construct and pathways to adverse outcomes could inform multidimensional assessment and intervention to prevent or manage dependence in frail older people, with potential to add life to years, and years to life.

Background To 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.Findings 11 143 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.Interpretation Not 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.