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Environmental factors resulting from climate change and air pollution are risk factors for many chronic conditions including dementia. Although research has shown the impacts of air pollution in terms of cognitive status, less is known about the association between climate change and specific health-related outcomes of older people living with dementia. In response, we outline a scoping review protocol to systematically review the published literature regarding the evidence of climate change, including temperature and weather variability, on health-related quality of life, morbidity, mobility, falls, the utilization of health resources, and mortality among older adults living with dementia. This scoping review will be guided by the framework proposed by Arksey and O'Malley. Electronic search (Medline, Embase, PsycINFO, CINAHL, Scopus, Web of Science) using relevant subject headings and synonyms for two concepts (older people with dementia, weather/ climate change). No publication date or other restrictions will be applied to the search strategy. No language restriction will be applied in order to understand the impact of non-English studies in the literature. Eligible studies must include older adults (65+years) with dementia living in the community and investigate the impacts of climate change and/or weather on their health-related quality of life, morbidity, mobility, falls, use of health resources and mortality. Two independent reviewers will screen abstracts and select those for a full-text review, perform these reviews, select articles for retention, and extract data from them in a standardized manner. This data will then be synthesized and interpreted. OSF registration: DOI: 10.17605/OSF.IO/YRFM8., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Astolphi Lima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Evaluating whether genetic susceptibility modifies the impact of lifestyle-related factors on dementia is critical for prevention., Methods: We studied 5170 participants from a French cohort of older persons free of dementia at baseline and followed for up to 17 years. The LIfestyle for BRAin health risk score (LIBRA) including 12 modifiable factors was constructed at baseline (higher score indicating greater risk) and was related to both subsequent cognitive decline and dementia incidence, according to genetic susceptibility to dementia (reflected by the apolipoprotein E [APOE] ε4 allele and a genetic risk score [GRS])., Results: The LIBRA was associated with higher dementia incidence, with no significant effect modification by genetics (hazard ratio for one point score = 1.09 [95% confidence interval, 1.05; 1.13]) in APOE ε4 non-carriers and = 1.15 [1.08; 1.22] in carriers; P = 0.15 for interaction). Similar findings were obtained with the GRS and with cognitive decline., Discussion: Lifestyle-based prevention may be effective whatever the genetic susceptibility to dementia., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Hippocampal neurogenesis (HN) occurs throughout the life course and is important for memory and mood. Declining with age, HN plays a pivotal role in cognitive decline (CD), dementia, and late-life depression, such that altered HN could represent a neurobiological susceptibility to these conditions. Pertinently, dietary patterns (e.g., Mediterranean diet) and/or individual nutrients (e.g., vitamin D, omega 3) can modify HN, but also modify risk for CD, dementia, and depression. Therefore, the interaction between diet/nutrition and HN may alter risk trajectories for these ageing-related brain conditions. Using a subsample (n = 371) of the Three-City cohort-where older adults provided information on diet and blood biobanking at baseline and were assessed for CD, dementia, and depressive symptomatology across 12 years-we tested for interactions between food consumption, nutrient intake, and nutritional biomarker concentrations and neurogenesis-centred susceptibility status (defined by baseline readouts of hippocampal progenitor cell integrity, cell death, and differentiation) on CD, Alzheimer's disease (AD), vascular and other dementias (VoD), and depressive symptomatology, using multivariable-adjusted logistic regression models. Increased plasma lycopene concentrations (OR [95% CI]  =  1.07 [1.01, 1.14]), higher red meat (OR [95% CI]  =  1.10 [1.03, 1.19]), and lower poultry consumption (OR [95% CI]  =  0.93 [0.87, 0.99]) were associated with an increased risk for AD in individuals with a neurogenesis-centred susceptibility. Increased vitamin D consumption (OR [95% CI]  =  1.05 [1.01, 1.11]) and plasma γ-tocopherol concentrations (OR [95% CI]  =  1.08 [1.01, 1.18]) were associated with increased risk for VoD and depressive symptomatology, respectively, but only in susceptible individuals. This research highlights an important role for diet/nutrition in modifying dementia and depression risk in individuals with a neurogenesis-centred susceptibility., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Predicting the individual risk of clinical events using the complete patient history is a major challenge in personalized medicine. Analytical methods have to account for a possibly large number of time-dependent predictors, which are often characterized by irregular and error-prone measurements, and are truncated early by the event. In this work, we extended the competing-risk random survival forests to handle such endogenous longitudinal predictors when predicting event probabilities. The method, implemented in the R package DynForest, internally transforms the time-dependent predictors at each node of each tree into time-fixed features (using mixed models) that can then be used as splitting candidates. The final individual event probability is computed as the average of leaf-specific Aalen-Johansen estimators over the trees. Using simulations, we compared the performances of DynForest to accurately predict an event with (i) a joint modeling alternative when considering two longitudinal predictors only, and with (ii) a regression calibration method that ignores the informative truncation by the event when dealing with a large number of longitudinal predictors. Through an application in dementia research, we also illustrated how DynForest can be used to develop a dynamic prediction tool for dementia from multimodal repeated markers, and quantify the importance of each marker., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Introduction: Diet and exercise influence the risk of cognitive decline (CD) and dementia through the food metabolome and exercise-triggered endogenous factors, which use the blood as a vehicle to communicate with the brain. These factors might act in concert with hippocampal neurogenesis (HN) to shape CD and dementia., Methods: Using an in vitro neurogenesis assay, we examined the effects of serum samples from a longitudinal cohort (n = 418) on proxy HN readouts and their association with future CD and dementia across a 12-year period., Results: Altered apoptosis and reduced hippocampal progenitor cell integrity were associated with exercise and diet and predicted subsequent CD and dementia. The effects of exercise and diet on CD specifically were mediated by apoptosis., Discussion: Diet and exercise might influence neurogenesis long before the onset of CD and dementia. Alterations in HN could signify the start of the pathological process and potentially represent biomarkers for CD and dementia., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Purpose of Review: Worldwide, approximately 50 million people have dementia (mostly Alzheimer's disease). Dementia results from a multicomponent pathophysiology that follows complex dynamics over many years before symptoms become apparent. Nutrition may represent a target of choice for the primary prevention of dementia; however, there is still no firm answer on how to prevent dementia efficiently. We provide a broad overview of recent studies leveraging system biology and life-long epidemiology to address the multidimensionality and dynamical patterns underlying dementia and improve knowledge on the link between nutrition, cardiometabolic health and dementia risk., Recent Findings: The aging of reference population-based cohort studies, the increasing availability of cutting-edge biomarkers (e.g., brain imaging, metabolomics) and the refinement of statistical tools to model complex exposures and dynamical health outcomes have yielded substantial progress in the understanding of dementia. Systems biology coupled with life-course epidemiology will pave the way toward novel precision nutrition approaches for prevention and management of dementia.

Scope: Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome., Methods and Results: A case-control study nested in the prospective Three-City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium-chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE-ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross-validated Area Under the Receiver Operating Curve = 75% [95% CI 70-80%] compared to 62% [95% CI 56-67%]., Conclusions: The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging., (© 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

As with many health constructs, cognition is difficult to measure accurately; it is assessed by multiple psychometric tests. Two approaches are commonly adopted to address this multivariate aspect in longitudinal analyses: the composite score approach summarizes the tests into a single outcome and subsequently analyzes its change; the multivariate approach relates the tests to the underlying cognitive level and simultaneously analyzes its change. We compared the quality of inference of these approaches in a simulation study based on three combinations of tests inspired by two population-based cohorts. In the absence of missing data and with relatively Gaussian psychometric tests, the composite score approach provided similar type-I error rates and statistical power as the multivariate latent process approach. In the more plausible scenario with departures from normality, transformations of each constituent test or of the composite score were required to avoid excess type-I error rates. When missing tests were more likely in cognitively impaired subjects, inference with the composite was not correct. In conclusion, composite scores can be used to assess risk factors for cognitive change provided they are correctly normalized, constituent tests are reliable and the amount of uninformative missing tests remains small. Otherwise, latent variable models are recommended.

In line with declining trends in dementia incidence, we compared the cognitive and functional evolution of 2 "generations" of elderly individuals aged 78-88 years, who were included 10 years apart in the French Personnes Agées Quid cohort (n = 612 in 1991-1992 and n = 628 in 2001-2002) and followed-up for 12 years with assessments of cognition and disability. The impact of specific risk factors on this evolution was evaluated. Differences between the generations in baseline levels and decline over time were estimated using a joint model to account for differential attrition. Compared with the first generation, the second generation had higher performances at baseline on 4 cognitive tests (from P < 0.005). Differences in global cognition, verbal fluency, and processing speed, but not in working memory, were mostly explained by improvement in educational level. The second generation also exhibited less cognitive decline in verbal fluency and working memory. Progression of disability was less over the follow-up period for the second generation than for the first. The cognitive state of this elderly population improved, partially due to improvements in educational level.

Importance: Cardiometabolic risk factors have been associated with an increased risk of dementia; yet, the optimal targets and time window for the management of cardiometabolic health to prevent dementia remain unknown., Objectives: To model concurrently and compare the trajectories of cardiometabolic risk factors up to 14 years preceding diagnosis in individuals with dementia and matched controls free of dementia., Design, Setting, and Participants: A case-control study nested within the Three-City study, a French population-based cohort of older persons (≥65 years), included 6 home visits with neuropsychological testing between 1999 and 2014. Data analysis was performed in September 2017. A total of 785 incident dementia cases and 3140 controls matched by sex, age, educational level, and cohort center at the time of diagnosis were evaluated., Exposures: Repeated measures of body mass index (BMI) and systolic (SBP) and diastolic (DBP) blood pressure, high-density lipoprotein (HDL-C) and low-density lipoprotein cholesterol (LDL-C), triglycerides, and glycemia levels between 1999 and 2014., Main Outcomes and Measures: Incidence of dementia based on systematic detection and validated diagnosis., Results: A total of 785 cases and 3140 controls (2530 [65%] women; mean [SD] age, 76 [5] years) were included in the study. Cases presented a faster decline in BMI, slower increase of SBP and constantly lower DBP. Mean values (95% CI) 14 years before diagnosis (-14 years) and at diagnosis (year 0) for the most common profile were BMI, 26.1 (25.6-26.5) and 24.8 (24.5-25.1) for a case, and 25.7 (25.4-26.1) and 25.3 (25.0-25.5) for a control; for SBP, 135.2 (131.8-138.7) and 142.1 (140.3-143.9) mm Hg for a case, and 135.8 (132.9-138.6) and 144.9 (143.7-146.1) mm Hg for a control; for DBP, 76.5 (74.7-78.5) and 74.0 (73.1-74.9) mm Hg for a case, and 76.7 (75.1-78.3) and 75.0 (74.2-75.7) mm Hg for a control. In contrast, glycemia was higher among cases (mean fasting glucose values [95% CI] at -14 years and year 0: 89.4 [86.9-92.1] and 96.4 [93.7-99.3] mg/dL for a case, and 87.1 [85.1-89.2] and 95.3 [93.5-97.1] mg/dL for a control), with a significant case-control difference from -1.6 to -14 years prior to diagnosis. There were no significant case-control differences in trajectories of blood lipid levels (mean values [95% CI] at -14 years and year 0: for HDL-C, 70.6 [67.6-73.9] and 61.3 [58.9-63.8] mg/dL for a case, and 70.4 [67.5-73.3] and 62.3 [60.2-64.3] mg/dL for a control; for LDL-C: 147.2 [140.5-154.5] and 141.6 [136.6-146.7] mg/dL for a case, and 144.3 [138.7-150.4] and 141.2 [137.5-145.2] mg/dL for a control; for triglycerides: 115.5 [103.6-149.1] and 112.6 [104.8-120.9] mg/dL for a case, and 112.5 [103.8-144.4] and 109.7 [105.0-114.8] mg/dL for a control)., Conclusions and Relevance: In this large cohort of older persons, BMI declined in prodromal dementia, possibly reflecting early preclinical changes. Lower BP prior to dementia may reflect both a consequence and a contributing factor for the disease, whereas higher blood glucose levels may constitute a risk factor for dementia in the older age range. Overall, these findings suggest that elevated glycemia, low BP, and weight loss may be primary targets for the management of cardiometabolic health for primary and secondary prevention of dementia in the older age range.

Importance: Evidence is limited regarding the relation between cardiovascular health level and dementia risk., Objective: To investigate the association between cardiovascular health level, defined using the 7-item tool from the American Heart Association (AHA), and risk of dementia and cognitive decline in older persons., Design, Setting, and Participants: Population-based cohort study of persons aged 65 years or older from Bordeaux, Dijon, and Montpellier, France, without history of cardiovascular diseases or dementia at baseline who underwent repeated in-person neuropsychological testing (January 1999-July 2016) and systematic detection of incident dementia (date of final follow-up, July 26, 2016)., Exposures: The number of the AHA's Life's Simple 7 metrics at recommended optimal level (nonsmoking, body mass index <25, regular physical activity, eating fish twice a week or more and fruits and vegetables at least 3 times a day, cholesterol <200 mg/dL [untreated], fasting glucose <100 mg/dL [untreated], and blood pressure <120/80 mm Hg [untreated]; score range, 0-7) and a global cardiovascular health score (range, 0-14; poor, intermediate, and optimal levels of each metric assigned a value of 0, 1, and 2, respectively)., Main Outcomes and Measures: Incident dementia validated by an expert committee and change in a composite score of global cognition (in standard units, with values indicating distance from population means, 0 equal to the mean, and +1 and -1 equal to 1 SD above and below the mean)., Results: Among 6626 participants (mean age, 73.7 years; 4200 women [63.4%]), 2412 (36.5%), 3781 (57.1%), and 433 (6.5%) had 0 to 2, 3 to 4, and 5 to 7 health metrics at optimal levels, respectively, at baseline. Over a mean follow-up duration of 8.5 (range, 0.6-16.6) years, 745 participants had incident adjudicated dementia. Compared with the incidence rate of dementia of 1.76 (95% CI, 1.38-2.15) per 100 person-years among those with 0 or 1 health metrics at optimal levels, the absolute differences in incident dementia rates for 2, 3, 4, 5, and 6 to 7 metrics were, respectively, -0.26 (95% CI, -0.48 to -0.04), -0.59 (95% CI, -0.80 to -0.38), -0.43 (95% CI, -0.65 to -0.21), -0.93 (95% CI, -1.18 to -0.68), and -0.96 (95% CI, -1.37 to -0.56) per 100 person-years. In multivariable models, the hazard ratios for dementia were 0.90 (95% CI, 0.84-0.97) per additional optimal metric and 0.92 (95% CI, 0.89-0.96) per additional point on the global score. Furthermore, the gain in global cognition associated with each additional optimal metric at baseline was 0.031 (95% CI, 0.009-0.053) standard units at inclusion, 0.068 (95% CI, 0.045-0.092) units at year 6, and 0.072 (95% CI, 0.042-0.102) units at year 12., Conclusions and Relevance: In this cohort of older adults, increased numbers of optimal cardiovascular health metrics and a higher cardiovascular health score were associated with a lower risk of dementia and lower rates of cognitive decline. These findings may support the promotion of cardiovascular health to prevent risk factors associated with cognitive decline and dementia.

Modeling risk-factor trajectories is critical to understanding the natural history of diseases, yet the measurement tools used to assess risk factors often evolve during follow-up in cohorts, and such change prevents longitudinal analyses using standard models. We addressed this issue with a latent process model. Trajectories of average intakes of 5 food families (fish, meat, fruits, vegetables, and carbohydrate-rich foods) were described in prodromal dementia during the 10 years prior to diagnosis of cases and compared with those of controls, using a case-control sample nested within the Three-City Study, Bordeaux, France (1999-2012). Food intakes were measured by 2 or 3 different subquestionnaires across 5 repeated food frequency questionnaires. The sample comprised 205 incident cases and 410 controls matched for age, sex, education, and number of repeated food frequency questionnaires. Intakes of fish, fruits, and vegetables decreased at the approach of diagnosis among cases, suggesting reverse causation. This study demonstrated that the latent process model approach constitutes a powerful framework for modeling risk-factor trajectories, even when measurement tools change sequentially over time. Coupled with a case-control approach to contrast trajectories in prodromal disease versus healthy status, it can help us to understand the dynamic, causal relationships between risk factors and diseases.

Background: Geriatric syndromes (GSs) are often the result of cumulative insults to multiple organ systems and are considered common in older adults. However, their frequency and co-occurrence are not well known in the elderly population. This study aimed to determine the prevalence of several GSs and to analyze the co-occurrence of these syndromes in a general population of elderly individuals., Methods: A cross-sectional analysis of 630 adults aged 75 years or older participating in the 10-year follow-up of the Bordeaux sample of the French Three-City Study was conducted. The following 10 GSs were assessed: physical frailty, dementia and cognitive impairment, depressive symptoms, polymedication, social isolation, thinness, falls, dependence, sensory deficit, and incontinence. The prevalence of the 10 GSs was estimated, and multiple correspondence analysis (MCA) models were used to explore the mutual associations between these GSs., Results: The mean age of the participants was 83.3 years; 69% were women, and 80.5% [95% confidence interval (CI) = 76.3-82.7] had at least one GS. The most frequent GSs were polymedication (50.6% 95%CI = 46.7-54.5) and falls (43.1% 95%CI = 38.4-46.1). The MCA models identified two major dimensions of the 10 GSs: "Dementia-Dependence-Incontinence" and "Frailty-Depression-Isolation.", Conclusions: GSs were very common in this French elderly population and were grouped into two major dimensions: the "Dementia-Dependence-Incontinence" and "Frailty-Depression-Isolation.", (© The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Joint models initially dedicated to a single longitudinal marker and a single time-to-event need to be extended to account for the rich longitudinal data of cohort studies. Multiple causes of clinical progression are indeed usually observed, and multiple longitudinal markers are collected when the true latent trait of interest is hard to capture (e.g., quality of life, functional dependency, and cognitive level). These multivariate and longitudinal data also usually have nonstandard distributions (discrete, asymmetric, bounded, etc.). We propose a joint model based on a latent process and latent classes to analyze simultaneously such multiple longitudinal markers of different natures, and multiple causes of progression. A latent process model describes the latent trait of interest and links it to the observed longitudinal outcomes using flexible measurement models adapted to different types of data, and a latent class structure links the longitudinal and cause-specific survival models. The joint model is estimated in the maximum likelihood framework. A score test is developed to evaluate the assumption of conditional independence of the longitudinal markers and each cause of progression given the latent classes. In addition, individual dynamic cumulative incidences of each cause of progression based on the repeated marker data are derived. The methodology is validated in a simulation study and applied on real data about cognitive aging obtained from a large population-based study. The aim is to predict the risk of dementia by accounting for the competing death according to the profiles of semantic memory measured by two asymmetric psychometric tests., (Copyright © 2015 John Wiley & Sons, Ltd.)

Background: Identifying modifiable lifestyle correlates of cognitive decline and risk of dementia is complex, particularly as few population-based longitudinal studies jointly model these interlinked processes. Recent methodological developments allow us to examine statistically defined sub-populations with separate cognitive trajectories and dementia risks., Methods: Engagement in social, physical, or intellectual pursuits, social network size, self-perception of feeling well understood, and degree of satisfaction with social relationships were assessed in 2854 participants from the Paquid cohort (mean baseline age 77 years) and related to incident dementia and cognitive change over 20-years of follow-up. Multivariate repeated cognitive information was exploited by defining the global cognitive functioning as the latent common factor underlying the tests. In addition, three latent homogeneous sub-populations of cognitive change and dementia were identified and contrasted according to social environment variables., Results: In the whole population, we found associations between increased engagement in social, physical, or intellectual pursuits and increased cognitive ability (but not decline) and decreased risk of incident dementia, and between feeling understood and slower cognitive decline. There was evidence for three sub-populations of cognitive aging: fast, medium, and no cognitive decline. The social-environment measures at baseline did not help explain the heterogeneity of cognitive decline and incident dementia diagnosis between these sub-populations., Conclusions: We observed a complex series of relationships between social-environment variables and cognitive decline and dementia. In the whole population, factors such as increased engagement in social, physical, or intellectual pursuits were related to a decreased risk of dementia. However, in a sub-population analysis, the social-environment variables were not linked to the heterogeneous patterns of cognitive decline and dementia risk that defined the sub-groups.

Clinical and population research on dementia and related neurologic conditions, including Alzheimer's disease, faces several unique methodological challenges. Progress to identify preventive and therapeutic strategies rests on valid and rigorous analytic approaches, but the research literature reflects little consensus on "best practices." We present findings from a large scientific working group on research methods for clinical and population studies of dementia, which identified five categories of methodological challenges as follows: (1) attrition/sample selection, including selective survival; (2) measurement, including uncertainty in diagnostic criteria, measurement error in neuropsychological assessments, and practice or retest effects; (3) specification of longitudinal models when participants are followed for months, years, or even decades; (4) time-varying measurements; and (5) high-dimensional data. We explain why each challenge is important in dementia research and how it could compromise the translation of research findings into effective prevention or care strategies. We advance a checklist of potential sources of bias that should be routinely addressed when reporting dementia research., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort., (© 2014, The International Biometric Society.)

Multivariate ordinal and quantitative longitudinal data measuring the same latent construct are frequently collected in psychology. We propose an approach to describe change over time of the latent process underlying multiple longitudinal outcomes of different types (binary, ordinal, quantitative). By relying on random-effect models, this approach handles individually varying and outcome-specific measurement times. A linear mixed model describes the latent process trajectory while equations of observation combine outcome-specific threshold models for binary or ordinal outcomes and models based on flexible parameterized non-linear families of transformations for Gaussian and non-Gaussian quantitative outcomes. As models assuming continuous distributions may be also used with discrete outcomes, we propose likelihood and information criteria for discrete data to compare the goodness of fit of models assuming either a continuous or a discrete distribution for discrete data. Two analyses of the repeated measures of the Mini-Mental State Examination, a 20-item psychometric test, illustrate the method. First, we highlight the usefulness of parameterized non-linear transformations by comparing different flexible families of transformation for modelling the test as a sum score. Then, change over time of the latent construct underlying directly the 20 items is described using two-parameter longitudinal item response models that are specific cases of the approach., (© 2012 The British Psychological Society.)

Objective: To review systematically, for the first time, the effectiveness of all pharmacologic interventions to improve quality of life and well-being in people with dementia., Design: Systematic review and meta-analysis., Methods: We systematically reviewed the 15 randomized controlled trials and one review that fitted predetermined criteria. We included studies that reported the outcomes quality of life, well-being, happiness, or pleasure., Measurements: We rated the validity of studies using a checklist. We calculated mean differences between intervention and control groups at follow-up., Results: None of the evaluated trials reported a significant benefit to quality of life or well-being for people with dementia when comparing those taking a drug or its comparator at follow-up (pooled weighted mean difference: 0.18 [95% confidence interval: -0.82 to 0.46])., Conclusion: We found no consistent evidence that any drug improves quality of life in people with dementia. We recommend that all dementia trials should include quality of life as an outcome, as this is important to patients, and cannot be presumed from improvements in cognition or other symptomatic outcomes, especially if the latter are small., (Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: People with dementia report lower quality of life, but we know little about what interventions might improve it., Methods: We systematically reviewed 20 randomized controlled trials reporting the effectiveness of non-pharmacological interventions in improving quality of life or well-being of people with dementia meeting predetermined criteria. We rated study validity with a checklist. We contacted authors for additional data. We calculated standardized mean differences (SMD) and, for studies reporting similar interventions, pooled standardized effect sizes (SES)., Results: Pooled analyses found that family carer coping strategy-based interventions (four studies, which did not individually achieve significance; n = 420; SES 0.24 (range 0.03-0.45)) and combined patient activity and family carer coping interventions (two studies, not individually significant; n = 191; SES 0.84 (range 0.54-1.14)) might improve quality of life. In one high-quality study, a care management system improved quality of life of people with dementia living at home. Group Cognitive Stimulation Therapy (GCST) improved quality of life of people with dementia in care homes., Conclusion: Preliminary evidence indicated that coping strategy-based family carer therapy with or without a patient activity intervention improved quality of life of people with dementia living at home. GCST was the only effective intervention in a higher quality trial for those in care homes, but we did not find such evidence in the community. Few studies explored whether effects continued after the intervention stopped. Future research should explore the longer-term impact of interventions on, and devise strategies to increase, life quality of people with dementia living in care homes or at home without a family carer.

Depression is the most common psychiatric disorder among the elderly and in old age may interact with emotional and cognitive functioning. Depression in old age has been shown to be associated with degenerative changes in the brain. It is, therefore, important that in this patient population antidepressants with a favourable tolerability profile, such as the selective serotonin reuptake inhibitors (SSRIs), are examined for both antidepressant efficacy and effect on cognitive function and emotional impairment. This randomised, double-blind study compared the efficacy and tolerability of citalopram and mianserin in 336 elderly, depressed patients with or without dementia. Patients received either citalopram 20-40 mg/day or mianserin 30-60 mg/day for 12 weeks. The treatments were equivalent with respect to change in Montgomery-Asberg Depression Rating Scale (MADRS) total score; patients in both treatment groups responded well. Patients with dementia showed a smaller decrease in total MADRS score than patients without dementia. Both treatments were well tolerated with a relatively low incidence of adverse events. Fatigue and somnolence were more frequent with mianserin, while insomnia was more frequent with citalopram. Overall, this study showed that the two treatments were equivalent in efficacy, and that citalopram is an effective, well-tolerated and non-sedative treatment for elderly depressed patients with or without dementia., (Copyright 2000 John Wiley & Sons, Ltd.)