ObjectivesTo assess the prevalence and factors associated with mild cognitive impairment (MCI) among older adults in an urban area of South India.SettingThe study was conducted in the capital city of Thiruvananthapuram in the South Indian state of Kerala.ParticipantsThe study participants were community-dwelling individuals aged 60 years and above.Primary outcome measureMCI was the primary outcome measure and was defined using the criteria by European Alzheimer’s Disease Consortium. Cognitive assessment was done using the Malayalam version of Addenbrooke’s Cognitive Examination tool. Data were also collected on sociodemographic variables, self-reported comorbidities like hypertension and diabetes, lifestyle factors, depression, anxiety and activities of daily living.ResultsThe prevalence of MCI was found to be 26.06% (95% CI of 22.12 to 30.43). History of imbalance on walking (adjusted OR 2.75; 95 % CI of 1.46 to 5.17), presence of depression (adjusted OR 2.17, 95 % CI of 1.21 to 3.89), anxiety (adjusted OR 2.22; 95 % CI of 1.21 to 4.05) and alcohol use (adjusted OR 1.99; 95 % CI of 1.02 to 3.86) were positively associated with MCI while leisure activities at home (adjusted OR 0.33; 95 % CI of 0.11 to 0.95) were negatively associated.ConclusionThe prevalence of MCI is high in Kerala. It is important that the health system and the government take up urgent measures to tackle this emerging public health issue.

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.

IntroductionMore than two-thirds of people with dementia live in low- and middle-income countries (LMICs), resulting in a significant economic burden in these settings. In this systematic review, we consolidate the existing evidence on the cost of dementia in LMICs.MethodsSix databases were searched for original research reporting on the costs associated with all-cause dementia or its subtypes in LMICs. The national-level dementia costs inflated to 2019 were expressed as percentages of each country’s gross domestic product (GDP) and summarised as the total mean percentage of GDP. The risk of bias of studies was assessed using the Larg and Moss method.ResultsWe identified 14 095 articles, of which 24 studies met the eligibility criteria. Most studies had a low risk of bias. Of the 138 LMICs, data were available from 122 countries. The total annual absolute per capita cost ranged from US$590.78 for mild dementia to US$25 510.66 for severe dementia. Costs increased with the severity of dementia and the number of comorbidities. The estimated annual total national costs of dementia ranged from US$1.04 million in Vanuatu to US$195 billion in China. The average total national expenditure on dementia estimated as a proportion of GDP in LMICs was 0.45%. Indirect costs, on average, accounted for 58% of the total cost of dementia, while direct costs contributed 42%. Lack of nationally representative samples, variation in cost components, and quantification of indirect cost were the major methodological challenges identified in the existing studies.ConclusionThe estimated costs of dementia in LMICs are lower than in high-income countries. Indirect costs contribute the most to the LMIC cost. Early detection of dementia and management of comorbidities is essential for reducing costs. The current costs are likely to be an underestimation due to limited dementia costing studies conducted in LMICs, especially in countries defined as low- income.PROSPERO registration numberThe protocol was registered in the International Prospective Register of Systematic Reviews database with registration number CRD42020191321.

Background: Although an increase in the burden of Alzheimer's disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HRQOL) associated with AD in low-and middle-income countries is still lacking.Objectives: This study aimed to collect real-world cost and HRQOL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand.Methods: We recruited AD patients aged $60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HRQOL, and caregiving information using standardized tools. The hospital's database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HRQOL.

Background: Multiple sclerosis is thought to be relatively uncommon in the Asia Pacific region with prevalence estimated between 0 and 20 per 100,000. There is reason to doubt these estimates due to the lack of data from many countries and the growing evidence of variability in prevalence across small geographic areas. This study was conducted to systematically review the population prevalence, incidence, mortality and disability progression estimates of MS within the Asia Pacific region.Methods: The systematic review was conducted on articles from 1985 till 31st July 2017 within the PubMed/MEDLINE, EMBASE, SCOPUS, and The Cochrane Library databases. The review included articles that were population-based studies conducted on patients with MS in the Asia Pacific region that reported either incidence, prevalence, mortality, or disease progression. Hospital-based studies and non-research articles were excluded to ensure that only information representative of the population was included for analysis. Data appraisal and extraction was done by independent reviewers. This review was registered with PROSPERO (ID: CRD42017082760).Findings: Of the 2,757 articles found, 16 studies were included. Information on 6 (18.75%) of 32 Asia Pacific countries was found, with data representing 8% of the total population. Prevalence estimates were available for 6 countries while estimates for incidence (3 countries), mortality (4 countries), and disease progression (2 countries) were limited.Interpretation: The lack of epidemiological data available in the Asia Pacific region creates a blind spot in the surveillance of MS which obscures the true burden of MS, causing patients to struggle to receive the resources and funding that they need.