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Risk Factors Associated With Cognitive, Functional, and Behavioral Trajectories of Newly Diagnosed Dementia Patients.

ABSTRACT: Dementia results in changes in cognition, function, and behavior. We examine the effect of sociodemographic and clinical risk factors on cognitive, functional, and behavioral declines in incident dementia patients.We used longitudinal data from the National Alzheimer's Coordinating Center to evaluate cognitive (Mini-Mental State Exam [MMSE]), functional (Functional Activities Questionnaire [FAQ]), and behavioral (Neuropsychiatric Inventory Questionnaire [NPI-Q] severity score) trajectories for incident dementia patients over an 8-year period. We evaluated trajectories of 457 patients with mixed effects linear regression models.In the first year, cognition worsened by -1.518 (95% confidence interval [CI] -1.745, -1.291) MMSE points (0-30 scale). Education, race, and region of residence predicted cognition at diagnosis. Age of onset, geographic region of residence, and history of hypertension and congestive heart failure predicted cognitive changes. Function worsened by 3.464 (95% CI 3.131, 3.798) FAQ points in the first year (0-30 scale). Cognition, gender, race, region of residence and place of residence, and a history of stroke and hypercholesterolemia predicted function at diagnosis. Place of residence and a history of diabetes predicted functional changes. Behavioral symptoms worsened by 0.354 (95% CI 0.123, 0.585) NPI-Q points in the first year (0-36 scale). Age of onset, region of residence, and history of hypertension and psychiatric problems predicted behaviors at diagnosis. Cognition explained changes in behavior.Sociodemographic characteristics and clinical comorbidities predict cognitive and functional changes. Only cognitive status explains behavioral decline. Results provide an understanding of the characteristics that impact cognitive, functional, and behavioral decline.

SUBMITTER: Jutkowitz E

PROVIDER: S-EPMC5344797 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Risk Factors Associated With Cognitive, Functional, and Behavioral Trajectories of Newly Diagnosed Dementia Patients.

Jutkowitz Eric E MacLehose Richard F RF Gaugler Joseph E JE Dowd Bryan B Kuntz Karen M KM Kane Robert L RL

The journals of gerontology. Series A, Biological sciences and medical sciences 20160429 2

<h4>Background</h4>Dementia results in changes in cognition, function, and behavior. We examine the effect of sociodemographic and clinical risk factors on cognitive, functional, and behavioral declines in incident dementia patients.<h4>Methods</h4>We used longitudinal data from the National Alzheimer's Coordinating Center to evaluate cognitive (Mini-Mental State Exam [MMSE]), functional (Functional Activities Questionnaire [FAQ]), and behavioral (Neuropsychiatric Inventory Questionnaire [NPI-Q] ...[more]

PMID: 27129917

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Project description:Background and objectivesCognitive reserve (CR) is meant to account for the mismatch between brain damage and cognitive decline or dementia. Generally, CR has been operationalized using proxy variables indicating exposure to enriching activities (activity-based CR). An alternative approach defines CR as residual variance in cognition, not explained by the brain status (residual-based CR). The aim of this study is to compare activity-based and residual-based CR measures in their association with cognitive trajectories and dementia. Furthermore, we seek to examine if the two measures modify the impact of brain integrity on cognitive trajectories and if they predict dementia incidence independent of brain status.MethodsWe used data on 430 older adults aged 60+ from the Swedish National Study on Aging and Care in Kungsholmen, followed for 12 years. Residual-based reserve was computed from a regression predicting episodic memory with a brain-integrity index incorporating six structural neuroimaging markers (white-matter hyperintensities volume, whole-brain gray matter volume, hippocampal volume, lateral ventricular volume, lacunes, and perivascular spaces), age, and sex. Activity-based reserve incorporated education, work complexity, social network, and leisure activities. Cognition was assessed with a composite of perceptual speed, semantic memory, letter-, and category fluency. Dementia was clinically diagnosed in accordance with DSM-IV criteria. Linear mixed models were used for cognitive change analyses. Interactions tested if reserve measures modified the association between brain-integrity and cognitive change. Cox proportional hazard models, adjusted for brain-integrity index, assessed dementia risk.ResultsBoth reserve measures were associated with cognitive trajectories [β × time (top tertile, ref.: bottom tertile) = 0.013; 95% CI: -0.126, -0.004 (residual-based) and 0.011; 95% CI: -0.001, 0.024, (activity-based)]. Residual-based, but not activity-based reserve mitigated the impact of brain integrity on cognitive decline [β (top tertile × time × brain integrity) = -0.021; 95% CI: -0.043, 0.001] and predicted 12-year dementia incidence, after accounting for the brain-integrity status [HR (top tertile) = 0.23; 95% CI: 0.09, 0.58].InterpretationThe operationalization of reserve based on residual cognitive performance may represent a more direct measure of CR than an activity-based approach. Ultimately, the two models of CR serve largely different aims. Accounting for brain integrity is essential in any model of reserve.

Project description:ImportanceIncident atrial fibrillation (AF) is associated with an increased risk of dementia. However, data on the association between smoking cessation after AF diagnosis and dementia risk are limited.ObjectiveTo evaluate the association between changes in smoking status after AF diagnosis and dementia risk.Design, setting, and participantsThis nationwide cohort study with 126 252 patients used data from the Korean National Health Insurance Service database, including patients who had a national health checkup examination within 2 years before and after AF diagnosis between January 1, 2010, and December 31, 2016. Based on their smoking status, participants were classified as never smokers, ex-smokers, quit smokers, and current smokers. Ex-smokers were defined as those who had quit smoking before the first examination and remained quit until the second examination. Patients who were current smokers at the first health examination but had quit smoking before the second examination were classed as quit smokers. The index date was the second health examination. Patients were followed up until dementia, death, or the study period ended (December 31, 2017), whichever occurred first. Data were analyzed from January 13, 2020, to March 29, 2022.ExposuresSmoking cessation after newly diagnosed AF.Main outcomes and measuresDementia, including Alzheimer disease and vascular dementia, was the primary outcome. Cox proportional hazards regression model was used to estimate hazard ratios.ResultsA total of 126 252 patients (mean [SD] age, 62.6 [12.0] years; 61.9% men) were included in the analysis. The mean (SD) CHA2DS2-VASc score, which measures the risk of ischemic stroke, was 2.7 (1.7). Smoking status of the total study population was as follows: 65 579 never smokers (51.9%), 34 670 ex-smokers (27.5%), 8919 quit smokers (7.1%), and 17 084 current smokers (13.5%). During a median of 3 years of follow-up, dementia occurred in 5925 patients (1.11 per 1000 person-years). After multivariable adjustment, the risk of quit smokers was significantly lower than that of current smokers (hazard ratio, 0.83 [95% CI, 0.72-0.95]).Conclusions and relevanceThe findings of this cohort study suggest that all types of smoking were associated with a significantly higher risk of dementia in patients with new-onset AF. Smoking cessation after AF diagnosis was associated with a lower risk of dementia than among current smokers. These findings may support promoting smoking cessation to reduce dementia risk in patients with new-onset AF.

Project description:BackgroundIn cognitively normal individuals, subjective cognitive decline (SCD) has been reported to predict MCI and dementia (MCI/dementia). However, prior studies mostly captured SCD at single time-points without considering the longitudinal course of SCD. This study examined whether the trajectories of SCD provide any added information-beyond one-time assessments of SCD-on the risk of MCI/dementia.MethodsThis cohort study included 5661 participants from the Alzheimer's Disease Centers across the USA, who were ≥ 50 years and had normal cognition in the first-four annual visits (year 1 to year 4). The participants were evaluated for SCD in the first-four annual visits (year 1 to year 4), and followed-up almost annually (year 4 up to year 14) for incident MCI/dementia. SCD trajectories (as identified from latent-class-growth-curve-analysis) were included in Cox regression to estimate their risks of MCI/dementia, with analyses further stratified by age (< 75 years versus ≥ 75 years; based on median-split).ResultsCompared to those without SCD (in the first-four annual visits), Intermittent SCD (i.e., reported in 1-2 of the first-four annual visits) predicted a higher risk (HR 1.4) and Persistent SCD (i.e., reported in 3-4 of the first-four annual visits) predicted the highest risk (HR 2.2), with the results remaining significant even after adjusting for baseline SCD. Age-stratified analysis revealed that the risk associated with Intermittent SCD was only present in older individuals, while risk related to Persistent SCD was consistently present across the younger and older age groups. Age compounded the effects of the trajectories, whereby older individuals with Persistent SCD had > 75% probability of developing MCI/dementia by 10 years, in contrast to < 25% probability by 10 years in younger individuals with No SCD.ConclusionsThe findings demonstrate the utility of SCD trajectories-especially when used in combination with age strata-in identifying high-risk populations for preventive interventions and trials. They also suggest a potential modification in the current SCD criteria, with the inclusion of "persistent SCD over several years" as a feature of SCD plus.

Project description:ObjectiveThere is variability across individuals in cognitive aging. To investigate the associations of several modifiable factors with high and low cognitive performance.MethodsData came from 17,724 community-dwelling individuals aged 65-98 years. Global cognition, verbal fluency, episodic memory, and psychomotor speed were assessed over up to seven years. Group-based multi-trajectory modeling identified distinct cognitive trajectories. Structural equation modeling examined the direct/indirect associations of social/behavioral factors and several chronic conditions with cognitive trajectories.ResultsSeven trajectory subgroups were identified. In the structural equation modeling we compared two subgroups-participants with the highest (14.2%) and lowest (4.1%) cognitive performance with the average subgroup. Lower education, never alcohol intake, and frailty directly predicted increased risk of low performance, and decreased likelihood of high performance. Hypertension (RR: 0.69, 95%CI: 0.60-0.80), obesity (RR: 0.84, 95%CI: 0.73-0.97), diabetes (RR: 0.69, 95%CI: 0.56-0.86) and depression (RR: 0.68, 95%CI: 0.54-0.85) only predicted lower likelihood of high cognitive performance, while dyslipidemia was only associated with low performance (RR: 1.30, 95%CI: 1.07-1.57). Living alone predicted increased risk of low cognitive performance and several comorbidities. Smoking did not predict cognitive trajectories but was associated with increased risk of diabetes, obesity and frailty. Findings were similar when examining the direct associations between modifiable risk factors and all seven cognitive subgroups.ConclusionsAlthough several modifiable factors were associated with high performance, and reversely with low performance, this was not observed for obesity, hypertension and dyslipidemia. Further, health behaviors may affect cognitive function indirectly, via geriatric conditions. This indicates that strategies to promote healthy cognitive aging, may be distinct from those targeting dementia prevention.

Dataset Information

Risk Factors Associated With Cognitive, Functional, and Behavioral Trajectories of Newly Diagnosed Dementia Patients.

Publications

Risk Factors Associated With Cognitive, Functional, and Behavioral Trajectories of Newly Diagnosed Dementia Patients.

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