A self-report risk index to predict occurrence of dementia in three independent cohorts of older adults: The ANU-ADRI

Background and Aims: The Australian National University AD Risk Index (ANU-ADRI, http://anuadri.anu.edu.au) is a self-report risk index developed using an evidence-based medicine approach to measure risk of Alzheimer's disease (AD). We aimed to evaluate the extent to which the ANU-ADRI can predict the risk of AD in older adults and to compare the ANU-ADRI to the dementia risk index developed from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study for middle-aged cohorts. Methods: This study included three validation cohorts, i.e., the Rush Memory and Aging Study (MAP) (n = 903, age ≥53 years), the Kungsholmen Project (KP) (n = 905, age ≥75 years), and the Cardiovascular Health Cognition Study (CVHS) (n = 2496, age ≥65 years) that were each followed for dementia. Baseline data were collected on exposure to the 15 risk factors included in the ANU-ADRI of which MAP had 10, KP had 8 and CVHS had 9. Risk scores and C-statistics were computed for individual participants for the ANU-ADRI and the CAIDE index. Results: For the ANU-ADRI using available data, the MAP study c-statistic was 0.637 (95% CI 0.596-0.678), for the KP study it was 0.740 (0.712-0.768) and for the CVHS it was 0.733 (0.691-0.776) for predicting AD. When a common set of risk and protective factors were used c-statistics were 0.689 (95% CI 0.650-0.727), 0.666 (0.628-0.704) and 0.734 (0.707-0.761) for MAP, KP and CVHS respectively. Results for CAIDE ranged from c-statistics of 0.488 (0.427-0.554) to 0.595 (0.565-0.625). Conclusion: A composite risk score derived from the ANU-ADRI weights including 8-10 risk or protective factors is a valid, self-report tool to identify those at risk of AD and dementia. The accuracy can be further improved in studies including more risk factors and younger cohorts with long-term follow-up. © 2014 Anstey et al

Development of the CogDrisk tool to assess risk factors for dementia

Introduction: We aimed to develop a comprehensive risk assessment tool for Alzheimer's disease (AD), vascular dementia (VaD), and any dementia, that will be applicable in high and low resource settings. Method: Risk factors which can easily be assessed in most settings, and their effect sizes, were identified from an umbrella review, or estimated using meta-analysis where new data were available. Results: Seventeen risk/protective factors met criteria for the algorithm to estimate risk for any dementia including age, sex, education, hypertension, midlife obesity, midlife high cholesterol, diabetes, insufficient physical activity, depression, traumatic brain injury, atrial fibrillation, smoking, social engagement, cognitive engagement, fish consumption (diet), stroke, and insomnia. A version for AD excluded atrial fibrillation and insomnia due to insufficient evidence and included pesticide exposure. There was insufficient evidence for a VaD risk score. Discussion: Validation of the tool on external datasets is planned. The assessment tool will assist with implementing risk reduction guidelines

Development and Concurrent Validity of the Short-Form CogDrisk Dementia Risk Assessment Tool

Evidence-based dementia risk assessment is required to inform individual and policy-level dementia risk reduction interventions. We developed the CogDrisk Short Form (CogDrisk-SF) to assess dementia risk factors, for situations where time and resources are limited. To evaluate concurrent validity with the original CogDrisk, we conducted an online survey using a repeated-measures, counterbalanced design. Community dwelling participants (n = 647, 50.1% were female, mean age 62.2 years, age range 40–89) completed the survey. The mean(sd) score for CogDrisk-SF and the CogDrisk was 9.7 (5.3) and 9.9 (5.5), respectively. The intraclass correlation between the risk score obtained from CogDrisk and CogDrisk-SF was 0.92. Fish intake, insomnia and depression had percentage agreements of 79%, 87% and 89% respectively. Other items had >95% agreement except for loneliness (94%), hypertension (94%), cholesterol (93%), atrial fibrillation (91%) and cognitive activity (90%). Very high agreement between the CogDrisk-SF and original CogDrisk shows that CogDrisk-SF is valid for use in research and clinical practice

A Technology-Enriched Approach to Studying Microlongitudinal Aging Among Adults Aged 18 to 85 Years: Protocol for the Labs Without Walls Study

Background: Traditional longitudinal aging research involves studying the same individuals over a long period, with measurement intervals typically several years apart. App-based studies have the potential to provide new insights into life-course aging by improving the accessibility, temporal specificity, and real-world integration of data collection. We developed a new research app for iOS named Labs Without Walls to facilitate the study of life-course aging. Combined with data collected using paired smartwatches, the app collects complex data including data from one-time surveys, daily diary surveys, repeated game-like cognitive and sensory tasks, and passive health and environmental data. Objective: The aim of this protocol is to describe the research design and methods of the Labs Without Walls study conducted between 2021 and 2023 in Australia. Methods: Overall, 240 Australian adults will be recruited, stratified by age group (18-25, 26-35, 36-45, 46-55, 56-65, 66-75, and 76-85 years) and sex at birth (male and female). Recruitment procedures include emails to university and community networks, as well as paid and unpaid social media advertisements. Participants will be invited to complete the study onboarding either in person or remotely. Participants who select face-to-face onboarding (n=approximately 40) will be invited to complete traditional in-person cognitive and sensory assessments to be cross-validated against their app-based counterparts. Participants will be sent an Apple Watch and headphones for use during the study period. Participants will provide informed consent within the app and then begin an 8-week study protocol, which includes scheduled surveys, cognitive and sensory tasks, and passive data collection using the app and a paired watch. At the conclusion of the study period, participants will be invited to rate the acceptability and usability of the study app and watch. We hypothesize that participants will be able to successfully provide e-consent, input survey data through the Labs Without Walls app, and have passive data collected over 8 weeks; participants will rate the app and watch as user-friendly and acceptable; the app will allow for the study of daily variability in self-perceptions of age and gender; and data will allow for the cross-validation of app- and laboratory-based cognitive and sensory tasks. Results: Recruitment began in May 2021, and data collection was completed in February 2023. The publication of preliminary results is anticipated in 2023. Conclusions: This study will provide evidence regarding the acceptability and usability of the research app and paired watch for studying life-course aging processes on multiple timescales. The feedback obtained will be used to improve future iterations of the app, explore preliminary evidence for intraindividual variability in self-perceptions of aging and gender expression across the life span, and explore the associations between performance on app-based cognitive and sensory tests and that on similar traditional cognitive and sensory tests

The use of driver screening tools to predict self-reported crashes and incidents in older drivers

There is a clear need to identify older drivers at increased crash risk, without additional burden on the individual or licensing system. Brief off-road screening tools have been used to identify unsafe drivers and drivers at risk of losing their license. The aim of the current study was to evaluate and compare driver screening tools in predicting prospective self-reported crashes and incidents over 24 months in drivers aged 60 years and older. 525 drivers aged 63–96 years participated in the prospective Driving Aging Safety and Health (DASH) study, completing an on-road driving assessment and seven off-road screening tools (Multi-D battery, Useful Field of View, 14-Item Road Law, Drive Safe, Drive Safe Intersection, Maze Test, Hazard Perception Test (HPT)), along with monthly self-report diaries on crashes and incidents over a 24-month period. Over the 24 months, 22% of older drivers reported at least one crash, while 42% reported at least one significant incident (e.g., near miss). As expected, passing the on-road driving assessment was associated with a 55% [IRR 0.45, 95% CI 0.29–0.71] reduction in self-reported crashes adjusting for exposure (crash rate), but was not associated with reduced rate of a significant incident. For the off-road screening tools, poorer performance on the Multi-D test battery was associated with a 22% [IRR 1.22, 95% CI 1.08–1.37] increase in crash rate over 24 months. Meanwhile, all other off-road screening tools were not predictive of rates of crashes or incidents reported prospectively. The finding that only the Multi-D battery was predictive of increased crash rate, highlights the importance of accounting for age-related changes in vision, sensorimotor skills and cognition, as well as driving exposure, in older drivers when using off-road screening tools to assess future crash risk

Associations Between Planned Exercise, Walking, Incidental Physical Activity, and Habit Strength in Older People: A Cross-Sectional Study

Habits play an important role in physical activity (PA) engagement; however, these associations in older people are not well understood. The present study aimed to investigate the relationship between engagement in types of PA and their automaticity in older people, using an observational, cross-sectional design. Current hours engaged in planned exercise (excluding walking), planned walking, and incidental activities and the automaticity of those PA behaviors were measured in 127 community-dwelling Australians aged 65 years and older via an online questionnaire. After controlling for demographic and health factors (age, gender, education level, body mass index, history of falls, and anxiety and depression symptoms), higher automaticity scores were associated with more hours undertaking planned walking and incidental activity but not planned exercise. Although preliminary, these findings indicate that the role of habit in maintaining PA in older people may, therefore, differ depending on the type of activity

MyCOACH (COnnected Advice for Cognitive Health): a digitally delivered multidomain intervention for cognitive decline and risk of dementia in adults with mild cognitive impairment or subjective cognitive decline–study protocol for a randomised controlled trial

Introduction Digital health interventions are cost-effective and easily accessible, but there is currently a lack of effective online options for dementia prevention especially for people at risk due to mild cognitive impairment (MCI) or subjective cognitive decline (SCD). Methods and analysis MyCOACH (COnnected Advice for Cognitive Health) is a tailored online dementia risk reduction programme for adults aged ≥65 living with MCI or SCD. The MyCOACH trial aims to evaluate the programme’s effectiveness in reducing dementia risk compared with an active control over a 64-week period (N=326). Eligible participants are randomly allocated to one of two intervention arms for 12 weeks: (1) the MyCOACH intervention programme or (2) email bulletins with general healthy ageing information (active control). The MyCOACH intervention programme provides participants with information about memory impairments and dementia, memory strategies and different lifestyle factors associated with brain ageing as well as practical support including goal setting, motivational interviewing, brain training, dietary and exercise consultations, and a 26-week post-intervention booster session. Follow-up assessments are conducted for all participants at 13, 39 and 65 weeks from baseline, with the primary outcome being exposure to dementia risk factors measured using the Australian National University-Alzheimer’s Disease Risk Index. Secondary measures include cognitive function, quality of life, functional impairment, motivation to change behaviour, self-efficacy, morale and dementia literacy. Ethics and dissemination Ethical approval was obtained from the University of New South Wales Human Research Ethics Committee (HC210012, 19 February 2021). The results of the study will be disseminated in peer-reviewed journals and research conferences

CogDrisk, ANU-ADRI, CAIDE, and LIBRA Risk Scores for Estimating Dementia Risk

Importance: While the Australian National University-Alzheimer Disease Risk Index (ANU-ADRI), Cardiovascular Risk Factors, Aging, and Dementia (CAIDE), and Lifestyle for Brain Health (LIBRA) dementia risk tools have been widely used, a large body of new evidence has emerged since their publication. Recently, Cognitive Health and Dementia Risk Index (CogDrisk) and CogDrisk for Alzheimer disease (CogDrisk-AD) risk tools have been developed for the assessment of dementia and AD risk, respectively, using contemporary evidence; comparison of the relative performance of these risk tools is limited. Objective: To evaluate the performance of CogDrisk, ANU-ADRI, CAIDE, LIBRA, and modified LIBRA (LIBRA with age and sex estimates from ANU-ADRI) in estimating dementia and AD risks (with CogDrisk-AD and ANU-ADRI). Design, Setting, and Participants: This population-based cohort study obtained data from the Rush Memory and Aging Project (MAP), the Cardiovascular Health Study Cognition Study (CHS-CS), and the Health and Retirement Study-Aging, Demographics and Memory Study (HRS-ADAMS). Participants who were free of dementia at baseline were included. The factors were component variables in the risk tools that included self-reported baseline demographics, medical risk factors, and lifestyle habits. The study was conducted between November 2021 and March 2023, and statistical analysis was performed from January to June 2023. Main outcomes and measures: Risk scores were calculated based on available factors in each of these cohorts. Area under the receiver operating characteristic curve (AUC) was calculated to measure the performance of each risk score. Multiple imputation was used to assess whether missing data may have affected estimates for dementia risk. Results: Among the 6107 participants in 3 validation cohorts included for this study, 2184 participants without dementia at baseline were available from MAP (mean [SD] age, 80.0 [7.6] years; 1606 [73.5%] female), 548 participants without dementia at baseline were available from HRS-ADAMS (mean [SD] age, 79.5 [6.3] years; 288 [52.5%] female), and 3375 participants without dementia at baseline were available from CHS-CS (mean [SD] age, 74.8 [4.9] years; 1994 [59.1%] female). In all 3 cohorts, a similar AUC for dementia was obtained using CogDrisk, ANU-ADRI, and modified LIBRA (MAP cohort: CogDrisk AUC, 0.65 [95% CI, 0.61-0.69]; ANU-ADRI AUC, 0.65 [95% CI, 0.61-0.69]; modified LIBRA AUC, 0.65 [95% CI, 0.61-0.69]; HRS-ADAMS cohort: CogDrisk AUC, 0.75 [95% CI, 0.71-0.79]; ANU-ADRI AUC, 0.74 [95% CI, 0.70-0.78]; modified LIBRA AUC, 0.75 [95% CI, 0.71-0.79]; CHS-CS cohort: CogDrisk AUC, 0.70 [95% CI, 0.67-0.72]; ANU-ADRI AUC, 0.69 [95% CI, 0.66-0.72]; modified LIBRA AUC, 0.70 [95% CI, 0.68-0.73]). The CAIDE and LIBRA also provided similar but lower AUCs than the 3 aforementioned tools (eg, MAP cohort: CAIDE AUC, 0.50 [95% CI, 0.46-0.54]; LIBRA AUC, 0.53 [95% CI, 0.48-0.57]). The performance of CogDrisk-AD and ANU-ADRI in estimating AD risks was also similar. Conclusions and relevance: CogDrisk and CogDrisk-AD performed similarly to ANU-ADRI in estimating dementia and AD risks. These results suggest that CogDrisk and CogDrisk-AD, with a greater range of modifiable risk factors compared with other risk tools in this study, may be more informative for risk reduction

On the role of Rossby wave breaking in quasi‐biennial odulation of the stratospheric polar vortex

The boreal‐winter stratospheric polar vortex is more disturbed when the quasi‐biennial oscillation (QBO) in the lower stratosphere is in its easterly phase (eQBO), and more stable during the westerly phase (wQBO). This so‐called “Holton‐Tan effect” (HTE) is known to involve Rossby waves (RWs) but the details remain obscure. This tropical‐extratropical connection is re‐examined in an attempt to explain its intra‐seasonal variation and its relation to Rossby wave breaking (RWB). Reanalyses in isentropic coordinates from the National Center for Environmental Prediction Climate Forecast System for the 1979 – 2017 period are used to evaluate the relevant features of RWB in the context of waveguide, wave mean‐flow interaction, and the QBO‐induced meridional circulation. During eQBO, the net extratropical wave forcing is enhanced in early winter with ~25% increase in upward propagating PRWs of zonal wavenumber 1 (wave‐1). RWB is also enhanced in the lower stratosphere, characterized by convergent anomalies in the subtropics and at high‐latitudes and strengthened waveguide in between at 20‐40°N, 350‐650 K. In late winter, RWB leads to finite amplitude growth, which hinders upward propagating PRWs of zonal wavenumber 2 and 3 (wave‐2‐3). During wQBO, RWB in association with wave‐2‐3 is enhanced in the upper stratosphere. Wave absorption/mixing in the surf zone reinforces a stable polar vortex in early to middle winter. A poleward confinement of extratropical waveguide in the upper stratosphere forces RWB to extend downward around January. A strengthening of upward propagating wave‐2‐3 follows and the polar‐vortex response switches from reinforcement to disturbance around February, thus a sign reversal of the HTE in late winter

Maintaining level of modifiable dementia risk scores is associated with better cognitive outcomes than increasing risk scores: A population-based prospective cohort study

BACKGROUND: A brain healthy lifestyle, consisting of good cardiometabolic health and being cognitively and socially active in midlife, is associated with a lower risk of cognitive decline years later. However, it is unclear whether lifestyle changes over time also affect the risk for mild cognitive impairment (MCI)/dementia, and rate of cognitive decline. OBJECTIVES: To investigate if lifestyle changes over time are associated with incident MCI/dementia risk and rate of cognitive decline. DESIGN: Population-based prospective cohort study SETTING: Personality and Total Health (PATH) Through Life Study cohort (Australia). PARTICIPANTS: 4,777 participants (50.4% women), recruited between 2000 and 2002, who were 40-44 and 60-64 years old at baseline, without a prevalent dementia diagnosis. Participants had to have cognitive outcome measures available after baseline. MEASUREMENTS: Various measurements (neurocognitive assessment, blood pressure) and survey responses (demographics, cognitive, social, and physical activity, smoking, alcohol consumption, body height and weight, depression, and previous diagnoses) were collected approximately every four years. A brain-healthy lifestyle was operationalized via two well-validated modifiable dementia risk scores, the LIfestyle for BRAin health (LIBRA) score and the modifiable part of the Australian National University Alzheimer's Disease Risk Index (ANU-ADRImod). Their change over time was estimated using latent growth curve modelling, and their association with cognition and incidence of MCI/dementia was investigated using parallel process modelling and Cox regression analysis. RESULTS: Within those aged 60-64 years at baseline (n=2,409), 211 cases of incident MCI/dementia were recorded over a median follow-up time of 12.2 years. On average, individuals' LIBRA and ANU-ADRImod increased (i.e., worsened) over time, but individuals whose scores increased one standard deviation (SD) less had a 19.0-24.6% lower risk for MCI/dementia (hazard ratio (95% confidence interval): LIBRAchange over time=0.754 (0.664-0.857), ANU-ADRImod, change over time=0.810 (0.71-0.915)), while controlling for the risk score at baseline and multiple potential confounders. Various associations between dementia risk score trajectories and cognitive performance trajectories were observed. CONCLUSIONS: Efforts to maintain a brain healthy lifestyle could reduce the risk for MCI or dementia, and slow cognitive decline