Performance-Based vs Informant-Reported Instrumental Activities of Daily Living in Predicting Dementia

Prevalence of cognitive impairment and associated factors in older people

BACKGROUND

Older people are the fastest-growing age group, with the highest risk of cognitive impairment. This study assessed the prevalence and associated factors with cognitive impairment in community-dwelling older people.

METHODS

Older people were interviewed and accomplished through sociodemographic and health questionnaires. The quantitative variables were described by mean and standard deviation or median and interquartile range. The significance level adopted was 5 % (p < 0.05). The association between the quantitative variables was evaluated using the Pearson or Spearman correlation coefficients.

RESULTS

The research population comprised 165 long-lived adults aged ≥80. The youngest one was 80, and the oldest one was 94 years old. The participants were 84.8 ± 3.6 years old, female (63 %) with a mean of education of 2.9 ± 1.8 years. A poor performance in the Mini-Mental State Examination (MMSE) was found in 58 (35.2 %) individuals when adjusted for educational level. After adjustment for confounding factors, body mass index (BMI) (p = 0.09), total older adults' income (up to 1 minimum wage [mw], p = 0.023; over 1 to 2 mw, p = 0.023), functional disability (Moderate dependence 75 %, p = 0.038; Moderate dependence 50 %, p = 0.081; Moderate dependence 25 %, p = 0.054), and the anxiety scale (p = 0.032), remained associated with cognitive impairment.

CONCLUSIONS

This study showed that BMI, total older adults' income, functional disability, and anxiety are related to cognitive impairment in long-lived adults. This study has some limitations, such as the fact that it is a cross-sectional study, the reduced number of individuals, and the fact that there were no comparisons among different ages and populations.

Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health

Background

EPs pose significant challenges to individual health and quality of life, attracting attention in public health as a risk factor for diminished quality of life and healthy life expectancy in middle-aged and older adult populations. Therefore, in the context of global aging, meticulous exploration of the factors behind emotional issues becomes paramount. Whether ADL can serve as a potential marker for EPs remains unclear. This study aims to provide new evidence for ADL as an early predictor of EPs through statistical analysis and validation using machine learning algorithms.

Methods

Data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) national baseline survey, comprising 9,766 samples aged 45 and above, were utilized. ADL was assessed using the BI, while the presence of EPs was evaluated based on the record of "Diagnosed with Emotional Problems by a Doctor" in CHARLS data. Statistical analyses including independent samples t-test, chi-square test, Pearson correlation analysis, and multiple linear regression were conducted using SPSS 25.0. Machine learning algorithms, including Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR), were implemented using Python 3.10.2.

Results

Population demographic analysis revealed a significantly lower average BI score of 65.044 in the "Diagnosed with Emotional Problems by a Doctor" group compared to 85.128 in the "Not diagnosed with Emotional Problems by a Doctor" group. Pearson correlation analysis indicated a significant negative correlation between ADL and EPs (r = -0.165, p < 0.001). Iterative analysis using stratified multiple linear regression across three different models demonstrated the persistent statistical significance of the negative correlation between ADL and EPs (B = -0.002, β = -0.186, t = -16.476, 95% CI = -0.002, -0.001, p = 0.000), confirming its stability. Machine learning algorithms validated our findings from statistical analysis, confirming the predictive accuracy of ADL for EPs. The area under the curve (AUC) for the three models were SVM-AUC = 0.700, DT-AUC = 0.742, and LR-AUC = 0.711. In experiments using other covariates and other covariates + BI, the overall prediction level of machine learning algorithms improved after adding BI, emphasizing the positive effect of ADL on EPs prediction.

Conclusion

This study, employing various statistical methods, identified a negative correlation between ADL and EPs, with machine learning algorithms confirming this finding. Impaired ADL increases susceptibility to EPs.

Analysis of Convergent Validity of Performance-Based Activities of Daily Living Assessed by PA-IADL Test in Relation to Traditional (Standard) Cognitive Assessment to Identify Older Adults with Mild Cognitive Impairment

Difficulty in performing instrumental activities of daily living (IADLs) is currently considered an important indicator of cognitive impairment in the elderly. A non-experimental case-control investigation was conducted to assess the convergent validity of the PA-IADL with traditional (standard) cognitive assessment tests in its ability to identify adults with mild cognitive impairment. The analysis of the data was carried out by means of various multivariate statistical tests, and the sequence in its execution led to the conclusion that 8 of the 12 Tasks that make up the PA-IADL allow for the identification of people with mild cognitive impairment (MCI) to the same extent as traditional cognitive assessment tests and regardless of age. Age was found to be a moderating variable in the performance of the eight tasks; however, the results allow us to hypothesize that people with MCI experience a significant decline when it happens but thereafter, the deterioration that occurs does so at the same rate as the deterioration experienced by healthy people. They also allow us to hypothesize that the difference in the cognitive skills required by the eight functional tasks, and therefore also in the cognitive skills required by the traditional (standard) tests of a person with MCI compared to a person of the same age without MCI (Healthy), is approximately 10 years. These hypotheses have remarkable relevance and should be tested via longitudinal research. In the meantime, the results highlight the importance of the IADL assessment for the diagnosis of MCI as a complement to the standard cognitive assessment.

Effects of computer-based cognitive training combined with physical training for older adults with cognitive impairment: A four-arm randomized controlled trial

Objective

Combined physical (PHY) and cognitive (COG) training in sequential (SEQ) and simultaneous (SIMUL) sessions may delay the progression of cognitive impairment. To date, no study has directly compared in older adults with cognitive impairment the effects of COG training, PHY training, SEQ motor-cognitive training and SIMUL motor-cognitve training on specific indices of cognitive performance and activities of daily living (ADL). The purpose of this study was to determine whether SEQ and SIMUL motor-cognitive training can improve treatment outcomes compared with PHY or COG training alone. We also aimed to compare the effects of SEQ versus SIMUL motor-cognitive training on cognitive functions and instrumental ADL (IADL) in older adults with cognitive impairment.

Methods

A cluster randomized controlled trial was conducted. Eighty older adults with cognitive impairment were randomly assigned to COG, PHY, SEQ or SIMUL training groups. The intervention consisted of 90-min training sessions, totaling 36 sessions. Outcome measures were the Montreal Cognitive Assessment, three subtests of the Wechsler Memory Scale (WMS) and the Lawton IADL scale.

Results

Significant interaction effects between group and time were found in WMS-spatial span (p = 0.04) and WMS-word lists (p = 0.041). For WMS-spatial span, the SIMUL group showed outperformed the COG (p = 0.039), PHY (p = 0.010) and SEQ groups (p = 0.017). For WMS-word lists, the SEQ group improve more than COG (p = 0.013), PHY (p = 0.030) and SIMUL (p = 0.019) groups. No significant differences were found in IADL performance among four groups (p = 0.645).

Conclusions

Our study showed SEQ and SIMUL motor-cognitive training led to more pronounced improvements in visuospatial working memory or verbal memory compared with isolated COG or PHY training for community-based older adults with cognitive impairment. For enhancing effects on IADL, we suggest the use of sensitive measurement tools and context-enriched cognitive training involving real-life task demands.