Multiple Cognitive and Behavioral Factors Link Association Between Brain Structure and Functional Impairment of Daily Instrumental Activities in Older Adults

Does Mild Functional Impairment Predict Dementia in Older Adults With Normal Cognition?

OBJECTIVES

Functional impairment can be an early indicator of cognitive decline. However, its predictive utility in cognitively normal (CN) older adults remains unclear. This study aimed to determine whether mild functional impairment (MFI) in CN older adults could predict incident dementia over 6 years, in addition to assessing its association with cognitive performance.

DESIGN

A longitudinal study with a 6-year follow-up.

PARTICIPANTS

A cohort of 296 community-dwelling CN older adults.

MEASUREMENTS

MFI was defined by cutoffs for impairment on an objective performance-based and/or subjective questionnaire-based functional assessment. Cox regression analysis was conducted to assess the relationship between MFI and risk of incident dementia and cognitive performances over 6 years. Linear regression analysis examined the association between MFI and baseline cognitive performance.

RESULTS

There were no significant longitudinal associations between MFI and incident dementia or changes in cognitive performance over 6 years. Defining MFI using both performance-based and informant-reported assessments was predictive of dementia. Cross-sectional analyses demonstrated significant associations between MFI and poorer baseline global cognition and performance in attention, visuospatial ability, and executive functioning.

CONCLUSIONS

CN older adults with MFI were not at an increased risk of developing dementia over 6 years. A definition of functional impairment requiring both performance-based and informant-based assessments may be useful in predicting dementia.

Time restricted feeding is associated with poor performance in specific cognitive domains of Suburb-Dwelling older Chinese

The purpose of this study was to investigate the association between time restricted feeding (TRF) and different areas of cognitive function in the elderly in Chinese communities. This study consisted of 1353 community-dwelling Chinese older adults aged 60 years and older in Chongming area, Shanghai (563 males; the mean age, 73.38 ± 6.16 years). Mild cognitive impairment (MCI) and six different cognitive domains was assessed by the Chinese-version of Mini Mental State Examination (MMSE). Recording the eating time of each meal through oral inquiry to calculate the time window between the first meal and the last meal of the average day. Participants with an eating time window duration of more than 10 h were then identified, as well as those with eating time restricted to less than 10 h (TRF). Our study found that TRF may be associated with a higher incidence rate of cognitive impairment. TRF only limited the eating time window and did not change the frequency of participants' dietary intake. We used a linear regression model to study the association of TRF with cognitive function. After adjusting for confounding variables, the results showed that TRF was related to MMSE score (P < 0.001), "Orientation to place" (P < 0.001) and "Attention/calculation" (P < 0.001) functions. Among Chinese older community-dwellers, TRF was associated with a higher prevalence of CI and negatively correlated with the "Orientation to place" and "attention/calculation" functions.

Elevated Anxious and Depressed Mood Relates to Future Executive Dysfunction in Older Adults: A Longitudinal Network Analysis of Psychopathology and Cognitive Functioning

Vulnerability models posit that executive-functioning (EF) problems centrally affect future common (vs. rare) psychopathology symptoms. Conversely, scar theory postulates that depression/anxiety (vs. other psychopathology) symptoms centrally influence reduced EF. However, most studies so far have been cross-sectional. We used cross-lagged panel network analysis to determine temporal and component-to-component relations on this topic. Community older adults participated across four time points. Cognitive tests and the caregiver-rated Neuropsychiatric Inventory assessed nine psychopathology and eight cognitive-functioning nodes. Nodes with the highest bridge expected influence cross-sectionally were agitation and episodic memory. Episodic memory had the strongest inverse relation with age. Agitation had the strongest negative association with global cognition. EF nodes tended to be centrally affected by prior depressed and anxious moods rather than influential on any future nodes. Heightened anxious and depressed mood (vs. other nodes) centrally predicted future decreased EF-related (vs. non-EF-related) nodes in older adults, supporting scar (vs. vulnerability) theory.

Aging changes the interactions between the oculomotor and memory systems

The use of multi-modal approaches, particularly in conjunction with multivariate analytic techniques, can enrich models of cognition, brain function, and how they change with age. Recently, multivariate approaches have been applied to the study of eye movements in a manner akin to that of neural activity (i.e., pattern similarity). Here, we review the literature regarding multi-modal and/or multivariate approaches, with specific reference to the use of eyetracking to characterize age-related changes in memory. By applying multi-modal and multivariate approaches to the study of aging, research has shown that aging is characterized by moment-to-moment alterations in the amount and pattern of visual exploration, and by extension, alterations in the activity and function of the hippocampus and broader medial temporal lobe (MTL). These methodological advances suggest that age-related declines in the integrity of the memory system has consequences for oculomotor behavior in the moment, in a reciprocal fashion. Age-related changes in hippocampal and MTL structure and function may lead to an increase in, and change in the patterns of, visual exploration in an effort to upregulate the encoding of information. However, such visual exploration patterns may be non-optimal and actually reduce the amount and/or type of incoming information that is bound into a lasting memory representation. This research indicates that age-related cognitive impairments are considerably broader in scope than previously realized.

Utility of Machine Learning Approach with Neuropsychological Tests in Predicting Functional Impairment of Alzheimer's Disease

Background:

In assessing the levels of clinical impairment in dementia, a summary index of neuropsychological batteries has been widely used in describing the overall functional status.

Objective:

It remains unexamined how complex patterns of the test performances can be utilized to have specific predictive meaning when the machine learning approach is applied.

Methods:

In this study, the neuropsychological battery (CERAD-K) and assessment of functioning level (Clinical Dementia Rating scale and Instrumental Activities of Daily Living) were administered to 2,642 older adults with no impairment (n = 285), mild cognitive impairment (n = 1,057), and Alzheimer’s disease (n = 1,300). Predictive accuracy on functional impairment level with the linear models of the single total score or multiple subtest scores (Model 1, 2) and support vector regression with low or high complexity (Model 3, 4) were compared across different sample sizes.

Results:

The linear models (Model 1, 2) showed superior performance with relatively smaller sample size, while nonlinear models with low and high complexity (Model 3, 4) showed an improved accuracy with a larger dataset. Unlike linear models, the nonlinear models showed a gradual increase in the predictive accuracy with a larger sample size (n > 500), especially when the model training is allowed to exploit complex patterns of the dataset.

Conclusion:

Our finding suggests that nonlinear models can predict levels of functional impairment with a sufficient dataset. The summary index of the neuropsychological battery can be augmented for specific purposes, especially in estimating the functional status of dementia.