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Background: Education and occupational complexity are main sources of mental engagement during early life and adulthood respectively, but research findings are not conclusive regarding protective effects of these factors against late-life dementia. Objective: This project aimed to examine the unique contributions of education and occupational complexity to incident dementia, and to assess the mediating effects of occupational complexity on the association between education and dementia across diverse cohorts. Method: We used data from 10,195 participants (median baseline age = 74.1, range = 58∼103), representing 9 international datasets from 6 countries over 4 continents. Using a coordinated analysis approach, the accelerated failure time model was applied to each dataset, followed by meta-analysis. In addition, causal mediation analyses were performed. Result: The meta-analytic results indicated that both education and occupational complexity were independently associated with increased dementia-free survival time, with 28%of the effect of education mediated by occupational complexity. There was evidence of threshold effects for education, with increased dementia-free survival time associated with ‘high school completion’ or ‘above high school’ compared to ‘middle school completion or below’. Conclusion: Using datasets from a wide range of geographical regions, we found that both early life education and adulthood occupational complexity were independently predictive of dementia. Education and occupational experiences occur during early life and adulthood respectively, and dementia prevention efforts could thus be made at different stages of the life course.

The Maintain Your Brain (MYB) trial is one of the largest internet-delivered multidomain randomised controlled trial designed to target modifiable risk factors for dementia. It comprises four intervention modules: physical activity, nutrition, mental health and cognitive training. This paper explains the MYB Nutrition Module, which is a fully online intervention promoting the adoption of the ‘traditional’ Mediterranean Diet (MedDiet) pattern for those participants reporting dietary intake that does not indicate adherence to a Mediterranean-type cuisine or those who have chronic diseases/risk factors for dementia known to benefit from this type of diet. Participants who were eligible for the Nutrition Module were assigned to one of the three diet streams: Main, Malnutrition and Alcohol group, according to their medical history and adherence to the MedDiet at baseline. A short dietary questionnaire was administered weekly during the first 10 weeks and then monthly during the 3-year follow-up to monitor whether participants adopted or maintained the MedDiet pattern during the intervention. As the Nutrition Module is a fully online intervention, resources that promoted self-efficacy, self-management and process of change were important elements to be included in the module development. The Nutrition Module is unique in that it is able to individualise the dietary advice according to both the medical and dietary history of each participant; the results from this unique intervention will contribute substantively to the evidence that links the Mediterranean-type diet with cognitive function and the prevention of dementia and will increase our understanding of the benefits of a MedDiet in a Western country.

Background and purpose: Mortality is known to be markedly increased in people with dementia. However, the association between multiple chronic conditions and mortality in dementia is not well clarified. The aim of this study was to investigate the impact of somatic and psychiatric diseases on mortality in dementia compared with the general elderly population. Methods: Using a cohort study design, nationwide registry data from 2006 to 2015 on dementia and psychiatric and somatic comorbidities defined by the Charlson Comorbidity Index (CCI) were linked. Impact of chronic conditions was assessed according to mortality rate ratios (MRRs) in all Danish residents aged ≥65 years with and without dementia. Results: Our population comprised 1,518,917 people, of whom 114,109 people were registered with dementia. The MRRs was 2.70 (95% confidence interval 2.68, 2.72) in people with dementia after adjusting for sex, age, calendar year, and comorbidities. MRRs increased with higher CCI score, and when comparing people with a similar comorbidity load, MRRs were significantly higher for people with dementia. Conclusions: The comorbidity load was associated with increased mortality in both people with and without dementia. Mortality in dementia remained increased, even after adjusting for psychiatric and chronic somatic comorbidities. Our findings suggest that dementia disorders alone contribute to excess mortality, which may be further increased by comorbidities.

In the past decade a large body of evidence has accumulated on risk factors for dementia, primarily from Europe and North America. Drawing on recent integrative reviews and a consensus workshop, the International Research Network on Dementia Prevention developed a consensus statement on priorities for future research. Significant gaps in geographical location, representativeness, diversity, duration, mechanisms, and research on combinations of risk factors were identified. Future research to inform dementia risk reduction should fill gaps in the evidence base, take a life-course, multi-domain approach, and inform population health approaches that improve the brain-health of whole communities.

Background While midlife hypertension is deleterious, late-life hypertension has been associated with better cognitive outcomes in several studies. Many questions remain, including the relative benefit or harm of a blood pressure (BP) target and antihypertensive therapy of Methods The Sydney Memory and Aging Study (n = 1015) comprises a cohort of 70- to 90-year-olds, who were followed biennially for 8 years. Global cognition was assessed with a battery of 10 neuropsychological tests. Blood pressure was measured at Waves 1 and 2 and classified into 3 systolic groupings: group 1 (≤120 mmHg), group 2 (121–140 mmHg), and group 3 (>140 mmHg). Multiple regression, linear mixed modeling, and Cox regression examined the effect of BP and antihypertensives. Results There were no overall significant differences in global cognition or dementia between the disparate BP groups. However, in those not taking antihypertensives, the systolic BP (SBP) > 140 mmHg group had a significantly worse global cognitive trajectory compared to SBP ≤ 120 mmHg (b = −0.067, 95% CI [−0.129, −0.006], p = .030). Within the SBP ≤ 120 mmHg group those taking antihypertensives had significantly worse global cognition trajectories compared to those not taking antihypertensives even when controlling for past history of hypertension (b = −0.077, 95% CI [−0.147, −0.007], p = .030). Conclusions Untreated hypertension in old age is related to worse global cognitive decline. However, ongoing treatment at new recommendations of lower SBP targets may be related to poorer cognitive decline and should be considered carefully in older populations.

Walsh (2020) underscores how dementia leads to a cognitive transformative experience, which can result in a change in preferences, values, and beliefs. This transformation supports placing greater ...

Introduction: Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts.Methods: To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives.Results: With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes.Discussion: This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond.

International audience; The Alzheimer's Association International Conference held its sixth Satellite Symposium in Sydney, Australia in 2019, highlighting the leadership of Australian researchers in advancing the understanding of and treatment developments for Alzheimer's disease (AD) and other dementias.This leadership includes the Australian Imaging, Biomarker, and Lifestyle Flagship Study of Ageing (AIBL), which has fueled the identification and development of many biomarkers and novel therapeutics. Two multimodal lifestyle intervention studies have been launched in Australia; and Australian researchers have played leadership roles in other global studies in diverse populations.Australian researchers have also played an instrumental role in efforts to understand mechanisms underlying vascular contributions to cognitive impairment and dementia; and through the Women's Healthy Aging Project have elucidated hormonal and other factors that contribute to the increased risk of AD in women. Alleviating the behavioral and psychological symptoms of dementia has also been a strong research and clinical focus in Australia.

Background: Longitudinal neuroimaging provides spatiotemporal brain data (STBD) measurement that can be utilised to understand dynamic changes in brain structure and/or function underpinning cognitive activities. Making sense of such highly interactive information is challenging, given that the features manifest intricate temporal, causal relations between the spatially distributed neural sources in the brain.\ud \ud Methods: The current paper argues for the advancement of deep learning algorithms in brain-inspired spiking neural networks (SNN), capable of modelling structural data across time (longitudinal measurement) and space (anatomical components). The paper proposes a methodology and a computational architecture based on SNN for building personalised predictive models from longitudinal brain data to accurately detect, understand, and predict the dynamics of an individual’s functional brain state. The methodology includes finding clusters of similar data to each individual, data interpolation, deep learning in a 3-dimensional brain-template structured SNN model, classification and prediction of individual outcome, visualisation of structural brain changes related to the predicted outcomes, interpretation of results, and individual and group predictive marker discovery. \ud \ud Results: To demonstrate the functionality of the proposed methodology, the paper presents experimental results on a longitudinal magnetic resonance imaging (MRI) dataset derived from 175 older adults of the internationally recognised community-based cohort Sydney Memory and Ageing Study (MAS) spanning 6 years of follow-up.\ud \ud Significance: The models were able to accurately classify and predict 2 years ahead of cognitive decline, such as mild cognitive impairment (MCI) and dementia with 95% and 91% accuracy, respectively. The proposed methodology also offers a 3-dimensional visualisation of the MRI models reflecting the dynamic patterns of regional changes in white matter hyperintensity (WMH) and brain volume over 6 years.\ud \ud Conclusion: The method is efficient for personalised predictive modelling on a wide range of neuroimaging longitudinal data, including also demographic, genetic, and clinical data. As a case study, it resulted in finding predictive markers for MCI and dementia as dynamic brain patterns using MRI data.

Objective: This study aimed to investigate psychometric properties and enhance precision of the 16-item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE-16) up to interval-level scale using Rasch methodology. Design: Partial Credit Rasch model was applied to the IQCODE-16 scores using longitudinal data spanning 10 years of biennial follow-up. Setting: Community-dwelling older adults aged 70–90 years and their informants, living in Sydney, Australia, participated in the longitudinal Sydney Memory and Ageing Study (MAS). Participants: The sample included 400 participants of the MAS aged 70 years and older, 109 out of those were diagnosed with dementia 10 years after the baseline assessment. Measurements: The IQCODE-16. Results: Initial analysis indicated excellent reliability of the IQCODE-16, Person Separation Index (PSI) = 0.92, but there were four misfitting items and local dependency issues. Combining locally dependent items into four super-items resulted in the best Rasch model fit with no misfitting or locally dependent items, strict unidimensionality, strong reliability, and invariance across person factors such as participants’ diagnosis and relationship to their informants, as well as informants’ age and sex. This permitted the generation of conversion algorithms to transform ordinal scores into interval data to enhance precision of measurement. Conclusions: The IQCODE-16 demonstrated strong reliability and satisfied expectations of the unidimensional Rasch model after minor modifications. Ordinal-to-interval transformation tables published here can be used to increase accuracy of the IQCODE-16 without altering its current format. These findings could contribute to enhancement of precision in assessing clinical conditions such as cognitive decline in older people.

Background: Poststroke cognitive impairment is common, but the trajectory and magnitude of cognitive decline after stroke is unclear. We examined the course and determinants of cognitive change after stroke using individual participant data from the Stroke and Cognition Consortium. Methods: Nine longitudinal hospital-based cohorts from 7 countries were included. Neuropsychological test scores and normative data were used to calculate standardized scores for global cognition and 5 cognitive domains. One-step individual participant data meta-analysis was used to examine the rate of change in cognitive function and risk factors for cognitive decline after stroke. Stroke-free controls were included to examine rate differences. Based on the literature and our own data that showed short-term improvement in cognitive function after stroke, key analyses were restricted to the period beginning 1-year poststroke to focus on its long-term effects. Results: A total of 1488 patients (mean age, 66.3 years; SD, 11.1; 98% ischemic stroke) were followed for a median of 2.68 years (25th–75th percentile: 1.21–4.14 years). After an initial period of improvement through up to 1-year poststroke, decline was seen in global cognition and all domains except executive function after adjusting for age, sex, education, vascular risk factors, and stroke characteristics (−0.053 SD/year [95% CI, −0.073 to −0.033]; P P Conclusions: Patients with stroke experience cognitive decline that is faster than that of stroke-free controls from 1 to 3 years after onset. An increased rate of decline is associated with older age and recurrent stroke.

Publisher's version (útgefin grein), Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = −0.71 to −1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = −0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10−6, 1.7 × 10− 9, 3.5 × 10−12 and 1.0 × 10−4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes., 1000BRAINS: 1000BRAINS is a population-based cohort based on the Heinz-Nixdorf Recall Study and is supported in part by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The HNR study is also supported by the German Ministry of Education and Science (FKZ 01EG940), and the German Research Council (DFG, ER 155/6-1). The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 7202070 (Human Brain Project SGA1; Katrin Amunts, Sven Cichon). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A to M.M.N. and S.C.), and by the Swiss National Science Foundation (SNSF, grant 156791 to S.C.). 16p.11.2 European Consortium: B.D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant Nr 32003B_159780) and Foundation Synapsis. LREN is very grateful to the Roger De Spoelberch and Partridge Foundations for their generous financial support. This work was supported by grants from the Simons Foundation (SFARI274424) and the Swiss National Science Foundation (31003A_160203) to A.R. and S.J. Betula: The relevant Betula data collection and analyses were supported by a grant from the Knut & Alice Wallenberg (KAW) to L. Nyberg. Brainscale: the Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Dorret Boomsma & Hilleke Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council (ERC-230374) (Dorret Boomsma), High Potential Grant Utrecht University (Hilleke Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hilleke Hulshoff Pol). Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers of the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud university medical centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received supported from the participating departments and centres and from external grants, i.e., the Biobanking and Biomolecular Resources Research Infrastructure (the Netherlands) (BBMRI-NL), the Hersenstichting Nederland, and the Netherlands Organisation for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreements n° 602450 (IMAGEMEND), n°278948 (TACTICS), and n°602805 (Aggressotype) as well as from the European Community’s Horizon 2020 programme under grant agreement n° 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. COBRE: This work was supported by a NIH COBRE Phase I grant (1P20RR021938, Lauriello, PI and 2P20GM103472, Calhoun, PI) awarded to the Mind Research Network. We wish to express our gratitude to numerous investigators who were either external consultants to the Cores and projects, mentors on the projects, members of the external advisory committee and members of the internal advisory committee. Decode: The research leading to these results has received financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007–2013), EU-FP7 funded grant no. 602450 (IMAGEMEND) as well as support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no.115300 (EUAIMS). DemGene: Norwegian Health Association and Research Council of Norway. Dublin: Work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and SFI08/IN.1/B1916-Corvin to Aidan C Corvin) and the European Research Council (ERC-StG-2015-677467). EPIGEN-UK (SMS, CL): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner, and the Epilepsy Society for supporting CL. Haavik: The work at the K.G.Jebsen center for neuropsychiatric disorders at the University of Bergen, Norway, was supported by Stiftelsen K.G. Jebsen, European Community’s Seventh Framework Program under grant agreement no 602805 and the H2020 Research and Innovation Program under grant agreement numbers 643051 and 667302. HUNT: The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: The work received support from the European Union-funded FP6Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), the FP7 projects IMAGEMEND (602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EU-AIMS (115300), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-1, SM 80/7-2, SFB 940/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, and ANR-12-SAMA-0004), the Fondation de France, the Fondation pour la Recherche Médicale, the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. MCIC: This work was supported primarily by the Department of Energy DE-FG02-99ER62764 through its support of the Mind Research Network and the consortium as well as by the National Association for Research in Schizophrenia and Affective Disorders (NARSAD) Young Investigator Award (to SE) as well as through the Blowitz-Ridgeway and Essel Foundations, and through NWO ZonMw TOP 91211021, the DFG research fellowship (to SE), the Mind Research Network, National Institutes of Health through NCRR 5 month-RR001066 (MGH General Clinical Research Center), NIMH K08 MH068540, the Biomedical Informatics Research Network with NCRR Supplements to P41 RR14075 (MGH), M01 RR 01066 (MGH), NIBIB R01EB006841 (MRN), R01EB005846 (MRN), 2R01 EB000840 (MRN), 1RC1MH089257 (MRN), as well as grant U24 RR021992. NCNG: this sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the K.G. Jebsen Foundation, the Research Council of Norway, to SLH, VMS and TE. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to AL, Grant 911397 and 911687 to AJL). NESDA: Funding for NESDA was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10-000-1002); the Center for Medical Systems Biology (CSMB, NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University’s Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, R01D0042157-01A, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health.Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. NTR: The NTR study was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (Eco de Geus & Dorret Boomsma), MaGW-nr: 400-07- 080 (Dennis van ‘t Ent), MagW 480-04-004 (Dorret Boomsma), NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council, ERC-230374 (Dorret Boomsma), and Amsterdam Neuroscience. OATS: OATS (Older Australian Twins Study) was facilitated by access to Twins Research Australia, which is funded by a National Health and Medical Research Council (NHMRC) Enabling Grant 310667. OATS is also supported via a NHMRC/Australian Research Council Strategic Award (401162) and a NHMRC Project Grant (1045325). DNA extraction was performed by Genetic Repositories Australia, which was funded by a NHMRC Enabling Grant (401184). OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. PAFIP: PAFIP data were collected at the Hospital Universitario Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support: Carlos III Health Institute PIE14/00031 and SAF2013-46292-R and SAF2015-71526-REDT. We wish to acknowledge IDIVAL Neuroimaging Unit for imaging acquirement and analysis.We want to particularly acknowledge the patients and the BioBankValdecilla (PT13/0010/0024) integrated in the Spanish National Biobanks Network for its collaboration. QTIM: The QTIM study was supported by grants from the US National Institute of Child Health and Human Development (R01 HD050735) and the Australian National Health and Medical Research Council (NHMRC) (486682, 1009064). Genotyping was supported by NHMRC (389875). Lachlan Strike is supported by an Australian Postgraduate Award (APA). AFM is supported by NHMRC CDF 1083656. We thank the twins and siblings for their participation, the many research assistants, as well as the radiographers, for their contribution to data collection and processing of the samples. SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, 01ZZ0403 and 01ZZ0701), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. Whole-body MR imaging was supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. StrokeMRI: StrokeMRI has been supported by the Research Council of Norway (249795), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Norwegian ExtraFoundation for Health and Rehabilitation. TOP: TOP is supported by the Research Council of Norway (223273, 213837, 249711), the South East Norway Health Authority (2017-112), the Kristian Gerhard Jebsen Stiftelsen (SKGJ‐MED‐008) and the European Community’s Seventh Framework Programme (FP7/2007–2013), grant agreement no. 602450 (IMAGEMEND). We acknowledge the technical support and service from the Genomics Core Facility at the Department of Clinical Science, the University of Bergen

Objectives Dementia, with its progressive cognitive and functional decline and associated neuropsychiatric symptoms, places a large burden on caregivers. While frequently studied, longitudinal findings about the overall trajectory of burden are mixed. The study sought to characterize caregiver burden over a 3-year period and identify predictors of this burden. Methods Seven-hundred-and-eighty-one patients with dementia were recruited from nine memory clinics around Australia. Measures of caregiver burden, cognition, function, and neuropsychiatric symptoms were completed with patients and their caregivers at regular intervals over a 3-year period. Patients' level of services and medication use were also recorded. Results Of the 720 patients with measures of caregiver burden at baseline, 47.4% of caregivers had clinically significant levels of burden. This proportion increased over time, with 56.8% affected at 3 years. Overall levels of burden increased for caregivers of patients without services, though did not change for caregivers of patients receiving services or residential care after controlling for other variables. Patient characteristics-including greater neuropsychiatric symptoms, lower functional ability, fewer medications, lack of driving ability-and female sex of caregivers were associated with greater burden. Conclusions High levels of caregiver burden are present in a large proportion of caregivers of people with dementia and this increases over time for those without services. Clinical characteristics of patients (including neuropsychiatric symptoms, function, overall health, driving status), level of services, and caregiver sex appear to be the best predictors of this burden. These characteristics may help identify caregivers at greater risk of burden to target for intervention.

Background There is widespread consumer concern that statin use may be associated with impaired memory and cognitive decline. Objectives This study sought to examine the association between statin use and changes in memory and global cognition in the elderly population over 6 years and brain volumes over 2 years. Interactions between statin use and known dementia risk factors were examined. Methods Prospective observational study of community-dwelling elderly Australians age 70 to 90 years (the MAS [Sydney Memory and Ageing Study], n = 1,037). Outcome measures were memory and global cognition (by neuropsychological testing every 2 years) and total brain, hippocampal and parahippocampal volumes (by magnetic resonance) in a subgroup (n = 526). Analyses applied linear mixed modeling, including the covariates of age, sex, education, body mass index, heart disease, diabetes, hypertension, stroke, smoking, and apolipoprotein Ee4 carriage. Interactions were sought between statin use and dementia risk factors. Results Over 6 years there was no difference in the rate of decline in memory or global cognition between statin users and never users. Statin initiation during the observation period was associated with blunting the rate of memory decline. Exploratory analyses found statin use was associated with attenuated decline in specific memory test performance in participants with heart disease and apolipoprotein Ee4 carriage. There was no difference in brain volume changes between statin users and never users. Conclusions In community-dwelling elderly Australians, statin therapy was not associated with any greater decline in memory or cognition over 6 years. These data are reassuring for consumers concerned about statin use and risk of memory decline.

Objectives Mild cognitive impairment (MCI) is common, affecting 10%–35% of people over 65, and poses unique challenges for patients and their caregivers. Comparatively little research has examined caregiver burden in this population, with longitudinal research, in particular, lacking. We examined caregiver burden in a sample of people with MCI over 3 years. Design Three-year observational study. Setting Nine memory clinics in Australia. Participants One-hundred-and-eighty-five people with MCI and their caregivers. Measurements Measures of caregiver burden, cognition, function, neuropsychiatric symptoms, driving status, and medication use were completed with patients and their caregivers at regular intervals over a 3-year period. Results Between 21.1% and 29.5% of caregivers reported a clinically significant level of burden over the study. Patients’ higher levels of neuropsychiatric symptoms, lower functional ability, and lack of driving ability, and caregivers’ employment were associated with greater caregiver burden over time. Caregiver burden did not increase over time when controlling for patient and caregiver characteristics. Conclusions High levels of caregiver burden are present in a significant proportion of caregivers of people with MCI. Clinical characteristics of patients – including severity of neuropsychiatric symptoms and functional impairment – and the employment status of caregivers predict burden. Such characteristics may help identify caregivers at greater risk of burden to target for intervention.

Introduction Both genetic and nongenetic factors contribute to the risk profile of young onset dementia (YOD), but risk factors often co-occur. This matched case-control study examined whether nongenetic risk factors cluster together, to inform targeted prevention efforts. Methods Ninety-six participants with non-autosomal-dominant degenerative and/or vascular YOD and 175 controls were recruited to 2 Australian epidemiological studies. Risk exposure was retrospectively self-reported and/or informant-reported. Results Each additional exposure increased the risk for YOD, though only where vascular dementia was included in the analysis. Cluster analysis identified 4 risk groups, one of which reported a high probability of exposure to all risks and a significantly higher risk for YOD. Discussion Results suggest that combinations of nongenetic risk factors confer more risk for young onset vascular dementia, and possibly primary degenerative YOD, than a single factor on its own. Compared with their same-age peers, some people with YOD experience a lifetime of risk exposure starting from early in life.

Objectives Telephone-based cognitive screens, such as the Telephone Interview for Cognitive Status (TICS), can potentially reduce the barriers and costs of assessing older adults. However, validation of clinically relevant psychometric properties is lacking in a large and comprehensively assessed sample of older adults. Furthermore, published normative data may lack sensitivity as they have not used regression-based demographic corrections or accounted for cases with subsequent dementia. We address these gaps using the modified TICS (TICS-M; a modified, 13-item, 39-point version) and provide an online norms calculator for clinicians and researchers. Design Prospective longitudinal study. Setting Sydney, Australia. Participants A total of 617 community-living older adults, aged from 71 to 91 years. Measurements The measures used included the TICS-M, the Mini-Mental State Examination (MMSE), Addenbrooke's Cognitive Examination-Revised (ACE-R), and a comprehensive neuropsychological test battery. Descriptive statistics, correlations, area under the curve, and regression analyses were used to determine the validity and normative properties of the TICS-M. Results TICS-M total scores (mean = 24.20; SD = 3.76) correlated well with the MMSE (0.70) and ACE-R (0.80) and moderately with neuropsychological tests tested noncontemporaneously. A cutoff score of 21 or lower reliably distinguished between those with and without incident dementia after 1 year (sensitivity = 77%; specificity = 88%) but was less reliable at distinguishing mild cognitive impairment from normal cognition. TICS-M scores decreased with age and increased with higher education levels. The robust normative sample, which excluded incident dementia cases, scored higher on the TICS-M and with less variability than the whole sample. An online calculator is provided to compute regression-based norms and reliable change statistics. Conclusions In a large sample of community-dwelling older adults, the TICS-M performed well in terms of construct validity against typical screening tools and neuropsychological measures and diagnostic validity for incident dementia. The comprehensive, regression-based, and robust normative data provided will help improve the sensitivity, accessibility, and cost-effectiveness of cognitive testing with older adults. J Am Geriatr Soc 67:2108-2115, 2019.

Objectives To describe the injury profile, hospitalisation rates and health outcomes for older people with cognitive impairment and to determine whether these differ from those with normal cognition. Methods Participants were 867 community-dwelling 70–90 year olds enrolled in the population-based longitudinal Sydney Memory and Ageing Study (MAS). Participant’s cognitive status was classified as normal, mild cognitive impairment (MCI) and dementia at baseline, then 2, 4 and 6 years’ follow-up. MAS records were linked to hospital and death records to identify injury-related hospitalisations for the 2-year period following each assessment. Results There were 335 injury-related hospitalisations for participants; 222 (25.6%) participants had at least one injury-related hospitalisation. The injury-related hospitalisation rate for participants with MCI (63.0 [95%CI 51.6–74.4] per 1000 person-years) was higher than for people with normal cognition (39.3 [95%CI 32.4–46.1] per 1000 person-years) but lower than people with dementia (137.1 [95%CI 87.2–186.9] per 1000 person-years). Upper limb fractures (22.1%) were the most common injuries for participants with normal cognition, and non-fracture head injuries for participants with MCI and dementia (25.9% and 23.3% respectively). Participants with dementia had a higher proportion of hip fractures (20.0%, p = 0.0483) than participants with normal cognition. There was no difference in 30-day mortality between participants with normal cognition, MCI and dementia (3.9%, 1.7%, 3.3% respectively). Conclusion Older people with objectively defined MCI are at higher risk of injury-related hospitalisation than their cognitively intact peers, but lower risk than people with dementia. Falls-risk screening and fall prevention initiatives may be indicated for older people with MCI.

Background and purpose The Vascular Behavioral and Cognitive Disorders (VASCOG) criteria for vascular cognitive disorders were published in 2014, but their concurrent and predictive validity have not been examined. Methods Participants (N = 165, aged 49-86 years) were from Sydney Stroke Study, a longitudinal study of post-stroke cognitive impairment and dementia. Diagnoses using the National Institute of Neurological Disorders and Stroke - Association Internationale pour la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN), the Alzheimer's Disease Diagnostic and Treatment Centers (ADDTC) and the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV), criteria for vascular dementia (VaD) were made by consensus at multidisciplinary case conferences. Diagnoses for mild vascular cognitive disorder (mVCD) and VaD using VASCOG, DSM-5 and the Vascular Impairment of Cognition Classification Consensus Study (VICCCS) criteria were made by two study authors. Agreement levels between criteria sets were examined using Cohen's kappa (κ). The ability of VaD diagnoses to predict mortality over 10 years and of mVCD to predict dementia over 5 years was investigated. Results The VASCOG criteria yielded rates of mVCD slightly lower than for DSM-5 and VICCCS. VaD rates were similar for all criteria, although slightly lower for DSM-IV. Agreement between the VASCOG, VICCCS and DSM-5 criteria was excellent for VaD and mVCD (κ = 0.83-1.0), but lower for VaD between VASCOG and the other criteria (κ = 0.47-0.63). VaD-based mortality predictions were similar for the VASCOG, VICCCS and DSM-5 criteria, and higher than those for other criteria. The prediction of incident dementia within 5 years from mVCD was slightly lower with VASCOG criteria than with DSM-5 and VICCCS criteria. Conclusions The VASCOG criteria have greater sensitivity, modest concurrent validity and better predictive validity than older criteria for VaD, but are comparable to DSM-5 and VICCCS criteria. Their operationalization and inclusion of a mild VCD category make them useful for clinical and research applications.

BACKGROUND A major issue in evaluating the cognitive status of ageing populations is a clear distinction between enduring and dynamic aspects of global cognition necessary for evaluating risks of dementia and effectiveness of preventive interventions. MATERIALS AND METHODS Generalizability Theory was applied to investigate dynamic and enduring aspects of global cognition using longitudinal data over 10 years of follow-up. Measures included the Mini-Mental Status Examination (MMSE) and the Telephone Interview for Cognitive Status-modified (TICS-M). The sample (N = 238) included 154 females, mean age = 76.54 years, SD = 3.94 from the Sydney Memory and Ageing Study. RESULTS The MMSE measured dynamic and enduring aspects of cognition to a comparable degree with 56% of variance explained by enduring aspects and 44% by dynamic aspects and showed low sensitivity/high specificity in detecting dementia. A shortened version of the MMSE (MMSE-D8) better captured dynamic aspects of cognition after removing three items less sensitive to change. The TICS-M predominantly measured enduring aspects of cognition (72%) with the remaining 28% due to dynamic aspects and displayed high sensitivity/high specificity for dementia screening. CONCLUSIONS The MMSE measures both dynamic and enduring cognitive aspects and is suitable for general clinical assessments, while the MMSE-D8 can be used to monitor transitory changes of global cognition over time. The TICS-M is more useful for measuring enduring features of cognition and screening for dementia. Our findings highlight the value of generalizability theory to distinguish dynamic and enduring features of cognition, which may contribute to preventive interventions and monitoring cognitive ability over time.

OBJECTIVE Lifespace, the physical area in which someone conducts life activities, indicates lived community mobility. This study explored the feasibility of technology-based lifespace measurement for older people with dementia and mild cognitive impairment (MCI), including the generation of a range of lifespace metrics, and investigation of relationships with health and mobility status. METHODS An exploratory study was conducted within a longitudinal observational study. Eighteen older adults (mean age 86.7 years (SD: 3.2); 8 men; 15 MCI), participated. Lifespace metrics were generated from geolocation data (GPS and Bluetooth beacon) collected through a smartphone application for one week (2015-2016). Cognitive and mobility-related outcomes were compared from study data sets at baseline (2005-2007) and 6-year follow-up (2011-2014). RESULTS Lifespace data could be collected from all participants, and metrics were generated including percentage of time at home, maximum distance from home, episodes of travel in a week, days in a week participants left home, lifespace area (daily, weekly and total), indoor lifespace (regions in the home/hour), and a developed lifespace score that combined time, frequency of travel, distance and area. Results indicated a large range of lifespace areas (0.1 - 97.88 km2 ; median 6.77 km2 ) with similar patterns across lifespace metrics. Significant relationships were found between lifespace metrics and concurrent driving status and anteceding scores on the sit-to-stand test (at baseline and follow-up). CONCLUSIONS Further longitudinal exploration of lifespace is required to develop an understanding of the nature of lifespace of older community-dwelling people, and its relationship with health, mobility and well-being outcomes.

Recruiting participants for dementia research takes time. For those who are interested, opportunities to participate can be ad hoc. Delays in finding the right participants can result in studies taking longer to deliver, often requiring funding extensions, and ultimately increasing the cost and limiting the effectiveness of research and evaluation. To address these issues, a digital platform, StepUp for Dementia Research, was developed in 2019 and evaluated through ongoing data analytics, researcher feedback and annual volunteer surveys in 2019 and 2021. Using innovative matching technology, StepUp provides volunteers with an opt-in, secure way of registering interest in dementia studies and allows researchers to access matched volunteers in Australia. As of June 2021, 1070 volunteers registered (78% female), and 25 organizations became ‘champions’ for StepUp promotion. Of 122 registered researchers, 90 completed training. Forty studies from 17 research/health institutions recruited participants using StepUp. The evaluation demonstrated program feasibility and recruitment efficiency with a high level of satisfaction from users. Evaluation outcomes highlighted disparities in public participation in dementia research (e.g., gender, education and race/ethnicity) and provided valuable insights for further enhancements of StepUp. A concerted and strategic effort is needed by leading registries such as StepUp to ensure narrowing volunteer participation gaps in dementia research.

Background: Behavioral and psychological symptoms of dementia (BPSD, also known as neuropsychiatric symptoms (NPS), changed behaviors and responsive behaviors), occur in up to 90 percent of people living with dementia (PLWD). These symptoms and behaviors strongly correlate with functional and cognitive impairment and contribute to ~30% of overall dementia costs. As decisions regarding care and strategies for BPSD are generally based on professional frames of reference, this study investigates whether the perspectives of PLWD and families/care partner on BPSD terminology can inform a more nuanced conceptualization of BPSD.Methods: PLWD and families/care partners participated in one-on-one semi-structured interviews. A thematic iterative approach was used to code the data and identify common themes until theoretical saturation was reached. Themes were compared between groups. Data were analyzed deductively in relation to pre-existing terminology regarding BPSD, and inductively to discover new ideas on use of such terminology as perceived by PLWD and others.Results: Forty-one volunteers were interviewed: 21 PLWD, mean age 71 yrs, mean Mini-Mental State Examination score 25, and 20 family members/care partners. Three main themes emerged from the data: (1) descriptions of BPSD from people with lived experience compared to clinical terms, (2) viewpoints on interpreting causes, and (3) experiences of concurrent BPSD. The experiences described and terms used by PLWD and families/care partners differed from terms used in existing professional frameworks (e.g., “disinhibition” described as ‘loss of filter') and there were differences between PLWD and family members' interpretations of BPSD causes.Discussion/Conclusion: Reports from PLWD and families/carers describing their experiences of BPSD suggest a reconceptualization of BPSD terminology is needed to understand and de-stigmatize these symptoms and behaviors. For example, the term “agitated/hard to handle” would benefit by clearer, contextualized description, such as “frustrated with cognitive decline, discriminatory behavior and inadequate support systems.” In better understanding individual expressions of BPSD, families, professionals and societies will be able to respond in ways that are helpful for PLWD. An informed, integrated understanding of BPSD and improved terminology use will have the potential to improve the quality of care and support for PLWD.

Aims: The association between diabetes and cognitive decline (CD) and dementia has been well-documented. This study estimated the associations between risk factors and CD/dementia, and the sex differences in these risk factors in individuals with type 2 diabetes, while accounting for the competing risk of death.\ud \ud Materials and methods: The Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial of 11,140 individuals with type 2 diabetes was used to estimate the odds of CD/dementia using multinomial logistic regression.\ud \ud Results: During a median five-year follow-up, 1,827 participants (43.2% women) had CD/dementia (1,718 with CD only; 21 with dementia only; 88 with CD and dementia), and 929 (31.0% women) died without CD/dementia. Women had a lower odds of CD/dementia than men (Odds Ratio (OR) (95% confidence interval), 0.88 (0.77, 1.00)); older age, higher total cholesterol, HbA1c , waist circumference, waist-to-height ratio, moderately increased ACR (Albumin-Creatinine Ratio), stroke/transient ischemic attack and retinal disease were each associated with greater odds of CD/dementia; higher years at education completion, baseline cognitive function, taller stature and current alcohol use were inversely associated. Higher waist circumference (women-to-men Ratio of Odds Ratios (ROR), 1.05 (1.00, 1.10) per 5 cm) and presence of anxiety/depression (ROR, 1.28 (1.01, 1.63)) were associated with greater OR for CD/dementia in women than men.\ud \ud Conclusions: Several risk factors were associated with CD/dementia. Higher waist circumference and mental health symptoms were more strongly associated with CD/dementia in women than men. Further studies should examine the mechanisms which underlie these sex differences. This article is protected by copyright. All rights reserved.

Objective To examine relationships between changing general practitioner after entering residential aged care and overall medicines prescribing (including polypharmacy) and that of psychotropic medicines in particular. Design Retrospective data linkage study. Setting, participants 45 and Up Study participants in New South Wales with dementia who were PBS concession card holders and entered permanent residential aged care during January 2010 - June 2014 and were alive six months after entry. Main outcome measures Inverse probability of treatment-weighted numbers of medicines dispensed to residents and proportions of residents dispensed antipsychotics, benzodiazepines, and antidepressants in the six months after residential care entry, by most frequent residential care GP category: usual (same as during two years preceding entry), known (another GP, but known to the resident), or new GP. Results Of 2250 new residents with dementia (mean age, 84.1 years; SD, 7.0 years; 1236 women [55%]), 625 most frequently saw their usual GPs (28%), 645 saw known GPs (29%), and 980 saw new GPs (44%). The increase in mean number of dispensed medicines after residential care entry was larger for residents with new GPs (+1.6 medicines; 95% CI, 1.4-1.9 medicines) than for those attended by their usual GPs (+0.7 medicines; 95% CI, 0.4-1.1 medicines; adjusted rate ratio, 2.42; 95% CI, 1.59-3.70). The odds of being dispensed antipsychotics (adjusted odds ratio [aOR], 1.59; 95% CI, 1.18-2.12) or benzodiazepines (aOR, 1.69; 95% CI, 1.25-2.30), but not antidepressants (aOR, 1.32; 95% CI, 0.98-1.77), were also higher for the new GP group. Differences between the known and usual GP groups were not statistically significant. Conclusions Increases in medicine use and rates of psychotropic dispensing were higher for people with dementia who changed GP when they entered residential care. Facilitating continuity of GP care for new residents and more structured transfer of GP care may prevent potentially inappropriate initiation of psychotropic medicines.

Objectives:This study aimed to apply the generalizability theory (G-theory) to investigate dynamic and enduring patterns of subjective cognitive complaints (SCC), and reliability of two widely used SCC assessment tools.Design:G-theory was applied to assessment scales using longitudinal measurement design with five assessments spanning 10 years of follow-up.Setting:Community-dwelling older adults aged 70–90 years and their informants, living in Sydney, Australia, participated in the longitudinal Sydney Memory and Ageing Study.Participants:The sample included 232 participants aged 70 years and older, and 232 associated informants. Participants were predominantly White Europeans (97.8%). The sample of informants included 76 males (32.8%), 153 females (65.9%), and their age ranged from 27 to 86 years, with a mean age of 61.3 years (SD = 14.38).Measurements:The Memory Complaint Questionnaire (MAC-Q) and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE).Results:The IQCODE demonstrated strong reliability in measuring enduring patterns of SCC with G = 0.86. Marginally acceptable reliability of the 6-item MAC-Q (G = 0.77–0.80) was optimized by removing one item resulting in G = 0.80–0.81. Most items of both assessments were measuring enduring SCC with exception of one dynamic MAC-Q item. The IQCODE significantly predicted global cognition scores and risk of dementia incident across all occasions, while MAC-Q scores were only significant predictors on some occasions.Conclusions:While both informants’ (IQCODE) and self-reported (MAC-Q) SCC scores were generalizable across sample population and occasions, self-reported (MAC-Q) scores may be less accurate in predicting cognitive ability and diagnosis of each individual.

Identifying individuals at risk of developing dementia may be aided by early detection of functional impairments. The aims of the present study were to examine differences in informant-reported and performance-based measures of instrumental activities of daily living (IADL) and to assess whether a performance-based IADL measure contributes additional unique variance over informant reports in predicting incident dementia over 4 years.Prospective cohort study (Sydney Memory and Ageing Study).Eastern Suburbs, Sydney, Australia.307 community-dwelling individuals (60.6% female) aged between 76 and 96 years with normal cognition (NC; n = 190) or mild cognitive impairment (MCI; n = 117).IADL ability was assessed with the performance-based Sydney Test of Activities of Daily Living in Memory Disorders (STAM) and the Bayer-Activities of Daily Living (B-ADL) informant report, at baseline and 4-year follow-up. Covariates included age, sex, education, Mini-Mental State Examination and Geriatric Depression Scale scores, arthritis, vision impairment, cardiovascular risk, and number of medications. Logistic regressions were conducted to examine the longitudinal association between the 2 types of IADL measures and incident dementia.Logistic regressions showed that performance-based IADL impairment at baseline [odds ratio (OR) = 0.83, 95% confidence interval (CI) 0.77, 0.90; P.001] and decline in performance-based IADL function (OR = 0.82, 95% CI 0.73, 0.91; P.001) were associated with incident dementia over 4 years, with the association provided by the STAM being statistically significant over and above the B-ADL.Performance-based measures of IADL can predict progression to dementia over 4 years beyond that provided by an informant report of IADL. Performance-based IADL measures are promising tools for clinical practice to identify individuals at greater risk of developing dementia.

Background Dementia is a global public health priority with an estimated prevalence of 150 million by 2050, nearly two-thirds of whom will live in the Asia-Pacific region. Dementia creates significant care needs for people with the disease, their families, and carers. iSupport is a self-help platform developed by the World Health Organization (WHO) to provide education, skills training, and support to dementia carers. It has been adapted in some contexts (Australia, India, the Netherlands, and Portugal). Carers using the existing adapted versions have identified the need to have a more user-friendly version that enables them to identify solutions for immediate problems quickly in real time. The iSupport virtual assistant (iSupport VA) is being developed to address this gap and will be evaluated in a randomized controlled trial (RCT). Objective This paper reports the protocol of a pilot RCT evaluating the iSupport VA. Methods Seven versions of iSupport VA will be evaluated in Australia, Indonesia, New Zealand, and Vietnam in a pilot RCT. Feasibility, acceptability, intention to use, and preliminary impact on carer-perceived stress of the iSupport VA intervention will be assessed. Results This study was funded by the e-ASIA Joint Research Program in November 2020. From January to July 2023, we will enroll 140 dementia carers (20 carers per iSupport VA version) for the pilot RCT. The study has been approved by the Human Research Committee, University of South Australia, Australia (203455). Conclusions This protocol outlines how a technologically enhanced version of the WHO iSupport program—the iSupport VA—will be evaluated. The findings from this intervention study will provide evidence on the feasibility and acceptability of the iSupport VA intervention, which will be the basis for conducting a full RCT to assess the effectiveness of the iSupport VA. The study will be an important reference for countries planning to adapt and enhance the WHO iSupport program using digital health solutions. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12621001452886; https://tinyurl.com/afum5tjz International Registered Report Identifier (IRRID) PRR1-10.2196/33572

ObjectiveTo determine whether severe perivascular space (PVS) dilation is associated with longitudinal cognitive decline and incident dementia over 4 and 8 years, respectively, we analyzed data from a prospective cohort study.MethodsA total of 414 community-dwelling older adults aged 72–92 years were assessed at baseline and biennially for up to 8 years, with cognitive assessments, consensus dementia diagnoses, and 3T MRI. The numbers of PVS in 2 representative slices in the basal ganglia (BG) and centrum semiovale (CSO) were counted and severe PVS pathology defined as the top quartile. The effects of severe PVS pathology in either region or both regions and those with severe BG PVS and severe CSO PVS were examined. White matter hyperintensity volume, cerebral microbleed number, and lacune number were calculated.ResultsParticipants with severe PVS pathology in both regions or in the CSO alone had greater decline in global cognition over 4 years, even after adjustment for the presence of other small vessel disease neuroimaging markers. The presence of severe PVS pathology in both regions was an independent predictor of dementia across 8 years (odds ratio 2.91, 95% confidence interval 1.43–5.95, p = 0.003). The presence of severe PVS pathology in all groups examined was associated with greater dementia risk at either year 4 or 6.ConclusionsSevere PVS pathology is a marker for increased risk of cognitive decline and dementia, independent of other small vessel disease markers. The differential cognitive associations for BG and CSO PVS may represent differences in their underlying pathology.

Background Subjective cognitive complaints (SCCs) are a risk factor for dementia; however, little is known about their trajectories. Method Participants were 873 older adults (mage = 78.65 years; 55% females) from the Sydney Memory and Ageing Study that were followed-up biennially. SCCs were measured using the six-item Memory Complaint Questionnaire. Associations between initial level of SCC reporting, linear change in SCC reporting, and change in global cognition over 6 years was examined using latent growth curve analysis. Risk of dementia was examined over 10 years using Cox regression. Results After controlling for demographics, mood and personality, results revealed a negative longitudinal association between the slope of SCCs and the slope of global cognition scores (b = -0.01, p = 0.005, β = -0.44), such that participants who reported increasing SCCs showed a steeper rate of decline in global cognition over 6 years. Cox regression also revealed participants who reported increasing SCCs had a nearly fourfold increased risk of developing dementia over 10 years (hazard ratio 3.70, 1.24-11.01). Conclusion This study explored whether initial levels of, and change in, SCCs over time are associated with both cognitive decline and risk of dementia. These findings are clinically relevant as GPs should note patients reporting increasing SCCs as they may be at greater risk of cognitive decline and incident dementia.

Clinical quality registries are increasingly utilised to monitor and improve healthcare quality. Opt-out consent is recommended to maximise participation and ensure validity of data, however, presents specific considerations when including persons with impaired decision-making abilities. This paper describes the innovative Australian Dementia Network Registry recruitment framework designed to optimise inclusion of people with dementia and mild cognitive impairment.

ENIGMA-CNV working group., Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function., 1000BRAINS: The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 945539 (Human Brain Project SGA3; Amunts, Caspers, Cichon). Brainscale: The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret I. Boomsma), 51.02.060 (Hilleke E. Hulshoff Pol), 668.772 (Dorret I. Boomsma and Hilleke E. Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret I. Boomsma), the European Research Council (ERC-230374) (Dorret I. Boomsma), High Potential Grant Utrecht University (Hilleke E.Hulshoff Pol) and NWO Brain and Cognition 433-09-220 (Hilleke E.Hulshoff Pol). Betula: The Betula study was funded by the Knut and Alice Wallenberg (KAW) foundation (Nyberg). The Freesurfer segmentations on the Betula sample were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N (in Umeå, Sweden), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers from the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud University Medical Centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received support from the participating departments and centres and from external grants, that is, the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland and the Netherlands Organization for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 602450 (IMAGEMEND), 278948 (TACTICS) and 602805 (Aggressotype), as well as from the European Community’s Horizon 2020 programme under grant agreement no. 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. deCODE genetics: deCODE genetics acknowledges support from the Innovative Medicines Initiative Joint Undertaking under grant agreement nos. 115008 (NEWMEDS) and 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007-2013), EU-FP7-funded grant agreement no. 602450 (IMAGEMEND) and EU-funded FP7-People-2011-IAPP grant agreement no. 286213 (PsychDPC). Dublin: This work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and grant SFI08/IN.1/B1916-Corvin to Aidan C. Corvin). ECHO-DEFINE: The ECHO study acknowledges funding from a Medical Research Council (MRC) Centre Grant to Michael J. Owen (G0801418), the Wellcome Trust (Institutional Strategic Support Fund (ISSF) to van den Bree and Clinical Research Training Fellowship to Joanne L. Doherty), the Waterloo Foundation (WF 918-1234 to van den Bree), the Baily Thomas Charitable Fund (2315/1 to van den Bree), National Institute of Mental Health (NIMH 5UO1MH101724 to van den Bree and Michael J. Owen), the IMAGINE-2 study (funded by the MRC (MR/T033045/1) to van den Bree, Jeremy Hall and Michael J. Owen), the IMAGINE-ID study (funded by MRC (MR/N022572/1) to Jeremy Hall, van den Bree and Owen). The DEFINE study was supported by a Wellcome Trust Strategic Award (100202/Z/12/Z) to Michael J. Owen. ENIGMA: ENIGMA is supported in part by NIH grants U54 EB20403, R01MH116147 and R56AG058854. NIA T32AG058507; NIH/NIMH 5T32MH073526. EPIGEN-Dublin: The EPIGEN-Dublin cohort was supported by a Science Foundation Ireland Research Frontiers Programme award (08/RFP/GEN1538). EPIGEN-UK (Sisodiya): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner. GAP: This work was supported by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. GOBS: The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111 and R01 MH083824, with work conducted in part in facilities constructed under the support of NIH grant C06 RR020547. GSP: Data were in part provided by the Brain Genomics Superstruct Project (GSP) of Harvard University and Massachusetts General Hospital (MGH) (Principal Investigators: Randy Buckner, Jordan Smoller and Joshua Roffman), with support from the Center for Brain Science Neuroinformatics Research Group, Athinoula A. Martinos Center for Biomedical Imaging, Center for Genomic Medicine and Stanley Center for Psychiatric Research. Twenty individual investigators at Harvard and MGH generously contributed data to the overall project. We would like to thank Randy Buckner for insightful comments and feedback on this work. HUBIN: The HUBIN study was financed by the Swedish Research Council (K2010-62X-15078-07-2, K2012-61X-15078-09-3, 521-2014-3487 K2015-62X-15077-12-3, 2017-00949), the regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet. HUNT: The HUNT study is a collaboration between HUNT Research Centre (Faculty of Medicine and Movement Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), Human Brain Project (HBP SGA 2, 785907),the FP7 projects IMAGEMEND(602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EUAIMS (115300-2), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152, 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL 01EE1406A, 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants, SM 80/7-2, SFB 940/2), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, ANR-12-SAMA-0004), the Eranet Neuron (ANR-18-NEUR00002-01), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1) and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. Lifespan: The study is funded by the Research Council of Norway (230345, 288083 and 223273). NCNG: NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the Research Council of Norway, to le Hellard, Steen and Espeseth. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to Arvid Lundervold, Grant 911397 and 911687 to Astri Johansen Lundervold). NTR: The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organisation for Health Research and Development (ZonMW) grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004,463-06-001, 451-04-034, 400-05-717, Addiction-31160008, 016-115-035, 481-08-011, 056-32-010, Middelgroot-911-09-032, OCW_NWO Gravity programme—024.001.003, NWO-Groot 480-15-001/674, Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007 and 184.033.111); Spinozapremie (NWO-56-464-14192), KNAW Academy Professor Award (PAH/6635) and University Research Fellow grant (URF) to Dorret I. Boomsma; Amsterdam Public Health research institute (former EMGO+), Neuroscience Amsterdam research institute (former NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Programme (FP7- HEALTH-F4-2007-2013, grant 01413: ENGAGE and grant 602768: ACTION); the European Research Council (ERC Starting 284167, ERC Consolidator 771057, ERC Advanced 230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the National Institutes of Health (NIH, R01D0042157-01A1, R01MH58799-03, MH081802, DA018673, R01 DK092127-04, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by NWO through grant 2018/EW/00408559, BiG Grid, the Dutch e-Science Grid and SURFSARA. OATS: The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Ageing Well, Ageing Productively Programme (ID No. 401162) and NHMRC Project Grants (ID Nos. 1045325 and 1085606). This research was facilitated through Twins Research Australia, a national resource in part supported by an NHMRC Centre for Research Excellence Grant (ID No.: 1079102). We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organization Flagship Collaboration Fund Grant. Osaka: Osaka study was supported by the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS: Grant Number JP18dm0207006), Brain/MINDS& beyond studies (Grant Number JP20dm0307002) and Health and Labour Sciences Research Grants for Comprehensive Research on Persons with Disabilities (Grant Number JP20dk0307081) from the Japan Agency for Medical Research and Development (AMED), Grants-in-Aid for Scientific Research (KAKENHI; Grant Numbers JP25293250 and JP16H05375). Some computations were performed at the Research Center for Computational Science, Okazaki, Japan. PAFIP: The PAFIP study was supported by Instituto de Salud Carlos III, FIS 00/3095, 01/3129, PI020499, PI060507, PI10/00183, the SENY Fundació Research Grant CI2005-0308007 and the FundaciónMarqués de Valdecilla API07/011. Biological samples from our cohort were stored at the Valdecilla Biobank and genotyping services were conducted at the Spanish ‘Centro Nacional de Genotipado’ (CEGEN-ISCIII). MCIC/COBRE: The study is funded by the National Institutes of Health studies R01EB006841, P20GM103472 and P30GM122734 and Department of Energy DE-FG02-99ER62764. PING: Data collection and sharing for the Paediatric Imaging, Neurocognition and Genetics (PING) Study (National Institutes of Health Grant RC2DA029475) were funded by the National Institute on Drug Abuse and the Eunice Kennedy Shriver National Institute of Child Health & Human Development. A full list of PING investigators is at http://pingstudy.ucsd.edu/investigators.html. QTIM: The QTIM study was supported by the National Institute of Child Health and Human Development (R01 HD050735) and the National Health and Medical Research Council (NHMRC 486682, 1009064), Australia. Genotyping was supported by NHMRC (389875). Medland is supported in part by an NHMRC fellowship (APP1103623). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide single-nucleotide polymorphism typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. StrokeMRI: StrokeMRI was supported by the Norwegian ExtraFoundation for Health and Rehabilitation(2015/FO5146), the Research Council of Norway (249795, 262372), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Department of Psychology, University of Oslo. Sydney MAS: The Sydney Memory and Aging Study (Sydney MAS) is funded by National and HealthMedical Research Council (NHMRC) Programme and Project Grants (ID350833, ID568969 and ID109308). We also thank the Sydney MAS participants and the Research Team. SYS: The SYS Study is supported by Canadian Institutes of Health Research. TOP: Centre of Excellence: RCN #23273 and RCN #226971. Part of this work was performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT) (tsd-drift@usit.uio.no). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7-PEOPLE-2013-COFUND) under grant agreement no. 609020—Scientia Fellows; the Research Council of Norway (RCN) #276082—A lifespan perspective on mental illness: toward precision medicine using multimodal brain imaging and genetics. Ida E. Sønderby and Rune Bøen are supported by South-Eastern Norway Regional Health Authority (#2020060). Ida E. Sønderby and Ole A. Andreassen have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement no. 847776 (CoMorMent project) and the KG Jebsen Foundation (SKGJ-MED-021). UCLA_UMCU: The UCLA_UMCU cohort comprises of six studies which were supported by National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) (20244 to Prof. Hillegers), The Netherlands Organisation for Health Research and Development (ZonMw) (908-02-123 to Prof. Hulshoff Pol), and Netherlands Organisation for Scientific Research (NWO 9120818 and NWO-VIDI 917-46-370 to Prof. Hulshoff Pol). The GROUP study was funded through the Geestkracht programme of the Dutch Health Research Council (ZonMw, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly and Janssen Cilag) and universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ inGeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord-Holland-Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia Psycho-medical Center, The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh, voor Geestelijke Gezondheid, Mondriaan, Virenzeriagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-JozefKortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions: Altrecht, GGZ Centraal and Delta.). UK Biobank: This work made use of data sharing from UK Biobank (under project code 27412). Others: Work by Pierre Vanderhaeghen was funded by Grants of the European Research Council (ERC Adv Grant GENDEVOCORTEX), the EOS Programme, the Belgian FWO, the AXA Research Fund and the Belgian Queen Elizabeth Foundation. Ikuo K. Suzuki was supported by a postdoctoral fellowship of the FRS/FNRS.

Addressing midlife hearing loss could prevent up to 9% of new cases of dementia, the highest of any potentially modifiable risk factor identified in the 2017 commissioned report in The Lancet. In Australia, hearing loss is the second-most common chronic health condition in older people, affecting 74% of people aged over 70. Estimates indicate that people with severe hearing loss are up to 5-times more likely to develop dementia, but these estimates vary between studies due to methodological limitations. Using data from the Sydney Memory and Aging Study, in which 1,037 Australian men and women aged between 70 and 90 years were enrolled and completed biennial assessments from 2005-2017, investigations between hearing loss and baseline cognitive performance as well as longitudinal risk of neurocognitive disorder were undertaken. Individuals who reported moderate-to-severe hearing difficulties had poorer cognitive performances in the domains of Attention/Processing Speed and Visuospatial Ability, and on an overall index of Global Cognition, and had a 1.5-times greater risk for the neurocognitive disorder during 6-years' follow-up. Hearing loss independently predicted risk for MCI but not dementia. The presence of hearing loss is an important consideration for neuropsychological case formulation in older adults with cognitive impairment. Hearing loss may increase cognitive load, resulting in observable cognitive impairment on neuropsychological testing. Individuals with hearing loss who demonstrate impairment in non-amnestic domains may experience benefits from the provision of hearing devices; This study provides support for a randomized control trial of hearing devices for improvement of cognitive function in this group.

Hip fracture trajectories have not been examined for older adults in aged care or living in the community. Trajectories of health care use were defined by distinct predictive factors. These results can inform the development of targeted strategies to reduce health service use following hip fracture. To examine hospital service use trajectories of older adults who were hospitalised for hip fracture and living in a residential aged care facility (RACF) or the community, and to identify factors predictive of trajectory group membership. These findings may inform future programmes aimed at reducing unexpected hospitalisations and subsequently reduce health care costs. A group-based trajectory analysis of hospitalisations was conducted for adults aged ≥ 65 years hospitalised for hip fracture during 2008–2009 in New South Wales, Australia. Linked hospitalisation and RACF data were examined for a 5-year period. Group-based trajectory models were derived for RACF and community-dwelling older adults based on the number of subsequent hospital admissions following the index hip fracture. Multinomial logistic regression examined predictors of trajectory group membership for subsequent hospital admissions. There were 5752 hip fracture hospitalisations, with two-thirds of hip fractures occurring in community-dwellers. Key predictors of trajectory group membership for both RACF residents and community-dwellers were age group, sex, hospital length of stay and cognitive impairment. Assistance with activities of daily living and complex health care needs were also predictive of group membership in RACF residents. Location of residence and time to move to a RACF were additional predictors of group membership for community-dwellers. Health service use trajectories differed for RACF residents and community-dwellers; however, there were similar patient characteristics that defined trajectory group membership. Low users of hospital services living in RACFs or the community included older adults with generally unfavourable health conditions, potentially indicating that palliative care or advanced care directives and community-care initiatives, respectively, have played a part in the lowered frequency of rehospitalisation.

IntroductionFall injuries are one of the leading causes of hospitalisation for adults aged ≥65 years. Distinguishing key characteristics of older adults who are either living in aged care or in the community who have multiple hospital readmissions after a fall injury may inform targeted approaches to the prevention of hospital readmissions. Objectives and ApproachTo examine trajectories of hospital readmission of older adults living in aged care or the community after a fall injury hospitalisation and to identify factors predictive of trajectory group membership. A group-based trajectory analysis of hospital readmissions of adults aged ≥65 years who had a fall injury hospitalisation during 2008-09 in New South Wales, Australia was conducted. Linked hospitalisation and aged care data were examined for a 5 year period to 2013. Group-based trajectory models were derived based on number of subsequent readmissions following the index admission. Multinominal logistic regression examined predictors of trajectory group membership. ResultsThere were 24,729 fall injury hospitalisations; 78.8% of fallers were living in the community and 21.2% in aged care. Five distinct trajectory groups were identified for community-living (i.e. Moderate-declining, Chronic, Low-constant, Low-declining, and High users) and four trajectory groups for aged care residents (i.e. Low, Moderate-declining, Moderate-chronic, and High users). Key predictors of trajectory group membership for both community-living and aged care residents were age group, number of comorbidities, and dementia status. For aged care residents, depression, assistance with activities of daily living, and number of subsequent fall injury admissions were also predictors of group membership, with time to move to an aged care facility a predictor of group membership for community-living. Conclusion / ImplicationsIdentifying trajectories of ongoing hospital use informs targeting of strategies to reduce hospital admissions and design of services to allow community-living individuals to remain as long as possible within their own residence.

Background Dementia shows sex difference in its epidemiology. Childbirth, a distinctive experience of women, is associated with the risk for various diseases. However, its association with the risk of dementia in women has rarely been studied. Methods We harmonized and pooled baseline data from 11 population-based cohorts from 11 countries over 3 continents, including 14,792 women aged 60 years or older. We investigated the association between parity and the risk of dementia using logistic regression models that adjusted for age, educational level, hypertension, diabetes mellitus, and cohort, with additional analyses by region and dementia subtype. Results Across all cohorts, grand multiparous (5 or more childbirths) women had a 47% greater risk of dementia than primiparous (1 childbirth) women (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.10–1.94), while nulliparous (no childbirth) women and women with 2 to 4 childbirths showed a comparable dementia risk to primiparous women. However, there were differences associated with region and dementia subtype. Compared to women with 1 to 4 childbirths, grand multiparous women showed a higher risk of dementia in Europe (OR = 2.99, 95% CI = 1.38–6.47) and Latin America (OR = 1.49, 95% CI = 1.04–2.12), while nulliparous women showed a higher dementia risk in Asia (OR = 2.15, 95% CI = 1.33–3.47). Grand multiparity was associated with 6.9-fold higher risk of vascular dementia in Europe (OR = 6.86, 95% CI = 1.81–26.08), whereas nulliparity was associated with a higher risk of Alzheimer disease (OR = 1.91, 95% CI 1.07–3.39) and non-Alzheimer non-vascular dementia (OR = 3.47, 95% CI = 1.44–8.35) in Asia. Conclusion Parity is associated with women’s risk of dementia, though this is not uniform across regions and dementia subtypes.

© 2020 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's AssociationIntroduction: Non-pharmacological treatments (NPTs) have the potential to improve meaningful outcomes for older people at risk of, or living with dementia, but research often lacks methodological rigor and continues to produce mixed results. Methods: In the current position paper, experts in NPT research have specified treatment targets, aims, and ingredients using an umbrella framework, the Rehabilitation Treatment Specification System. Results: Experts provided a snapshot and an authoritative summary of the evidence for different NPTs based on the best synthesis efforts, identified main gaps in knowledge and relevant barriers, and provided directions for future research. Experts in trial methodology provide best practice principles and recommendations for those working in this area, underscoring the importance of prespecified protocols. Discussion: We conclude that the evidence strongly supports various NPTs in relation to their primary targets, and discuss opportunities and challenges associated with a unifying theoretical framework to guide future efforts in this area.

Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent need for methods that can overcome these challenges to model this complex data. At present there is no cure for dementia and no treatment that can successfully change the course of the disease. Machine learning models that can predict the time until a patient develops dementia are important tools in helping understand dementia risks and can give more accurate results than traditional statistical methods when modelling high-dimensional, heterogeneous, clinical data. This work compares the performance and stability of ten machine learning algorithms, combined with eight feature selection methods, capable of performing survival analysis of high-dimensional, heterogeneous, clinical data. We developed models that predict survival to dementia using baseline data from two different studies. The Sydney Memory and Ageing Study (MAS) is a longitudinal cohort study of 1037 participants, aged 70–90 years, that aims to determine the effects of ageing on cognition. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal study aimed at identifying biomarkers for the early detection and tracking of Alzheimer's disease. Using the concordance index as a measure of performance, our models achieve maximum performance values of 0.82 for MAS and 0.93 For ADNI.

Background The relationship of dietary patterns to cognitive health in older adults has attracted much research attention. However, results from existing studies are inconclusive. Objective The aim of this study was to investigate the association between dietary patterns and overall cognitive performance and cognitive change over time. Design This analysis was conducted as part of the longitudinal Sydney Memory and Ageing study with six years follow up. Mediterranean diet and Dietary Approaches to Stop Hypertension (DASH) diet scores were generated based on dietary intake for each individual, assessed by the Dietary Questionnaire for Epidemiological Studies Version 2. Participants/Setting This longitudinal study comprised 1037 community dwelling non-demented participants aged 70-90 years at baseline (September 2005 to December 2007), recruited from Sydney, Australia. Main outcome measures Neuropsychological tests assessed global cognition and 6 cognitive domains on four occasions, at baseline and 2, 4 and 6 years later. Statistical analyses performed Linear mixed model analyses were conducted to examine the relationship between dietary scores, food components and overall cognitive function and cognitive change over six years. Results No associations of Mediterranean or DASH dietary scores with overall cognition and cognitive decline over six years were found. Higher intake of legumes and nuts was related to better overall performance in global cognition (β=0.091; 95% CI:0.035, 0.146; P=0.001) and to multiple cognitive domains, and to less decline in global cognition (β=-0.016; 95% CI: -0.032, -0.001; P=0.032). Conclusion Study findings suggest that greater consumption of legumes and nuts maybe important to slow cognitive decline with age.

Background Dementia was identified as a priority area for the development of a Clinical Quality Registry (CQR) in Australia in 2016. The Australian Dementia Network (ADNeT) Registry is being established as part of the ADNeT initiative, with the primary objective of collecting data to monitor and enhance the quality of care and patient outcomes for people diagnosed with either dementia or Mild Cognitive Impairment (MCI). A secondary aim is to facilitate the recruitment of participants into dementia research and trials. This paper describes the Registry protocol. Methods The ADNeT Registry is a prospective CQR of patients newly diagnosed with either dementia or MCI. Eligible patients will be identified initially from memory clinics and individual medical specialists (e.g., geriatricians, psychiatrists and neurologists) involved in the diagnosis of dementia. Participants will be recruited using either an opt-out approach or waiver of consent based on three key determinants (capacity, person responsible, and communication of diagnosis). Data will be collected from four sources: participating sites, registry participants, carers, and linkage with administrative datasets. It is anticipated that the Registry will recruit approximately 10,000 participants by the end of 2023. The ADNeT registry will be developed and implemented to comply with the national operating principles for CQRs and governed by the ADNeT Registry Steering Committee. Discussion The ADNeT Registry will provide important data on current clinical practice in the diagnosis, treatment and care of people with dementia and MCI in Australia as well as long-term outcomes among these people. These data will help to identify variations in clinical practice and patient outcomes and reasons underlying these variations, which in turn, will inform the development of interventions to improve care and outcomes for people with dementia and MCI.

Objectives To examine the role of frailty in risk of re-hospitalisation and mortality for aged care residents following a fall injury hospitalisation. Methods Retrospective analysis of linked hospitalisation and aged care data of adults aged ≥65 years residing in aged care. A semi-competing risk analysis examined risk of hospital readmission. Results Residents who had intermediate or high frailty, who were aged 70-79 or 80-89 years, who had 1-2 or ≥3 comorbidities, sustained a hip fracture, and who had either low, moderate or high complex health-care requirements had a higher risk of being readmitted to hospital. Frailty was not associated with mortality for those with no hospital readmission or mortality after readmission. Conclusions Frailty is an important prognostic factor associated with readmission for residents of aged care hospitalised for a fall injury. Frailty screening could assist to identify people at a high risk of re-hospitalisation following a fall injury.

It is unclear what non-pharmacological interventions to prevent cognitive decline should comprise. We systematically reviewed lifestyle and psychosocial interventions that aimed to reduce cognitive decline in healthy people aged 50+, and people of any age with Subjective Cognitive Decline or Mild Cognitive Impairment. We narratively synthesised evidence, prioritising results from studies rated as at lower Risk of Bias (ROB) and assigning Centre for Evidence Based Medicine grades. We included 64 papers, describing: psychosocial (n = 12), multi-domain (n = 10), exercise (n = 36), and dietary (n = 6) interventions. We found Grade A evidence that over 4+ months: aerobic exercise twice weekly had a moderate effect on global cognition in people with/ without MCI; and interventions that integrate cognitive and motor challenges (e.g. dance, dumb bell training) had small to moderate effects on memory or global cognition in people with MCI. We found Grade B evidence that 4+ months of creative art or story-telling groups in people with MCI; 6 months of resistance training in people with MCI and a two-year, dietary, exercise, cognitive training and social intervention in people with or without MCI had small, positive effects on global cognition. Effects for some intervention remained up to a year beyond facilitated sessions.