Background: Cognitive dispersion, variation in performance across cognitive domains, is posited as a non-invasive and cost-effective marker of early neurodegeneration. Little work has explored associations between cognitive dispersion and Alzheimer’s disease (AD) biomarkers in healthy older adults. Even less is known about the influence or interaction of biomarkers reflecting brain pathophysiology or other risk factors on cognitive dispersion scores. Objective: The main aim of this study was to examine whether higher cognitive dispersion was associated with cerebrospinal fluid (CSF) levels of amyloid-β (Aβ42), total tau (t-tau), phosphorylated tau (p-tau), and amyloid positivity in a cohort of older adults at various severities of AD. A secondary aim was to explore which AD risk factors were associated with cognitive dispersion scores. Methods: Linear and logistic regression analyses explored the associations between dispersion and CSF levels of Aβ42, t-tau, and p-tau and amyloid positivity (Aβ42 < 1000 pg/ml). Relationships between sociodemographics, APOE ɛ4 status, family history of dementia, and levels of depression and dispersion were also assessed. Results: Dispersion did not emerge as associated with any of the analytes nor amyloid positivity. Older (β= –0.007, SE = 0.002, p = 0.001) and less educated (β= –0.009, SE = 0.003, p = 0.009) individuals showed greater dispersion. Conclusion: Dispersion was not associated with AD pathology, but was associated with age and years of education, highlighting individual differences in cognitive aging. The use of this metric as a screening tool for existing AD pathology is not supported by our analyses. Follow-up work will determine if dispersion scores can predict changes in biomarker levels and/or positivity status longitudinally.

Objectives: Dispersion in cognitive test performance within a single testing session is proposed as an early marker of poor brain health. Existing research, however, has not investigated factors that may explain individual differences in cognitive dispersion. We investigate the extent to which the Big Five personality traits are associated with cognitive dispersion in older adulthood. Method:To promote transparency and reliability, we applied pre-registration and conceptual replication via coordinated analysis. Drawing data from seven longitudinal studies of aging (Ntotal=33,581; Mage range=56.4-71.2), cognitive dispersion scores were derived from cognitive test results. Independent linear regression models were fit in each study to examine personality traits as predictors of dispersion scores, adjusting for mean cognitive performance and sociodemographics (age, sex, education). Results from individual studies were synthesized using random effects meta-analyses.Results: Synthesized results revealed that openness was positively associated with cognitive dispersion (0.028, 95%CI:[0.003,0.054]). There was minimal evidence for associations between cognitive dispersion and the other personality traits in independent analyses or metaanalyses. Mean cognitive scores were negatively associated with cognitive dispersion across the majority of studies, while socio-demographic variables were not consistently associated with cognitive dispersion.Discussion: Higher levels of openness were associated with greater cognitive dispersion across seven independent samples, indicating that individuals higher in openness had more dispersion across cognitive tests. Further research is needed to investigate mechanisms that may help to explain the link between openness and cognitive dispersion, as well as to identify additional individual factors, beyond personality traits, that may be associated with cognitive dispersion.

Background International comparisons of trajectories of depressive symptoms in older adults are scarce and longitudinal associations with co-morbid conditions not fully understood. Objective To compare trajectories of depressive symptoms from participants living in 10 European Countries and identify ages at which the associations of co-morbid conditions with these trajectories become more relevant. Methods Latent growth curve models were fitted to depressive symptoms scores from participants of the Survey of Health and Retirement in Europe (SHARE) initiative (combined n = 21,253) and co-morbid conditions modelled as time varying covariates. To identify the ages at which the association between co-morbid conditions and depressive symptoms was significant the Johnson-Neyman (JN) technique was used. Results The shape of depressive symptoms trajectories varied between countries, and was highly dependent on modelling decisions. The association between the average number of co-morbidities reported over time and depressive symptoms was consistent and positive across countries and ages. Conclusion International differences in ageing-related trajectories of depressive symptoms emerged. The longitudinal association of co-morbid conditions with trajectories of depressive symptoms was found, but the results overall suggest that modelling decisions could greatly influence the outcomes, and should thus be interpreted with caution.

Background Older adults living in the community may have daily needs for help to perform different types of activities. In developing countries, older adults face the additional challenge of lacking sufficient economic means to face their increasing needs with ageing, and health and social policies may be under pressure. The aim of this study was to assess dependency in the older population from a developing country using a latent class approach to identify heterogeneity in the type of activities in which dependent older adults require help. Methods In this cross-sectional evaluation of dependency, we considered individuals aged 60 years and older from a nationally representative study (N = 5138) in Uruguay. We fitted latent class regressions to analyse dependency, measured by the need for help to perform Activities of Daily Living, adjusted by sociodemographic characteristics. Results Four latent classes were identified, 86.4% of the individuals were identified as non-dependent, 7.4% with help requirements to perform instrumental activities while individuals in the other two classes need help to perform all types of activities with different degrees (4.3 and 1.9%). Less educated women are more likely to be in the group with needs in instrumental activities. Conclusions The heterogeneous patterns of dependency have to be addressed with different services that meet the specific needs of dependent older adults.

Objectives: To assess the heterogeneity of transitions toward dependency in older adults and to explore the robustness of results to different operationalizations of dependency. Method: Using data from people aged 60 years and older from a national representative study in Uruguay ( Encuesta Longitudinal de Protección Social, N = 5071), we fitted multinomial regressions adjusted by sociodemographic and health characteristics to model transitions into dependency and death. We used a harder operationalization with basic activities of daily living (Katz-dependency) and Comprehensive-dependency with basic, instrumental, and advanced activities. Results: Increasing age (RRR = 1.08, CI = [1.05; 1.12], p < .001) and having comorbidities (RRR = 2.16, CI = [1.31; 3.57], p = .003) increased the risk of transition from nondependent to dependent using Katz-dependency. Women with at least two chronic conditions have increased risk of Comprehensive-dependency (RRR = 1.79, CI = [1.15; 2.80], p = .010). Discussion: Inconsistencies in findings emerged when evaluating transitions into dependency with the different measures, which may have social care implications.