The symptom of low mood in the prodromal stage of mild cognitive impairment and dementia: a cohort study of a community dwelling elderly population

OBJECTIVE: To investigate the symptom of low mood as a predictor of mild cognitive impairment (MCI) and its progression to dementia, taking into account: (i) MCI severity, (ii) time of assessment and (iii) interaction with other factors. METHODS: 764 cognitively healthy elderly subjects living in the community, from the Kungsholmen Project. Participants were assessed by direct interview to detect low mood. Subjects were then followed for 6 years to identify those who developed MCI. People with incident MCI were followed for a further 3 years to assess progression to dementia. RESULTS: People with low mood at baseline had a 2.7-fold (95% CI 1.9 to 3.7) increased risk of developing MCI at follow-up. The association was stronger for amnestic MCI (aMCI: HR 5.8; 95% CI 3.1 to 10.9) compared with global cognitive impairment (other cognitive impairment no dementia, oCIND: HR 2.2; 95% CI 1.5 to 3.3). ApoE-ε4 interacted with low mood in a synergistic fashion, increasing the risk of aMCI, while no interaction with psychiatric, vascular, frailty related or psychosocial factors was observed. Low mood at baseline, as opposed to low mood co-occurring with MCI, was associated with a 5.3-fold (95% CI 1.2 to 23.3) increased risk of progression to dementia in aMCI. In contrast, no association was found in oCIND. CONCLUSION: Low mood was more strongly associated with aMCI than with global cognitive impairment. Progression towards dementia was predicted only by low mood manifest in the prodromal stage of MCI. These findings indicate that low mood is particularly prominent in the very early stages of cognitive decline

HETEROGENEITY IN RISK FACTORS FOR COGNITIVE IMPAIRMENT, NO DEMENTIA: Population-Based Longitudinal Study From the Kungsholmen Project.

OBJECTIVES: The objectives of this study were to investigate the relation of vascular, neuropsychiatric, social, and frailty-related factors with "Cognitive impairment, no dementia" (CIND) and to verify their effect independently of future progression to Alzheimer disease (AD). METHODS: Seven hundred eighteen subjects aged 75+ years who attended baseline, 3- and 6-year follow-up examinations of the Kungsholmen Project, a Swedish prospective cohort study, were studied. CIND was defined according to the performance on the Mini-Mental State Examination. Potential risk factors were collected at baseline and clustered according to four research hypotheses (frailty, vascular, neuropsychiatric, and social hypothesis), each representing a possible pathophysiological mechanism of CIND independently of subsequent development of AD. RESULTS: Over a mean 3.4 years of follow up, 82 participants (11.4%) developed CIND. When the population was subsequently followed for a mean of 2.7 years, subjects with CIND had a threefold increased risk to progress to AD. After multiple adjustments, including adjustment for the development of AD at the 6-year follow up, risk factors for CIND were hip fracture, polypharmacy, and psychoses. CONCLUSIONS: The results suggest that not only the AD-type neurodegenerative process, but also neuropsychiatric- and frailty-related factors may induce cognitive impairment in nondemented elderly. These findings may have relevant preventive and therapeutic implications

Predictors of progression from mild cognitive impairment to Alzheimer disease

OBJECTIVE: To determine the occurrence of neuropsychiatric symptomatology and the relation to future development of Alzheimer disease (AD) in persons with and without mild cognitive impairment (MCI). METHOD: We followed 185 persons with no cognitive impairment and 47 with MCI(amnestic and multidomain), ages 75 to 95, from the population-based Kungsholmen Project, Stockholm, Sweden, for 3 years. Three types of neuropsychiatric symptoms were assessed at baseline: mood-related depressive symptoms, motivation-related depressive symptoms, and anxiety-related symptomatology. AD at 3-year follow-up was diagnosed according to Diagnostic and Statistical Manual for Mental Disorders-III-R criteria. RESULTS: Psychiatric symptoms occurred more frequently in persons with MCI (36.2% mood, 36.2% motivation, and 46.8% anxiety symptoms) than in cognitively intact elderly individuals (18.4% mood, 13.0% motivation, and 24.9% anxiety). Of persons with both MCI and anxiety symptoms, 83.3% developed AD over follow-up vs 6.1% of cognitively intact persons and 40.9% persons who had MCI without anxiety. Among persons with MCI, the 3-year risk of progressing to AD almost doubled with each anxiety symptom (relative risk [RR] = 1.8 [1.2 to 2.7] per symptom). Conversely, among cognitively intact subjects, only symptoms of depressive mood were related to AD development (RR = 1.9 [1.0 to 3.6] per symptom). CONCLUSIONS: The predictive validity of mild cognitive impairment (MCI) for identifying future Alzheimer disease (AD) cases is improved in the presence of anxiety symptoms. Mood-related depressive symptoms (dysphoria, suicidal ideation, etc.) in preclinical AD might be related to the neuropathologic mechanism, as they appear preclinically in persons both with and without MCI

Disease or function? What matters most for self-rated health in older people depends on age

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Emergence of Complex Dynamics in a Simple Model of Signaling Networks

A variety of physical, social and biological systems generate complex fluctuations with correlations across multiple time scales. In physiologic systems, these long-range correlations are altered with disease and aging. Such correlated fluctuations in living systems have been attributed to the interaction of multiple control systems; however, the mechanisms underlying this behavior remain unknown. Here, we show that a number of distinct classes of dynamical behaviors, including correlated fluctuations characterized by $1/f$-scaling of their power spectra, can emerge in networks of simple signaling units. We find that under general conditions, complex dynamics can be generated by systems fulfilling two requirements: i) a ``small-world'' topology and ii) the presence of noise. Our findings support two notable conclusions: first, complex physiologic-like signals can be modeled with a minimal set of components; and second, systems fulfilling conditions (i) and (ii) are robust to some degree of degradation, i.e., they will still be able to generate $1/f$-dynamics

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

Measuring gait speed to better identify prodromal dementia

Abstract Slow gait speed has been shown to predict incident dementia and cognitive decline in older individuals. We aimed to summarize the evidence concerning the association of slow gait speed with cognitive decline and dementia, and discuss the possible shared pathways leading to cognitive and motor impairments, under the unifying hypothesis that body and mind are intimately connected. This is a scoping review supported by a systematic search of the literature, performed on PubMed and Web of Science. Longitudinal studies providing information on the role of gait speed in the prediction of cognitive decline and dementia in cognitively intact people and in those with initial cognitive impairment were eligible. Of 39 studies selected, including overall 57,456 participants, 33 reported a significant association between gait speed and cognitive outcomes, including dementia. Neurodegenerative pathology and cerebrovascular burden may damage cerebral areas involved in both cognitive functions and motor control. At the same time, systemic conditions, characterized by higher cardiorespiratory, and metabolic and inflammatory burden, can affect a number of organs and systems involved in motor functions, including the brain, having ultimately an impact on cognition. The interplay of body and mind seems relevant during the development of cognitive decline and dementia. The measurement of gait speed may improve the detection of prodromal dementia and cognitive impairment in individuals with and without initial cognitive deficits. The potential applicability of such a measure in both clinical and research settings points at the importance of expanding our knowledge about the common underlying mechanisms of cognitive and motor decline

An International Perspective on Chronic Multimorbidity: Approaching the Elephant in the Room

Multimorbidity is a common and burdensome condition that may affect quality of life, increase medical needs, and make people live more years of life with disability. Negative outcomes related to multimorbidity occur beyond what we would expect from the summed effect of single conditions, as chronic diseases interact with each other, mutually enhancing their negative effects, and eventually leading to new clinical phenotypes. Moreover, multimorbidity mirrors an accelerated global susceptibility and a loss of resilience, which are both hallmarks of aging. Due to the complexity of its assessment and definition, and the lack of clear evidence steering its management, multimorbidity represents one of the main current challenges for clinicians, researchers, and policymakers. The authors of this article recently reflected on these issues during two twin international symposia at the 2016 European Union Geriatric Medicine Society (EUGMS) meeting in Lisbon, Portugal, and the 2016 Gerontological Society of America (GSA) meeting in New Orleans, USA. The present work summarizes the most relevant aspects related to multimorbidity, with the ultimate goal to identify knowledge gaps and suggest future directions to approach this condition

Association of resting heart rate with cognitive decline and dementia in older adults: A population‐based cohort study

AbstractIntroduction: Resting heart rate (RHR) predicts future risk for cardiovascular disease (CVD). However, longitudinal studies investigating the relationship of RHR with cognitive decline are scarce.Methods: This population‐based cohort study included 2147 participants (age≥60) in SNAC‐K who were free of dementia and regularly followed from 2001–2004 to 2013–2016. RHR was assessed with electrocardiogram. Dementia was diagnosed following the Diagnostic and Statistical Manual of Mental Disorders 4th Revision criteria. Global cognitive function was assessed using Mini‐Mental State Examination (MMSE). Data were analyzed using Cox and linear mixed‐effects models.Results: RHR≥80 (vs. 60–69) bpm was associated with a multi‐adjusted hazard ratio of 1.55 (95% confidence interval 1.06−2.27) for dementia. The association remained significant after excluding participants with prevalent and incident CVDs. Similarly, RHR≥80 bpm was associated with a multi‐adjusted β‐coefficient of –0.13 (–0.21 to –0.04) for MMSE score.Discussion: Higher RHR is associated with increased risk for dementia and faster cognitive decline independent of CVDs in a general population of elderly people

Rapidly developing multimorbidity and disability in older adults: does social background matter?

Background Multimorbidity is among the most disabling geriatric conditions. In this study we explored whether a rapid development of multimorbidity potentiates its impact on the functional independence of older adults, and whether different sociodemographic factors play a role beyond the rate of chronic disease accumulation. Methods A random sample of persons aged ≥60 years (n = 2387) from the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) was followed over 6 years. The speed of multimorbidity development was estimated as the rate of chronic disease accumulation (linear mixed models) and further dichotomized into the upper versus the three lower rate quartiles. Binomial negative mixed models were used to analyse the association between speed of multimorbidity development and disability (impaired basic and instrumental activities of daily living), expressed as the incidence rate ratio (IRR). The effect of sociodemographic factors, including sex, education, occupation and social network, was investigated. Results The risk of new activity impairment was higher among participants who developed multimorbidity faster (IRR 2.4, 95% CI 1.9–3.1) compared with those who accumulated diseases more slowly over time, even after considering the baseline number of chronic conditions. Only female sex (IRR for women vs. men 1.6, 95% CI 1.2–2.0) and social network (IRR for poor vs. rich social network 1.7, 95% CI 1.3–2.2) showed an effect on disability beyond the rate of chronic disease accumulation. Conclusions Rapidly developing multimorbidity is a negative prognostic factor for disability. However, sociodemographic factors such as sex and social network may determine older adults' reserves of functional ability, helping them to live independently despite rapid accumulation of chronic conditions. This article is protected by copyright. All rights reserved