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Background: While age specific prevalence of dementia has recently declined in some high‐income countries it is unclear whether or how the milder end of the spectrum, including Mild Cognitive Impairment might also have changed across generations. This is likely to vary according to how cognitive impairment has been defined, including exclusion criteria. Previous findings from the Cognitive Function and Ageing Studies (CFAS) show prevalence of mild impairment has either increased or remained stable depending on the criteria used, while more severe impairment has decreased over time. Whether different subtypes of MCI used in contemporary studies have different time trends are not known. Method: Data are from the English sites of the population representative Cognitive Function and Ageing Studies (CFAS). In 1991 7,635 participants were interviewed in CFAS I in Cambridgeshire, Nottingham and Newcastle with 1457 being diagnostically assessed. In the same geographical areas, the CFAS II investigators interviewed 7,796 individuals in 2011. Using consensus criteria, the population was categorised into MCI and 'other cognitive impairment no dementia' OCIND. Each cognitive group was further subtyped by the domain of cognition into amnestic (aMCI and aOCIND), non‐amnestic (naMCI and naOCIND) and multi‐domain (mMCI and mOCIND) groups, memory complaints were included as an OCIND subtype. Prevalence estimates for each were calculated using multinomial logistic regression, adjusted for age, sex and education. Results were standardized to the age‐sex specific UK and global population. Result: Between 1991 and 2011 naMCI declined substantially (10.5% versus 6.3%), mMCI increased very slightly (5.9% versus 6.3%) while aMCI, whilst relatively rare, more than doubled in prevalence (1.2% versus 2.6%). In terms of OCIND, the prevalence of naOCIND has dropped (from 17.6% to 13.9%), aOCIND has increased (3.8% to 4.9%) while mOCIND has more than doubled (from 5.7% to 11.2%). Conclusion: Between 1991 and 2011 naMCI declined substantially (10.5% versus 6.3%), mMCI increased very slightly (5.9% versus 6.3%) while aMCI, whilst relatively rare, more than doubled in prevalence (1.2% versus 2.6%). In terms of OCIND, the prevalence of naOCIND has dropped (from 17.6% to 13.9%), aOCIND has increased (3.8% to 4.9%) while mOCIND has more than doubled (from 5.7% to 11.2%). [ABSTRACT FROM AUTHOR]

Background: Vaccine hesitancy is a risk to global health and has become particularly salient considering the COVID‐19 pandemic. To date, no studies have investigated COVID‐19 vaccination behaviour in people with young‐onset dementia (YOD) and their carers. This study aimed to fill this gap. Method: 26 participants with YOD and 24 carers for a person with YOD (i.e., aged <65 years) from the UK were enrolled. Participants filled out a self‐administered online questionnaire including demographic data, history of COVID‐19, and adulthood vaccination. Following this, participants attended a one‐to‐one semi‐structured interview focused on their experiences and thoughts on COVID‐19 vaccines and the vaccination process. Result: The mean age of participants with YOD was 42.2 (range 26‐60), 88.5% were male, and 96.2% self‐identified as Black. The mean age of carers was 31.7 (range 19‐54 years), 70.8% were male, and 79.2% self‐identified as Black. In total, more than 30 reasons for acceptance and hesitation were identified. Willing to protect themselves, loved ones, and the community were identified as important reason to accept the vaccination by both groups. Recommendations from family members or healthcare professionals and wanting to go back to normal life were two of the most commonly repeated acceptance reason for people with YOD. Meanwhile, two of the most frequently mentioned acceptance reasons in carer groups were believing vaccination is the right thing to do and knowing the severity of COVID‐19. Several causes of vaccine hesitancy were mentioned by both groups, including fear of vaccine side effects and hearing negative news about the vaccination. In addition, people with YOD, but not carers, also identified fear of needles and suspicion that vaccination would exacerbate dementia as important causes of vaccine hesitancy. Important difficulties experienced in the vaccination process included long queues for vaccination, remote vaccine centre locations, and needing to be accompanied to the hospital for each dose. Conclusion: Participants delayed or refused COVID‐19 vaccination largely due to resolvable reasons such as a lack of time, issues around queuing, inaccurate information about vaccines, or previous negative experiences. Future research should explore the factors of COVID‐19 vaccination behaviour in women and in other ethnic groups. [ABSTRACT FROM AUTHOR]

Background: More than two thirds of people with dementia are living in the low‐ and middle‐ income countries (LMICs). The growing dementia prevalence will result in significant economic burden in these countries. This systematic review aimed to summarise the evidence on the economic burden of dementia in LMICs. Method: Seven databases (EconLit, EMBASE, PubMed, Cochrane Review (DARE), ERIC, PsycINFO and CINAHL) were searched from inception to September 2020 for original research articles reporting the economic burden or cost of illness for all‐cause dementia and/or its subtypes e.g., Alzheimer's disease (AD), from any LMICs as defined by the World Bank. Two independent reviewers assessed studies for eligibility. Data on the location, study characteristics, cost estimation methods and estimated costs were extracted. The national level total, direct and indirect costs inflated to 2019, were expressed as a percentage of each country's Gross Domestic Product (GDP) and were summarised using mean percentage of GDP. Study quality was assessed using the Larg and Moss method. Result: The literature search identified 14092 articles, of which 22 studies met the eligibility criteria. The national cost of dementia was reported in 64% of the studies (from 120 countries). The remaining studies reported only patient level cost. Majority of the studies had low risk of bias. The average national dementia cost estimated as proportion of GDP was 0.42%. Informal care or indirect costs on average accounted for 62% of the total cost of dementia, while 38% was due to the direct cost. Conclusion: Dementia is a major cause of economic burden in LMICs. Cost of informal care or indirect cost is the major contributor of this cost. The cost of dementia in LMIC has doubled since first reported in the World Alzheimer Report in 2015 (0.2% of GDP). Acknowledgement: This research was funded by the National Institute for Health Research (NIHR) (16/137/62 ‐ Dementia Prevention and Enhanced Care (DePEC), Newcastle University, United Kingdom), using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. [ABSTRACT FROM AUTHOR]

The article discusses geriatric psychiatry as of April 2013, with a focus on the instruments used in measuring behavioural and psychological symptoms of dementia (BPSD). Topics include the Neuropsychiatric Inventory (NPI) questionnaire which measures BPSD, cognitive impairment assessments, and the Behavioral Pathology in Alzheimer’s Disease Scale (BEHAVE-AD).

Background: Most people with dementia live in Low and Middle Income Countries (LMICs), where little research on dementia risk prediction modelling has occurred. This study aimed to develop new models to simply predict all‐cause dementia, suitable for use in LMICs. Country‐specific models were expected, due to different risk profiles. Method: Data was from the 10/66 cohort study. Individuals aged ≥65 years without dementia at baseline (N=11,143) were recruited from Cuba, the Dominican Republic, Peru, Venezuela, Mexico, Puerto Rico and China. Dementia incidence was assessed over a mean follow‐up of 3.8 years (SD=1.3 years). Variables were selected to be tested that have been associated with dementia previously. Two Cox risk models were produced for each site, with and without objective cognitive variables. Predictive accuracy (c‐statistic) and calibration were tested. Result: 1,069 individuals progressed to dementia during follow‐up. The models had mostly moderate to good predictive accuracy. The models in the total sample performed moderately (cognitive model c‐statistic = 0.74; 95%CI: 0.72‐0.75; non‐cognitive model c‐statistic = 0.71; 95%CI: 0.70‐0.73). In each country, the cognitive models' c‐statistics ranged from 0.70 (95%CI: 0.67‐0.74) in China to 0.84 (95%CI: 0.80‐0.88) in Peru, and the non‐cognitive models' c‐statistics ranged from 0.67 (95%CI: 0.63‐0.71) in the Dominican Republic to 0.80 (95%CI: 0.74‐0.85) in Peru. There were no major noticeable patterns of variables included in each country‐specific model. Model calibration was however poor. Conclusion: Different prediction models were necessary for each country, most of which had moderate to good predictive accuracy. Further research is needed to improve calibration, and to determine whether risk prediction is cost‐effective, ethical and acceptable in LMICs. Dementia risk prediction is important so that individuals at high risk can be identified, and their risk factors addressed, to help decrease the burden of dementia. [ABSTRACT FROM AUTHOR]