Predicting risk of dementia in older adults: The late-life dementia risk index

Association of Brain Magnetic Resonance Imaging Signs With Cognitive Outcomes in Persons With Nonimpaired Cognition and Mild Cognitive Impairment

IMPORTANCE

Brain atrophy and vascular lesions contribute to dementia and mild cognitive impairment (MCI) in clinical referral populations. Prospective evidence in older general populations is limited.

OBJECTIVE

To evaluate which magnetic resonance imaging (MRI) signs are independent risk factors for dementia and MCI.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort study included 1553 participants sampled from the Atherosclerosis Risk in Communities Study who had brain MRI scans and were dementia free during visit 5 (June 2011 to September 2013). Participants' cognitive status was evaluated through visit 6 (June 2016 to December 2017).

EXPOSURES

Brain regional volumes, microhemorrhages, white matter hyperintensity (WMH) volumes, and infarcts measured on 3-T MRI.

MAIN OUTCOMES AND MEASURES

Cognitive status (dementia, MCI, or nonimpaired cognition) was determined from in-person evaluations. Dementia among participants who missed visit 6 was identified via dementia surveillance and hospital discharge or death certificate codes. Cox proportional hazards models were used to evaluate the risk of dementia in 3 populations: dementia-free participants (N = 1553), participants with nonimpaired cognition (n = 1014), and participants with MCI (n = 539). Complementary log-log models were used for risk of MCI among participants with nonimpaired cognition who also attended visit 6 (n = 767). Models were adjusted for demographic variables, apolipoprotein E ε4 alleles, vascular risk factors, depressive symptoms, and heart failure.

RESULTS

Overall, 212 incident dementia cases were identified among 1553 participants (mean [SD] age at visit 5, 76 [5.2] years; 946 [60.9%] women; 436 [28.1%] African American) with a median (interquartile range) follow-up period of 4.9 (4.3-5.2) years. Significant risk factors of dementia included lower volumes in the Alzheimer disease (AD) signature region, including hippocampus, entorhinal cortex, and surrounding structures (hazard ratio [HR] per 1-SD decrease, 2.40; 95% CI, 1.89-3.04), lobar microhemorrhages (HR, 1.90; 95% CI, 1.30-2.77), higher volumes of WMH (HR per 1-SD increase, 1.44; 95% CI, 1.23-1.69), and lacunar infarcts (HR, 1.66; 95% CI, 1.20-2.31). The AD signature region volume was also consistently associated with both MCI and progression from MCI to dementia, while subcortical microhemorrhages and infarcts contributed less to the progression from MCI to dementia.

CONCLUSIONS AND RELEVANCE

In this study, lower AD signature region volumes, brain microhemorrhages, higher WMH volumes, and infarcts were risk factors associated with dementia in older community-based residents. Vascular changes were more important in the development of MCI than in its progression to dementia, while AD-related signs were important in both stages.

Population-based dementia prediction model using Korean public health examination data: A cohort study

The early identification and prevention of dementia is important for reducing its worldwide burden and increasing individuals’ quality of life. Although several dementia prediction models have been developed, there remains a need for a practical and precise model targeted to middle-aged and Asian populations. Here, we used national Korean health examination data from adults (331,126 individuals, 40–69 years of age, mean age: 52 years) from 2002–2003 to predict the incidence of dementia after 10 years. We divided the dataset into two cohorts to develop and validate of our prediction model. Cox proportional hazards models were used to construct dementia prediction models for the total group and sex-specific subgroups. Receiver operating characteristics curves, C-statistics, calibration plots, and cumulative hazards were used to validate model performance. Discriminative accuracy as measured by C-statistics was 0.81 in the total group (95% confidence interval (CI) = 0.81 to 0.82), 0.81 in the male subgroup (CI = 0.80 to 0.82), and 0.81 in the female subgroup (CI = 0.80 to 0.82). Significant risk factors for dementia in the total group were age; female sex; underweight; current hypertension; comorbid psychiatric or neurological disorder; past medical history of cardiovascular disease, diabetes mellitus, or hypertension; current smoking; and no exercise. All identified risk factors were statistically significant in the sex-specific subgroups except for low body weight and current hypertension in the female subgroup. These results suggest that public health examination data can be effectively used to predict dementia and facilitate the early identification of dementia within a middle-aged Asian population.

Combining modifiable risk factors and risk of dementia: a systematic review and meta-analysis

OBJECTIVE

To systematically review the literature relating to the impact of multiple co-occurring modifiable risk factors for cognitive decline and dementia.

DESIGN

A systematic review and meta-analysis of the literature relating to the impact of co-occurring key risk factors for incident cognitive decline and dementia. All abstracts and full text were screened independently by two reviewers and each article assessed for bias using a standard checklist. A fixed effects meta-analysis was undertaken.

DATA SOURCES

Databases Medline, Embase and PsycINFO were searched from 1999 to 2017.

ELIGIBILITY CRITERIA

For inclusion articles were required to report longitudinal data from participants free of cognitive decline at baseline, with formal assessment of cognitive function or dementia during follow-up, and an aim to examine the impact of additive or clustered comorbid risk factor burden in with two or more core modifiable risk factors.

RESULTS

Seventy-nine full-text articles were examined. Twenty-two articles (18 studies) were included reporting data on >40 000 participants. Included studies consistently reported an increased risk associated with greater numbers of intraindividual risk factors or unhealthy behaviours and the opposite for healthy or protective behaviours. A meta-analysis of studies with dementia outcomes resulted in a pooled relative risk for dementia of 1.20 (95% CI 1.04 to 1.39) for one risk factor, 1.65 (95% CI 1.40 to 1.94) for two and 2.21 (95% CI 1.78 to 2.73) for three or more, relative to no risk factors. Limitations include dependence on published results and variations in study outcome, cognitive assessment, length of follow-up and definition of risk factor exposure.

CONCLUSIONS

The strength of the reported associations, the consistency across studies and the suggestion of a dose response supports a need to keep modifiable risk factor exposure to a minimum and to avoid exposure to additional modifiable risks. Further research is needed to establish whether particular combinations of risk factors confer greater risk than others.

PROSPERO REGISTRATION NUMBER

42016052914.

Cognitive reserve

Cognitive reserve is a latent construct theorized to account for the discrepancy between observed brain deterioration and ultimate clinical outcomes. This review outlines the theoretical development of the reserve concept and presents major trends within epidemiological and neuroimaging research literatures in support of such a construct. Particular focus is placed on the implications for cognitive aging and dementia.

Validity and reliability of the Brazilian Portuguese version of the Australian National University - Alzheimer's Disease Risk Index (ANU-ADRI)

The ANU-ADRI is a self-report tool that assesses risk for Alzheimer’s Disease (AD).

A reliable global cognitive decline and cortisol as an associated risk factor for patients with late-life depression in the short term: A 1-year prospective study

BACKGROUND

Late-life depression is a risk factor of dementia. It may increase the risk of reliable cognitive decline in the short term, and its associated risk factors remain unclear. Cortisol level may be one of the important predictors.

OBJECTIVES

To estimate whether patients with late-life depression are at an increased risk for reliable global cognitive declines in 1 year, and explore associated risk factors predicting cognitive declines.

METHODS

This prospective 1-year follow-up study involved 148 participants (67 with late-life depression and 81 normal elderly). Global cognitive function was assessed by the Mini-Mental State Examination (MMSE). The reliable global cognitive decline was defined by the reliable change index (RCI) of the MMSE. Factors related to cognitive function (e.g., age, gender, education, duration of depression and severity of depression) were obtained. Serum cortisol levels were measured at baseline.

RESULTS

At the 1-year follow-up assessment, 19 patients with late-life depression (28.4%) showed reliable global cognitive declines, a risk that was 6.4 times (95% CIs = 1.3-31.1, p = 0.021) higher than that of normal elderly. Elevated serum cortisol levels and older age were associated with the risk of cognitive decline that was 1.6- and 1.2-times higher (95% CIs = 1.07-2.5, p = 0.02, and 95% CIs = 1.04-1.4, p = 0.01 respectively).

LIMITATIONS

Serum cortisol levels were measured only in the morning.

CONCLUSIONS

Late-life depression is associated with a greatly increased risk of reliable cognitive decline in short term. Cortisol dysregulation may contribute to the pathology of cognitive decline.

Lack of associations between modifiable risk factors and dementia in the very old: findings from the Cambridge City over-75s cohort study

OBJECTIVES

To investigate the association between modifiable risk and protective factors and severe cognitive impairment and dementia in the very old. Additionally, the present study tests the predictive validity of the 'LIfestyle for BRAin health' (LIBRA) score, an index developed to assess an individual's dementia prevention potential.

METHOD

Two hundred seventy-eight individuals aged 85 years or older from the Cambridge City over-75s cohort study were followed-up until death. Included risk and protective factors were: diabetes, heart disease, hypertension, depression, smoking, low-to-moderate alcohol use, high cognitive activity, and physical inactivity. Incident severe cognitive impairment was based on the Mini-Mental State Examination (score: 0-17) and incident dementia was based on either post-mortem consensus clinical diagnostic assessments or death certificate data. Logistic regressions were used to test whether individual risk and protective factors and the LIBRA score were associated with severe cognitive impairment or dementia after 18 years follow-up.

RESULTS

None of the risk and protective factors or the LIBRA score was significantly associated with increased risk of severe cognitive impairment or dementia. Sensitivity analyses using a larger sample, longer follow-up period, and stricter cut-offs for prevalent cognitive impairment showed similar results.

CONCLUSION

Associations between well-known midlife risk and protective factors and risk for severe cognitive impairment or dementia might not persist into very old age, in line with suggestions that targeting these factors through lifestyle interventions should start earlier in life.

Fine Particle Sources and Cognitive Function in An Older Puerto Rican Cohort in Greater Boston

Supplemental Digital Content is available in the text.

Background:

Puerto Ricans living in the mainland US have substantially higher rates of impairment to cognitive performance as compared to non-Hispanic Whites, with air pollutant exposures a potential risk factor. We investigated whether exposures to specific air pollution sources were associated with performance across several cognitive domains in a cohort of Puerto Rican older adults.

Objectives:

To investigate the association between sources of fine particulate matter (PM_2.5) and cognitive performance in each of five cognitive domains.

Methods:

We obtained demographic, health, and cognitive function data for 1500 elderly participants of the Boston Puerto Rican Health Study. Cognitive function was assessed in each of two waves for five domains: verbal memory, recognition, mental processing, and executive and visuospatial function. To these data, we linked concentrations of PM_2.5 and its components, black carbon (BC), nickel, sulfur, and silicon, as tracers for PM_2.5 from traffic, oil combustion, coal combustion, and resuspended dust, respectively. Associations between each PM_2.5 component and cognitive domain were examined using linear mixed models.

Results:

One year moving average exposures to BC were significantly associated with decreased verbal memory (−0.38; 95% confidence interval [CI] = −0.46, −0.30), recognition (−0.35; 95% CI = −0.46, −0.25), mental processing (−1.14; 95% CI = −1.55, −0.74), and executive function (−0.94; 95% CI = −1.31, −0.56). Similar associations were found for nickel. Associations for sulfur, and silicon, and PM_2.5 were generally null, although sulfur (−0.51; 95% CI = −0.75, −0.28), silicon (−0.25; 95% CI = −0.36, −0.13), and PM_2.5 (−0.35; 95% CI = −0.57, −0.12) were associated with decreased recognition.

Conclusion:

Long-term exposures to BC and nickel, tracers of traffic and oil combustion, respectively, were associated with decreased cognitive function across all domains, except visuospatial function.

CAIDE Dementia Risk Score, Alzheimer and cerebrovascular pathology: a population-based autopsy study

BACKGROUND

CAIDE Dementia Risk Score is a tool for estimating dementia risk in the general population. Its longitudinal associations with Alzheimer or vascular neuropathology in the oldest old are not known.

AIM

To explore the relationship between CAIDE Dementia Risk Score at baseline and neuritic plaques, neurofibrillary tangles, cerebral infarcts and cerebral amyloid angiopathy (CAA) after up to 10-year follow-up in the Vantaa 85 +  population.

METHODS

Study population included 149 participants aged ≥85 years, without dementia at baseline, and with available clinical and autopsy data. Methenamine silver staining was used for β-amyloid and modified Bielschowsky method for neurofibrillary tangles and neuritic plaques. Macroscopic infarcts were identified from cerebral hemispheres, brainstem and cerebellum slices. Standardized methods were used to determine microscopic infarcts, CAA and α-synuclein pathologies. The CAIDE Dementia Risk Score was calculated based on scores for age, sex, BMI, total cholesterol, systolic blood pressure, physical activity and APOEε4 carrier status (range 0-18 points).

RESULTS

A CAIDE Dementia Risk Score above 11 points was associated with more cerebral infarctions up to 10 years later: OR (95% CI) was 2.10 (1.06-4.16). No associations were found with other neuropathologies.

CONCLUSION

In a population of elderly aged ≥85 years, higher CAIDE Dementia Risk Score was associated with increased risk of cerebral infarcts.

Cerebral small vessel disease and the risk of dementia: A systematic review and meta-analysis of population-based evidence

INTRODUCTION

Cerebral small vessel disease is increasingly linked to dementia.

METHODS

We systematically searched Medline, Embase, and Cochrane databases for prospective population-based studies addressing associations of white matter hyperintensities, covert brain infarcts (i.e., clinically silent infarcts), and cerebral microbleeds with risk of all-dementia or Alzheimer's disease and performed meta-analyses.

RESULTS

We identified 11 studies on white matter hyperintensities, covert brain infarcts, or cerebral microbleeds with risk of all-dementia or Alzheimer's disease. Pooled analyses showed an association of white matter hyperintensity volume and a borderline association of covert brain infarcts with risk of all-dementia (hazard ratio: 1.39 [95% confidence interval: 1.00; 1.94], N = 3913, and 1.47 [95% confidence interval: 0.97; 2.22], N = 8296). Microbleeds were not statistically significantly associated with an increased risk of all-dementia (hazard ratio: 1.25 [95% confidence interval: 0.66; 2.38], N = 8739).

DISCUSSION

White matter hyperintensities are associated with an increased risk of all-dementia and Alzheimer's disease in the general population. However, studies are warranted to further determine the role of markers of cerebral small vessel disease in dementia.

Modifiable Risk Factors for Prevention of Dementia in Midlife, Late Life and the Oldest-Old: Validation of the LIBRA Index

BACKGROUND

Recently, the LIfestyle for BRAin health (LIBRA) index was developed to assess an individual's prevention potential for dementia.

OBJECTIVE

We investigated the predictive validity of the LIBRA index for incident dementia in midlife, late life, and the oldest-old.

METHODS

9,387 non-demented individuals were recruited from the European population-based DESCRIPA study. An individual's LIBRA index was calculated solely based on modifiable risk factors: depression, diabetes, physical activity, hypertension, obesity, smoking, hypercholesterolemia, coronary heart disease, and mild/moderate alcohol use. Cox regression was used to test the predictive validity of LIBRA for dementia at follow-up (mean 7.2 y, range 1-16).

RESULTS

In midlife (55-69 y, n = 3,256) and late life (70-79 y, n = 4,320), the risk for dementia increased with higher LIBRA scores. Individuals in the intermediate- and high-risk groups had a higher risk of dementia than those in the low-risk group. In the oldest-old (80-97 y, n = 1,811), higher LIBRA scores did not increase the risk for dementia.

CONCLUSION

LIBRA might be a useful tool to identify individuals for primary prevention interventions of dementia in midlife, and maybe in late life, but not in the oldest-old.

Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study

BACKGROUND AND OBJECTIVE

This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study.

METHODS

The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC).

RESULTS

AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype.

CONCLUSION

The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions.

A Risk Score for the Prediction of Neurocognitive Disorders among Community-Dwelling Chinese Older Adults

BACKGROUND

Several risk scores have been developed for predicting cognitive impairment and dementia, but none have been validated in Asian samples. We aimed to produce a risk score that best predicts incident neurocognitive disorder (NCD) among Chinese elderly and to validate this score against the modified risk score derived from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study.

METHODS

Data from participants enrolled in the Singapore Longitudinal Ageing Study (SLAS) 1 were analyzed. A total of 957 participants >55 years of age with normal cognition at baseline were included. Incident cases of NCD were measured using the global Clinical Dementia Rating (CDR) and determined by a consensus panel.

RESULTS

The best prediction model from SLAS included age, gender, education, depression, heart disease, social and productive activities and Mini-Mental State Examination score. This model predicted the short-term risk of incident NCD in elderly participants moderately well, with a C statistic (area under the curve) of 0.72. Modified CAIDE models applied to our sample had a C statistic of 0.71.

CONCLUSION

Our risk score performs as well as other available risk scores. It is the only risk score formulated for ethnic Chinese, rendering it valuable for clinical use in Asia; at-risk individuals can be identified for early intervention.

Lifestyle for Brain Health (LIBRA): a new model for dementia prevention

OBJECTIVE

Modifiable risk factors for dementia were recently identified and compiled in a systematic review. The 'Lifestyle for Brain Health' (LIBRA) score, reflecting someone's potential for dementia prevention, was studied in a large longitudinal population-based sample with respect to predicting cognitive change over an observation period of up to 16 years.

METHODS

Lifestyle for Brain Health was calculated at baseline for 949 participants aged 50-81 years from the Maastricht Ageing Study. The predictive value of LIBRA for incident dementia and cognitive impairment was examined by using Cox proportional hazard models and by testing its relation with cognitive decline.

RESULTS

Lifestyle for Brain Health predicted future risk of dementia, as well as risk of cognitive impairment. A one-point increase in LIBRA score related to 19% higher risk for dementia and 9% higher risk for cognitive impairment. LIBRA predicted rate of decline in processing speed, but not memory or executive functioning.

CONCLUSIONS

Lifestyle for Brain Health (LIBRA) may help in identifying and monitoring risk status in dementia-prevention programmes, by targeting modifiable, lifestyle-related risk factors. Copyright © 2017 John Wiley & Sons, Ltd.

Personalized long-term prediction of cognitive function: Using sequential assessments to improve model performance

Prediction of onset and progression of cognitive decline and dementia is important both for understanding the underlying disease processes and for planning health care for populations at risk. Predictors identified in research studies are typically accessed at one point in time. In this manuscript, we argue that an accurate model for predicting cognitive status over relatively long periods requires inclusion of time-varying components that are sequentially assessed at multiple time points (e.g., in multiple follow-up visits). We developed a pilot model to test the feasibility of using either estimated or observed risk factors to predict cognitive status. We developed two models, the first using a sequential estimation of risk factors originally obtained from 8 years prior, then improved by optimization. This model can predict how cognition will change over relatively long time periods. The second model uses observed rather than estimated time-varying risk factors and, as expected, results in better prediction. This model can predict when newly observed data are acquired in a follow-up visit. Performances of both models that are evaluated in10-fold cross-validation and various patient subgroups show supporting evidence for these pilot models. Each model consists of multiple base prediction units (BPUs), which were trained using the same set of data. The difference in usage and function between the two models is the source of input data: either estimated or observed data. In the next step of model refinement, we plan to integrate the two types of data together to flexibly predict dementia status and changes over time, when some time-varying predictors are measured only once and others are measured repeatedly. Computationally, both data provide upper and lower bounds for predictive performance.

Getting RID of the blues: Formulating a Risk Index for Depression (RID) using structural equation modeling

OBJECTIVE

While risk factors for depression are increasingly known, there is no widely utilised depression risk index. Our objective was to develop a method for a flexible, modular, Risk Index for Depression using structural equation models of key determinants identified from previous published research that blended machine-learning with traditional statistical techniques.

METHODS

Demographic, clinical and laboratory variables from the National Health and Nutrition Examination Study (2009-2010, N = 5546) were utilised. Data were split 50:50 into training:validation datasets. Generalised structural equation models, using logistic regression, were developed with a binary outcome depression measure (Patient Health Questionnaire-9 score ⩾ 10) and previously identified determinants of depression: demographics, lifestyle-environs, diet, biomarkers and somatic symptoms. Indicative goodness-of-fit statistics and Areas Under the Receiver Operator Characteristic Curves were calculated and probit regression checked model consistency.

RESULTS

The generalised structural equation model was built from a systematic process. Relative importance of the depression determinants were diet (odds ratio: 4.09; 95% confidence interval: [2.01, 8.35]), lifestyle-environs (odds ratio: 2.15; 95% CI: [1.57, 2.94]), somatic symptoms (odds ratio: 2.10; 95% CI: [1.58, 2.80]), demographics (odds ratio:1.46; 95% CI: [0.72, 2.95]) and biomarkers (odds ratio:1.39; 95% CI: [1.00, 1.93]). The relationships between demographics and lifestyle-environs and depression indicated a potential indirect path via somatic symptoms and biomarkers. The path from diet was direct to depression. The Areas under the Receiver Operator Characteristic Curves were good (logistic:training = 0.850, validation = 0.813; probit:training = 0.849, validation = 0.809).

CONCLUSION

The novel Risk Index for Depression modular methodology developed has the flexibility to add/remove direct/indirect risk determinants paths to depression using a structural equation model on datasets that take account of a wide range of known risks. Risk Index for Depression shows promise for future clinical use by providing indications of main determinant(s) associated with a patient's predisposition to depression and has the ability to be translated for the development of risk indices for other affective disorders.

Dementia Population Risk Tool (DemPoRT): study protocol for a predictive algorithm assessing dementia risk in the community

INTRODUCTION

The burden of disease from dementia is a growing global concern as incidence increases dramatically with age, and average life expectancy has been increasing around the world. Planning for an ageing population requires reliable projections of dementia prevalence; however, existing population projections are simple and have poor predictive accuracy. The Dementia Population Risk Tool (DemPoRT) will predict incidence of dementia in the population setting using multivariable modelling techniques and will be used to project dementia prevalence.

METHODS AND ANALYSIS

The derivation cohort will consist of elderly Ontario respondents of the Canadian Community Health Survey (CCHS) (2001, 2003, 2005 and 2007; 18 764 males and 25 288 females). Prespecified predictors include sociodemographic, general health, behavioural, functional and health condition variables. Incident dementia will be identified through individual linkage of survey respondents to population-level administrative healthcare databases (1797 and 3281 events, and 117 795 and 166 573 person-years of follow-up, for males and females, respectively, until 31 March 2014). Using time of first dementia capture as the primary outcome and death as a competing risk, sex-specific proportional hazards regression models will be estimated. The 2008/2009 CCHS survey will be used for validation (approximately 4600 males and 6300 females). Overall calibration and discrimination will be assessed as well as calibration within predefined subgroups of importance to clinicians and policy makers.

ETHICS AND DISSEMINATION

Research ethics approval has been granted by the Ottawa Health Science Network Research Ethics Board. DemPoRT results will be submitted for publication in peer-review journals and presented at scientific meetings. The algorithm will be assessable online for both population and individual uses.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov NCT03155815, pre-results.

Change in multimodal MRI markers predicts dementia risk in cerebral small vessel disease

Objective:

To determine whether MRI markers, including diffusion tensor imaging (DTI), can predict cognitive decline and dementia in patients with cerebral small vessel disease (SVD).

Methods:

In the prospective St George's Cognition and Neuroimaging in Stroke study, multimodal MRI was performed annually for 3 years and cognitive assessments annually for 5 years in a cohort of 99 patients with SVD, defined as symptomatic lacunar stroke and confluent white matter hyperintensities (WMH). Progression to dementia was determined in all patients. Progression of WMH, brain volume, lacunes, cerebral microbleeds, and a DTI measure (the normalized peak height of the mean diffusivity histogram distribution) as a marker of white matter microstructural damage were determined.

Results:

Over 5 years of follow-up, 18 patients (18.2%) progressed to dementia. A significant change in all MRI markers, representing deterioration, was observed. The presence of new lacunes, and rate of increase in white matter microstructural damage on DTI, correlated with both decline in executive function and global functioning. Growth of WMH and deterioration of white matter microstructure on DTI predicted progression to dementia. A model including change in MRI variables together with their baseline values correctly classified progression to dementia with a C statistic of 0.85.

Conclusions:

This longitudinal prospective study provides evidence that change in MRI measures including DTI, over time durations during which cognitive change is not detectable, predicts cognitive decline and progression to dementia. It supports the use of MRI measures, including DTI, as useful surrogate biomarkers to monitor disease and assess therapeutic interventions.

Defining Optimal Brain Health in Adults: A Presidential Advisory From the American Heart Association/American Stroke Association

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA's Life's Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m2) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer's Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA's Life's Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA's Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention.

Cognitive activity mediates the association between social activity and cognitive performance: A longitudinal study

Social activity is 1 aspect of an active lifestyle and some evidence indicates it is related to preserved cognitive function in older adulthood. However, the potential mechanisms underlying this association remain unclear. We investigate 4 potential mediational pathways through which social activity may relate to cognitive performance. A multilevel structural equation modeling approach to mediation was used to investigate whether cognitive activity, physical activity, depressive symptoms, and vascular health conditions mediate the association between social activity and cognitive function in older adults. Using data from the Victoria Longitudinal Study, we tested 4 cognitive outcomes: fluency, episodic memory, reasoning, and vocabulary. Three important findings emerged. First, the association between social activity and all 4 domains of cognitive function was significantly mediated by cognitive activity at the within-person level. Second, we observed a significant indirect effect of social activity on all domains of cognitive function through cognitive activity at the between-person level. Third, we found a within-person indirect relationship of social activity with episodic memory performance through physical activity. For these older adults, engagement in social activities was related to participation in everyday cognitive activities and in turn to better cognitive performance. This pattern is consistent with the interpretation that a lifestyle of social engagement may benefit cognitive performance by providing opportunities or motivation to participate in supportive cognitively stimulating activities. (PsycINFO Database Record

Body mass index in midlife and dementia: Systematic review and meta-regression analysis of 589,649 men and women followed in longitudinal studies

INTRODUCTION

We conducted a meta-analysis of the conflicting epidemiologic evidence on the association between midlife body mass index (BMI) and dementia.

METHODS

We searched standard databases to identify prospective, population-based studies of dementia risk by midlife underweight, overweight, and obesity. We performed random-effects meta-analyses and meta-regressions of adjusted relative risk (RR) estimates and formally explored between-study heterogeneity.

RESULTS

We included 19 studies on 589,649 participants (2040 incident dementia cases) followed up for up to 42 years. Midlife (age 35 to 65 years) obesity (BMI ≥ 30) (RR, 1.33; 95% confidence interval [CI], 1.08-1.63), but not overweight (25 < BMI < 30) (RR, 1.07; 95% CI, 0.96-1.20), was associated with dementia in late life. The association with midlife underweight (RR, 1.39; 95% CI, 1.13-1.70) was potentially driven by residual confounding (P from meta-regression = .004), selection (P = .046), and information bias (P = .007).

DISCUSSION

Obesity in midlife increases the risk of dementia. The association between underweight and dementia remains controversial.

Practical risk score for 5-, 10-, and 20-year prediction of dementia in elderly persons: Framingham Heart Study

INTRODUCTION

With a rapidly aging population, general practitioners are confronting the challenge of how to determine those who are at greatest risk for dementia and potentially need more specialized follow-up to mitigate symptoms early in its course. We created a practical dementia risk score and provided individualized estimates of future dementia risk.

METHODS

Using the Framingham Heart Study data, we built our prediction model using Cox proportional hazard models and developed a point system for the risk score and risk estimates.

RESULTS

The score system used total points ranging from -1 to 31 and stratifies individuals into different levels of risk. We estimated 5-, 10-, and 20-year dementia risk prediction and incorporated these into the points system.

DISCUSSION

This risk score system provides a practical tool because all included predictors are easy to assess by practitioners. It can be used to estimate future probabilities of dementia for individuals.

The BIOCARD Index: A Summary Measure to Predict Onset of Mild Cognitive Impairment

BACKGROUND

Changes in neuropsychological testing, neuroimaging, and cerebrospinal fluid may precede mild cognitive impairment (MCI). However, these markers are not routinely performed in outpatient clinical visits.

OBJECTIVE

To evaluate whether a simple clinical index, consisting of questions given to patients and their informants, could predict the onset of symptoms of MCI among cognitively normal individuals.

MATERIALS AND METHODS

Two hundred twenty-two participants in the BIOCARD study received a detailed history, physical examination, and neuropsychological testing annually. An index was calculated by including questions about memory problems, depression, age, education, history of cerebrovascular disease risk factors, and brain injury, family history of dementia, and the Mini-Mental State examination score. Cox regression analyses were used to determine if this index score was related to diagnosis of MCI.

RESULTS

The BIOCARD Index score mean for individuals who progressed to MCI was 20.3 (SD=2.9), whereas the score for individuals who remained normal was 24.8 (SD=2.3) (P<0.001) [hazard ratio, SE for subsequent diagnosis of MCI=0.75 (0.67 to 0.84); P<0.001].

CONCLUSIONS

Lower BIOCARD Index score predicted symptoms of MCI several years before the MCI diagnosis. The BIOCARD Index can be easily used in clinics to identify cognitively normal older individuals who are at risk for deterioration.

Coronary Artery Bypass Graft Surgery and Dementia Risk in the Cardiovascular Health Study

INTRODUCTION

The association between history of coronary artery bypass graft surgery (CABG) and dementia risk remains unclear.

METHODS

We conducted a prospective cohort analysis using data on 3155 elderly adults free from prevalent dementia from the US population-based Cardiovascular Health Study (CHS) with adjudicated incident all-cause dementia, Alzheimer disease (AD), vascular dementia (VaD), and mixed dementia.

RESULTS

In the CHS, the hazard ratio (HR) for all-cause dementia was 1.93 [95% confidence interval (CI), 1.36-2.74] for those with CABG history compared with those with no CABG history after adjustment for potential confounders. Similar HRs were observed for AD (HR=1.71; 95% CI, 0.98-2.98), VaD (HR=1.42; 95% CI, 0.56-3.65), and mixed dementia (HR=2.73; 95% CI, 1.55-4.80). The same pattern of results was observed when these CHS findings were pooled with a prior prospective study, the pooled HRs were 1.96 (95% CI, 1.42-2.69) for all-cause dementia, 1.71 (95% CI, 1.04-2.79) for AD and 2.20 (95% CI, 0.78-6.19) for VaD.

DISCUSSION

Our results suggest CABG history is associated with long-term dementia risk. Further investigation is warranted to examine the causal mechanisms which may explain this relationship or whether the association reflects differences in coronary artery disease severity.

A Late Life Risk Index for Severe Cognitive Impairment in Mexico

BACKGROUND

Several dementia risk indices have been developed for older adults in high-income countries. However, no index has been developed for populations in low- or middle-income countries.

OBJECTIVE

To create a risk index for predicting severe cognitive impairment among adults aged ≥60 in Mexico and to compare the accuracy of this index to the Dementia Screening Indicator (DSI).

METHODS

This study included 3,002 participants from the Mexican Health and Aging Study (MHAS) interviewed in 2001 and 2012. The MHAS risk index included sociodemographic, health, and functional characteristics collected in 2001. A point value based on the beta coefficients from a multivariable logistic regression model was assigned to each risk factor and the total score was calculated.

RESULTS

The MHAS risk index (AUC = 0.74 95% CI = 0.70-0.77) and DSI (AUC = 0.72 95% CI = 0.69-0.77) had similar accuracy for discriminating between participants who developed severe cognitive impairment from those who did not. A score of ≥16 on the MHAS risk index had a sensitivity of 0.69 (95% CI = 0.64-0.70) and specificity of 0.67 (95% CI = 0.66-0.69). A score of ≥23 on the DSI had a sensitivity of 0.56 (95% CI = 0.50-0.63) and specificity of 0.78 (95% CI = 0.76-0.79).

DISCUSSION

The MHAS risk index and DSI have moderate accuracy for predicting severe cognitive impairment among older adults in Mexico. This provides evidence that existing dementia risk indices may be applicable in low- and middle-income countries such as Mexico. Future research should seek to identify additional risk factors that can improve the accuracy of the MHAS risk index.

Mexican-American Dementia Nomogram: Development of a Dementia Risk Index for Mexican-American Older Adults

OBJECTIVES

To create a risk index (Mexican American Dementia Nomogram (MADeN)) that predicts dementia over a 10-year period for Mexican Americans aged 65 and older.

DESIGN

Retrospective cohort study with longitudinal analysis.

SETTING

Texas, New Mexico, Colorado, Arizona, and California.

PARTICIPANTS

Hispanic Established Populations for the Epidemiologic Study of the Elderly (H-EPESE) participants (n = 1,739).

MEASUREMENTS

Dementia was defined as a decline of three or more points per year on the Mini-Mental State Examination and inability to perform one or more daily activities. Candidate risk factors included demographic characteristics, measures of social engagement, self-reported health conditions, ability to perform daily activities, and physical activity.

RESULTS

The MADeN comprised the following risk factors: age, sex, education, not having friends to count on, not attending community events, diabetes mellitus, feeling the blues, pain, impairment in instrumental activities of daily living, and unable to walk a half-mile. The area under the receiver operating characteristic curve was 0.74 (95% confidence interval (CI) = 0.70-0.78) and a score of 16 points or higher had a sensitivity of 0.65 (95% CI = 0.59-0.72) and specificity of 0.70 (95% CI = 0.67-0.73) in predicting dementia.

CONCLUSION

The MADeN was able to predict dementia in a population of older Mexican-American adults with moderate accuracy. It has the potential to identify older Mexican-American adults who may benefit from interventions to reduce dementia risk and to educate this population about risk factors for dementia.

Changes in Neural Activity Underlying Working Memory after Computerized Cognitive Training in Older Adults

Computerized cognitive training (CCT) may counter the impact of aging on cognition, but both the efficacy and neurocognitive mechanisms underlying CCT remain controversial. In this study, 35 older individuals were randomly assigned to Cogmed adaptive working memory (WM) CCT or an active control CCT, featuring five weeks of five ∼40 min sessions per week. Before and after the 5-week intervention, event-related potentials were measured while subjects completed a visual n-back task with three levels of demand (0-back, 1-back, 2-back). The anterior P3a served as an index of directing attention and the posterior P3b as an index of categorization/WM updating. We hypothesized that adaptive CCT would be associated with decreased P3 amplitude at low WM demand and increased P3 amplitude at high WM demand. The adaptive CCT group exhibited a training-related increase in the amplitude of the anterior P3a and posterior P3b in response to target stimuli across n-back tasks, while subjects in the active control CCT group demonstrated a post-training decrease in the anterior P3a. Performance did not differ between groups or sessions. Larger overall P3 amplitudes were strongly associated with better task performance. Increased post-CCT P3 amplitude correlated with improved task performance; this relationship was especially robust at high task load. Our findings suggest that adaptive WM training was associated with increased orienting of attention, as indexed by the P3a, and the enhancement of categorization/WM updating processes, as indexed by the P3b. Increased P3 amplitude was linked to improved performance; however. there was no direct association between adaptive training and improved performance.

Middle age self-report risk score predicts cognitive functioning and dementia in 20-40 years

INTRODUCTION

On the basis of the proxy measures of cognitive reserve, we created a middle age self-report risk score for early prediction of dementia.

METHODS

We used a longitudinal population-based study of 2602 individuals with a replication sample (N = 1011). Risk score at a mean age of 47 years was based on questions on educational and occupational attainments. Cognitive status at a mean age of 74 was determined via two validated telephone instruments.

RESULTS

The prevalence of dementia was 10% after a mean follow-up of 28 years. Risk score was a good predictor of dementia: area under the curve = 0.77 (95% confidence interval, 0.74-0.80). The risk of dementia decreased as a function of risk score from 36% to 0%. The risk score was significantly associated with cognition after a mean follow-up of 39 years in the replication sample.

DISCUSSION

Self-report risk score predicted cognitive functioning and dementia risk 20-40 years later.

Composite risk scores for predicting dementia

PURPOSE OF REVIEW

A key priority in dementia research is the development of tools to identify individuals at high risk of dementia. This is important to prevent or delay dementia onset and as we move towards personalized medicine.

RECENT FINDINGS

Numerous models (n > 50) for predicting dementia have been developed. These vary in the number (0 to 20+) and type (e.g. demographics, health, neuropsychological, and genetic) of predictor variables used for risk calculation, follow-up length (1-20 years) and age at screening (mid vs laterlife). Evaluation of the models shows that most have moderate-to-poor predictive accuracy. Few have been externally validated, raising questions about their generalizability outside the cohorts from which they were developed. The results highlight that if additional models are proposed the field will be overwhelmed with many competing risk models, making it difficult to reach consensus on which is best.

SUMMARY

Numerous models for predicting dementia have been proposed but are limited by a lack of external validation and evaluation of economic impact. Innovative methods and data designs may be needed to improve derivation of dementia risk scores. Having a method for predicting dementia risk could transform medical research and allow for earlier testing of intervention strategies.

Risk of dementia and death in the long-term follow-up of the Pittsburgh Cardiovascular Health Study-Cognition Study

INTRODUCTION

Increasing life expectancy has resulted in a larger population of older individuals at risk of dementia.

METHODS

The Cardiovascular Health Study-Cognition Study followed 532 participants from 1998-99 (mean age 79) to 2013 (mean age 93) for death and dementia.

RESULTS

Risk of death was determined by extent of coronary artery calcium, high-sensitivity cardiac troponin, brain natriuretic peptide, and white matter grade. Significant predictors of dementia were age, apolipoprotein-E4, vocabulary raw score, hippocampal volume, ventricular size, cognitive performance, and number of blocks walked. By 2013, 160 of 532 were alive, including 19 cognitively normal. Those with normal cognition had higher grade education, better cognition test scores, greater hippocampal volume, faster gait speed, and number of blocks walked as compared with survivors who were demented.

DISCUSSION

Few survived free of dementia and disability. Prevention and delay of cognitive decline for this older population is an imperative.

Predicting dementia risk in primary care: development and validation of the Dementia Risk Score using routinely collected data

BACKGROUND

Existing dementia risk scores require collection of additional data from patients, limiting their use in practice. Routinely collected healthcare data have the potential to assess dementia risk without the need to collect further information. Our objective was to develop and validate a 5-year dementia risk score derived from primary healthcare data.

METHODS

We used data from general practices in The Health Improvement Network (THIN) database from across the UK, randomly selecting 377 practices for a development cohort and identifying 930,395 patients aged 60-95 years without a recording of dementia, cognitive impairment or memory symptoms at baseline. We developed risk algorithm models for two age groups (60-79 and 80-95 years). An external validation was conducted by validating the model on a separate cohort of 264,224 patients from 95 randomly chosen THIN practices that did not contribute to the development cohort. Our main outcome was 5-year risk of first recorded dementia diagnosis. Potential predictors included sociodemographic, cardiovascular, lifestyle and mental health variables.

RESULTS

Dementia incidence was 1.88 (95% CI, 1.83-1.93) and 16.53 (95% CI, 16.15-16.92) per 1000 PYAR for those aged 60-79 (n = 6017) and 80-95 years (n = 7104), respectively. Predictors for those aged 60-79 included age, sex, social deprivation, smoking, BMI, heavy alcohol use, anti-hypertensive drugs, diabetes, stroke/TIA, atrial fibrillation, aspirin, depression. The discrimination and calibration of the risk algorithm were good for the 60-79 years model; D statistic 2.03 (95% CI, 1.95-2.11), C index 0.84 (95% CI, 0.81-0.87), and calibration slope 0.98 (95% CI, 0.93-1.02). The algorithm had a high negative predictive value, but lower positive predictive value at most risk thresholds. Discrimination and calibration were poor for the 80-95 years model.

CONCLUSIONS

Routinely collected data predicts 5-year risk of recorded diagnosis of dementia for those aged 60-79, but not those aged 80+. This algorithm can identify higher risk populations for dementia in primary care. The risk score has a high negative predictive value and may be most helpful in 'ruling out' those at very low risk from further testing or intensive preventative activities.

The Alzheimer's Prevention Clinic at Weill Cornell Medical College / New York - Presbyterian Hospital: Risk Stratification and Personalized Early Intervention

In July 2013, Weill Cornell Medical College founded the first Alzheimer's Prevention Clinic (APC) in the United States, providing direct clinical care to family members of patients with Alzheimer's disease (AD) as part of the Weill Cornell Memory Disorders Program. At the APC, patients seeking to lower their AD risk undergo a comprehensive assessment, receive a personalized plan based on rapidly evolving scientific evidence, and are followed over time using validated as well as emerging clinical and research technologies. The APC approach applies the principles of pharmacogenomics, nutrigenomics and clinical precision medicine, to tailor individualized therapies for patients. Longitudinal measures currently assessed in the clinic include anthropometrics, cognition, blood biomarkers (i.e., lipid, inflammatory, metabolic, nutritional) and genetics, as well as validated, self-reported measures that enable patients to track several aspects of health-related quality of life. Patients are educated on the fundamental concepts of AD prevention via an interactive online course hosted on Alzheimer's Universe (www.AlzU.org), which also contains several activities including validated computer-based cognitive testing. The primary goal of the APC is to employ preventative measures that lower modifiable AD risk, possibly leading to a delay in onset of future symptoms. Our secondary goal is to establish a cohort of at-risk individuals who will be primed to participate in future AD prevention trials as disease-modifying agents emerge for testing at earlier stages of the AD process. The clinical services are intended to lower concern for future disease by giving patients a greater sense of control over their brain health.

Bridging the Translation Gap: From Dementia Risk Assessment to Advice on Risk Reduction

Dementia risk reduction is a global health and fiscal priority given the current lack of effective treatments and the projected increased number of dementia cases due to population ageing. There are often gaps among academic research, clinical practice, and public policy. We present information on the evidence for dementia risk reduction and evaluate the progress required to formulate this evidence into clinical practice guidelines. This narrative review provides capsule summaries of current evidence for 25 risk and protective factors associated with AD and dementia according to domains including biomarkers, demographic, lifestyle, medical, and environment. We identify the factors for which evidence is strong and thereby especially useful for risk assessment with the goal of personalising recommendations for risk reduction. We also note gaps in knowledge, and discuss how the field may progress towards clinical practice guidelines for dementia risk reduction.

Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review

BACKGROUND

Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. To evaluate these models we undertook a systematic review in 2010 and updated this in 2014 due to the increase in research published in this area. Here we include a critique of the variables selected for inclusion and an assessment of model prognostic performance.

METHODS

Our previous systematic review was updated with a search from January 2009 to March 2014 in electronic databases (MEDLINE, Embase, Scopus, Web of Science). Articles examining risk of dementia in non-demented individuals and including measures of sensitivity, specificity or the area under the curve (AUC) or c-statistic were included.

FINDINGS

In total, 1,234 articles were identified from the search; 21 articles met inclusion criteria. New developments in dementia risk prediction include the testing of non-APOE genes, use of non-traditional dementia risk factors, incorporation of diet, physical function and ethnicity, and model development in specific subgroups of the population including individuals with diabetes and those with different educational levels. Four models have been externally validated. Three studies considered time or cost implications of computing the model.

INTERPRETATION

There is no one model that is recommended for dementia risk prediction in population-based settings. Further, it is unlikely that one model will fit all. Consideration of the optimal features of new models should focus on methodology (setting/sample, model development and testing in a replication cohort) and the acceptability and cost of attaining the risk variables included in the prediction score. Further work is required to validate existing models or develop new ones in different populations as well as determine the ethical implications of dementia risk prediction, before applying the particular models in population or clinical settings.

Is air pollution associated with increased risk of cognitive decline? A systematic review

INTRODUCTION

exposure to air pollution has been shown to increase risk of inflammatory processes and risk of cardiovascular mortality. Such exposure may therefore also be a risk factor for cognitive impairment/dementia.

METHOD

a systematic review of the literature was conducted with databases searched using keywords for air pollution, cognitive decline and dementia. All identified abstracts and potentially relevant articles were double read. For those papers meeting the inclusion criteria, summary tables were prepared and papers quality assessed.

RESULTS

from 1,551 abstracts identified, 10 articles were retrieved of which two were rejected. Of the eight remaining six reported prevalent cognitive assessment with historical pollution exposure and two incident cognitive decline, also with historical pollution exposure. In general, an association was reported between exposure and poorer prevalent measures of cognitive function. Data were mixed for incident cognitive decline with one study finding an association and the other not. Reports were limited by a lack of detailed reporting, use of proxy measures of pollution exposure and a lack of clarity regarding cognitive testing methodology and analysis.

CONCLUSION

this systematic review highlights that there is some evidence of a potential association between air pollution and subsequent cognitive decline. Further work is clearly required and longitudinal analysis of ongoing cohort studies or new research would add much needed clarity to this area.

Usefulness of data from magnetic resonance imaging to improve prediction of dementia: population based cohort study

OBJECTIVE

To determine whether the addition of data derived from magnetic resonance imaging (MRI) of the brain to a model incorporating conventional risk variables improves prediction of dementia over 10 years of follow-up.

DESIGN

Population based cohort study of individuals aged ≥ 65.

SETTING

The Dijon magnetic resonance imaging study cohort from the Three-City Study, France.

PARTICIPANTS

1721 people without dementia who underwent an MRI scan at baseline and with known dementia status over 10 years' follow-up.

MAIN OUTCOME MEASURE

Incident dementia (all cause and Alzheimer's disease).

RESULTS

During 10 years of follow-up, there were 119 confirmed cases of dementia, 84 of which were Alzheimer's disease. The conventional risk model incorporated age, sex, education, cognition, physical function, lifestyle (smoking, alcohol use), health (cardiovascular disease, diabetes, systolic blood pressure), and the apolipoprotein genotype (C statistic for discrimination performance was 0.77, 95% confidence interval 0.71 to 0.82). No significant differences were observed in the discrimination performance of the conventional risk model compared with models incorporating data from MRI including white matter lesion volume (C statistic 0.77, 95% confidence interval 0.72 to 0.82; P=0.48 for difference of C statistics), brain volume (0.77, 0.72 to 0.82; P=0.60), hippocampal volume (0.79, 0.74 to 0.84; P=0.07), or all three variables combined (0.79, 0.75 to 0.84; P=0.05). Inclusion of hippocampal volume or all three MRI variables combined in the conventional model did, however, lead to significant improvement in reclassification measured by using the integrated discrimination improvement index (P=0.03 and P=0.04) and showed increased net benefit in decision curve analysis. Similar results were observed when the outcome was restricted to Alzheimer's disease.

CONCLUSIONS

Data from MRI do not significantly improve discrimination performance in prediction of all cause dementia beyond a model incorporating demographic, cognitive, health, lifestyle, physical function, and genetic data. There were, however, statistical improvements in reclassification, prognostic separation, and some evidence of clinical utility.

Alcohol consumption in the elderly and risk of dementia related death--a Norwegian prospective study with a 17-year follow-up

PURPOSE

The aim of this study was to determine the association between alcohol intake and risk of dementia related death, taking into account relevant confounding and mediating factors.

MATERIALS AND METHODS

Data was obtained from a Norwegian prospective study with a 17-year follow-up. The study population comprised 25,635 participants aged between 60 and 80 years at the time of examination from the Cohort of Norway (CONOR). Cox regression was used to investigate the association between alcohol use and dementia related death.

RESULTS

Nearly half (12,139) of the study population died during follow-up, of which 1,224 had a diagnosis of dementia on their death certificate. The risk of dementia related death was significantly higher among abstainers than among individuals that drank alcohol once per month (HR = 1.33, 95% CI = 1.14-1.56, p < 0.001, in a fully adjusted model). Respondents with missing information regarding alcohol consumption (representing 5% of the study population) had the highest risk of dementia related death (HR = 1.60, 95% CI = 1.28-2.00, p < 0.001) and also significantly higher mortality rates due to alcohol-related causes (HR = 1.41, 95% CI = 1.03-1.93, p = 0.031) and other causes (HR = 1.32, 95% CI = 1.21-1.43, p < 0.001), all compared to those drinking alcohol no more than once per month.

CONCLUSION

These findings suggest that the risk of dementia related death is significantly higher among elderly abstainers than among those who drink alcohol, after adjusting for relevant confounders. However, care should be taken in interpretation of data due to missing information on drinking frequency, as this missing-group might have a large share of the heavy drinkers in the study cohort.

Alzheimer's Disease prevalence, costs, and prevention for military personnel and veterans

By 2050, more than 13 million Americans of all ages are estimated to be living with Alzheimer's disease (AD), and the aggregate costs of care will swell to approximately $1.2 trillion. The rapidly climbing number of those affected with AD includes a growing population of aging military veterans affected who may have an added risk for the disease as a consequence of traumatic brain injury, posttraumatic stress disorder, and/or service-related injuries. The increasing number of individuals, the long duration of disability, and the rising cost of care for AD and other dementia to our society are important public health challenges facing many older adults. These challenges are further compounded by a burgeoning military veteran population that is much younger, with an increased risk of AD and other dementia, and who may experience decades-long periods of disability and care. This outlook underscores the critical need for investments in research at the federal and international levels to accelerate the pace of progress in developing breakthrough discoveries that will change the trajectory of AD and related dementia.

Effects of metabolic syndrome on language functions in aging

This study explored effects of the metabolic syndrome (MetS) on language in aging. MetS is a constellation of five vascular and metabolic risk factors associated with the development of chronic diseases and increased risk of mortality, as well as brain and cognitive impairments. We tested 281 English-speaking older adults aged 55-84, free of stroke and dementia. Presence of MetS was based on the harmonized criteria (Alberti et al., 2009). Language performance was assessed by measures of accuracy and reaction time on two tasks of lexical retrieval and two tasks of sentence processing. Regression analyses, adjusted for age, education, gender, diabetes, hypertension, and heart disease, demonstrated that participants with MetS had significantly lower accuracy on measures of lexical retrieval (action naming) and sentence processing (embedded sentences, both subject and object relative clauses). Reaction time was slightly faster on the test of embedded sentences among those with MetS. MetS adversely affects the language performance of older adults, impairing accuracy of both lexical retrieval and sentence processing. This finding reinforces and extends results of earlier research documenting the negative influence of potentially treatable medical conditions (diabetes, hypertension) on language performance in aging. The unanticipated finding that persons with MetS were faster in processing embedded sentences may represent an impairment of timing functions among older individuals with MetS.

Development and validation of risk index for cognitive decline using blood-derived markers

OBJECTIVE

We sought to develop and validate a risk index for prospective cognitive decline in older adults based on blood-derived markers.

METHODS

The index was based on 8 markers that have been previously associated with cognitive aging: APOE genotype, plasma β-amyloid 42/40 ratio, telomere length, cystatin C, glucose, C-reactive protein, interleukin-6, and albumin. The outcome was person-specific cognitive slopes (Modified Mini-Mental State Examination) from 11 years of follow-up. A total of 1,445 older adults comprised the development sample. An index based on dichotomized markers was divided into low-, medium-, and high-risk categories; the risk categories were validated with the remaining sample (n = 739) using linear regression. Amyloid was measured on a subsample (n = 865) and was included only in a secondary index.

RESULTS

The risk categories showed significant differences from each other and were predictive of prospective cognitive decline in the validation sample, even after adjustment for age and baseline cognitive score: the low-risk group (24.8%) declined 0.32 points/y (95% confidence interval [CI]: -0.46, -0.19), the medium-risk group (58.7%) declined 0.55 points/y (95% CI: -0.65, 0.45), and the high-risk group (16.6%) declined 0.69 points/y (95% CI: -0.85, -0.54). Using the secondary index, which included β-amyloid 42/40 (validation n = 279), the low-risk group (26.9%) declined 0.20 points/y (95% CI: -0.42, 0.01), the medium-risk group (61.3%) declined 0.55 points/y (95% CI: -0.72, -0.38), and the high-risk group (11.8%) declined 0.83 points/y (95% CI: -1.14, -0.51).

CONCLUSIONS

A risk index based on 8 blood-based markers was modestly able to predict cognitive decline over an 11-year follow-up. Further validation in other cohorts is necessary.

The red cell distribution width and anemia in association with prevalent dementia

The red cell distribution width (RDW), a measure of anisocytosis, independently predicts cardiovascular disease outcomes and chronic disease mortality. Little is known about the RDW, or the interplay between RDW and anemia, in relation to dementia risk. We evaluated the association between the RDW and prevalent dementia, overall and by anemia status, among 2556 community-dwelling older adults participating in the Chicago Health and Aging Project. RDW measurements came from complete blood counts, and participants underwent diagnosis for dementia according to standard clinical criteria. Five hundred twenty-five participants were diagnosed with dementia. Elevated RDW was associated with increased odds of having dementia: after adjusting for age, sex, race, and education, the odds of prevalent dementia increased progressively over increasing quartile of RDW (Ptrend=0.02), and persons in the highest RDW quartile (≥14.8%) had 42% greater odds of having dementia than those in the lowest quartile [odds ratio (OR), 1.42; 95% confidence interval (CI), 1.05-1.92)]. Per unit (%) increment in RDW, the odds of dementia were higher by 6% (OR, 1.06; 95% CI, 1.00-1.13). Findings were similar upon further adjustment for health behaviors and diabetes. In analyses adjusted for hemoglobin concentration, the RDW-dementia association was attenuated, whereas the inverse association between hemoglobin and dementia remained significant. However, RDW was associated with dementia more strongly among participants without anemia (OR, 1.09; 95% CI, 1.00-1.43) than among those with anemia (OR, 0.99; 95% CI, 0.86-1.18), although this difference was not statistically significant. The RDW, a readily available and inexpensive hematologic measure, may offer novel information about dementia risk, particularly among persons without anemia. Future studies should establish the RDW's ability to predict risk prospectively.

Carotid plaque as a predictor of dementia in older adults: the Three-City Study

BACKGROUND

The contribution of carotid atherosclerosis to incident dementia remains unclear. We examined the association between carotid plaques (CP) and common carotid intima media thickness (CCA-IMT) with incident dementia and its subtypes, and their added value for dementia risk prediction.

METHODS

At baseline, 6025 dementia-free subjects aged 65-86 years underwent bilateral carotid ultrasonography measures of CP and plaque-free CCA-IMT. Subjects were followed-up over 7 years for the detection of dementia.

RESULTS

After a mean 5.4 years of follow-up, 421 subjects developed dementia including 272 Alzheimer's disease and 83 vascular/mixed dementia (VaD). Only CP were independently related to VaD (HR(≥2 sites with plaques) = 1.92; 95% confidence interval or CI = 1.13-3.22) and improved VaD risk prediction (continuous Net Reclassification Index = 30.1%; 95% CI = 8.4-51.7) beyond known dementia risk factors. Accounting for stroke or competing risk by death marginally modified the results.

CONCLUSION

In older adults, CP are independent predictors of incident VaD and may improve VaD risk prediction.