Heterogeneity in the dynamic change of cognitive function among older Chinese people: A growth mixture model

Bidirectional associations between hearing difficulty and cognitive function in Chinese adults: a longitudinal study

Background

Middle-aged and older adults frequently experience hearing loss and a decline in cognitive function. Although an association between hearing difficulty and cognitive function has been demonstrated, its temporal sequence remains unclear. Therefore, we investigated whether there are bidirectional relationships between hearing difficulty and cognitive function and explored the mediating role of depressive symptoms in this relationship.

Method

We used the cross-lagged panel model and the random-intercept cross-lagged panel model to look for any possible two-way link between self-reported hearing difficulty and cognitive function. To investigate depressive symptoms' role in this association, a mediation analysis was conducted. The sample was made up of 4,363 adults aged 45 and above from the China Health and Retirement Longitudinal Study (CHARLS; 2011-2018; 44.83% were women; mean age was 56.16 years). One question was used to determine whether someone had a hearing impairment. The tests of cognitive function included episodic memory and intelligence. The Center for Epidemiologic Studies Depression Scale, which consists of 10 items, was used to measure depressive symptoms.

Results

A bidirectional association between hearing and cognition was observed, with cognition predominating (Wald χ2 (1) = 7.241, p < 0.01). At the between-person level, after controlling for potential confounders, worse hearing in 2011 predicted worse cognitive function in 2013 (β = -0.039, p < 0.01) and vice versa (β = -0.041, p < 0.01) at the between-person level. Additionally, there was no corresponding cross-lagged effect of cognitive function on hearing difficulty; rather, the more hearing difficulty, the greater the cognitive decline at the within-person level. According to the cross-lagged mediation model, depressive symptoms partially mediates the impact of cognitive function on subsequent hearing difficulty (indirect effect: -0.003, bootstrap 95% confidence interval: -0.005, -0.001, p < 0.05), but not the other way around.

Conclusion

These results showed that within-person relationships between hearing impairment and cognitive function were unidirectional, while between-person relationships were reciprocal. Setting mental health first may be able to break the vicious cycle that relates hearing loss to cognitive decline. Comprehensive long-term care requires services that address depressive symptoms and cognitive decline to be integrated with the hearing management.

Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors

Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.

Openness to experience and cognitive functioning and decline in older adults: The mediating role of cognitive reserve

OBJECTIVE

Openness to experience has been consistently associated with better cognitive functioning in older people, but its association with cognitive decline is less clear. Cognitive reserve has been proposed as a mechanism underlying this relationship, but previous studies have reported mixed findings, possibly due to the different ways of conceptualizing cognitive reserve. We aimed to analyze the potential mediating role of cognitive reserve in the association between openness and cognitive functioning and decline in healthy older people.

METHOD

In Wave 1 and at the four-year follow-up (Wave 2), 87 healthy older people (49.4% women; M age = 65.08, SD = 4.54) completed a neuropsychological battery to assess cognitive functioning and a questionnaire to assess cognitive reserve. Openness was measured with the NEO- Five-Factor Inventory. Mediation models were proposed to investigate the relationship between openness and cognitive function or decline through cognitive reserve or its change.

RESULTS

Cognitive reserve mediated the openness-cognitive functioning association. Thus, individuals with higher openness showed greater cognitive reserve, and this greater cognitive reserve was associated with better cognitive functioning. Moreover, greater cognitive reserve at baseline also mediated the association between higher openness and slower cognitive decline. However, change in cognitive reserve did not mediate the association between openness and change in cognitive functioning.

CONCLUSIONS

Cognitive reserve is a mechanism underlying the association between openness and cognitive functioning and decline. These findings support the differential preservation hypothesis, suggesting that healthy older adults who engage in more cognitively stimulating activities would show less age-related cognitive decline.

Proteomic clusters underlie heterogeneity in preclinical Alzheimer's disease progression

Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.

Long-term trajectories of depressive symptoms and machine learning techniques for fall prediction in older adults:Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

BACKGROUND

Falls are the most common adverse outcome of depression in older adults, yet a accurate risk prediction model for falls stratified by distinct long-term trajectories of depressive symptoms is still lacking.

METHODS

We collected the data of 1617 participants from the China Health and Retirement Longitudinal Study register, spanning between 2011 and 2018. The 36 input variables included in the baseline survey were regarded as candidate features. The trajectories of depressive symptoms were classified by the latent class growth model and growth mixture model. Three data balancing technologies and four machine learning algorithms were utilized to develop predictive models for fall classification of depressive prognosis.

RESULTS

Depressive symptom trajectories were divided into four categories, i.e., non-symptoms, new-onset increasing symptoms, slowly decreasing symptoms, and persistent high symptoms. The random forest-TomekLinks model achieved the best performance among the case and incident models with an AUC-ROC of 0.844 and 0.731, respectively. In the chronic model, the gradient boosting decision tree-synthetic minority oversampling technique obtained an AUC-ROC of 0.783. In the three models, the depressive symptom score was the most crucial component. The lung function was a common and significant feature in both the case and the chronic models.

CONCLUSIONS

This study suggests that the ideal model has a good chance of identifying older persons with a high risk of falling stratified by long-term trajectories of depressive symptoms. Baseline depressive symptom score, lung function, income, and injury experience are influential factors associated with falls of depression evolution.

Associations between trajectories of cardiovascular risk factor change and cognitive impairment in Chinese elderly: A nationwide cohort study

Objectives

This study aimed to investigate the relationship between long-term trajectories of changes in cardiovascular risk factors (CVRFs) and the risk of cognitive impairment among Chinese adults over 60 years old.

Methods

Data were obtained from the Chinese Longitudinal Healthy Longevity Survey 2005-2018. Cognitive function was evaluated longitudinally through the Chinese version of the Mini-Mental State Examination (C-MMSE), and cognitive impairment (C-MMSE ≤23) was used as the main outcome variable. The cardiovascular risk factors, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), pulse pressure (PP), and body mass index (BMI), were continuously measured in the follow-up duration. The patterns of trajectories of changes in CVRFs were derived from the latent growth mixture model (LGMM). The Cox regression model was used to evaluate the cognitive impairment hazard ratio (HR) across different CVRF trajectories.

Results

A total of 5,164 participants aged ≥60 years with normal cognitive function at baseline were included in the study. After a median follow-up of 8 years, 2,071 participants (40.1%) developed cognitive impairment (C-MMSE ≤ 23). The four-class trajectories of SBP and BMI were obtained by means of LGMM, and the trajectories of DBP, MAP, and PP were grouped into a three-class subgroup. In the final adjusted Cox model, the lowered SBP [adjusted HR (aHR): 1.59; 95% CI: 1.17-2.16], lowered PP (aHR: 2.64; 95% CI: 1.66-4.19), and progressively obese (aHR: 1.28; 95% CI: 1.02-1.62) and stable slim (aHR: 1.13; 95% CI: 1.02-1.25) were associated with the higher risk of cognitive impairment. Low stable DBP (aHR: 0.80; 95% CI: 0.66-0.96) and elevated PP (aHR: 0.76; 95% CI: 0.63-0.92) decreased the risk for cognitive impairment among participants.

Conclusion

Lowered SBP, lowered PP, progressive obesity, and stable slim increased the risk for cognitive impairment in the Chinese elderly. Low stable DBP and elevated PP were protective against cognitive impairment, but more DBP lowering and ≥25 mmHg growth in PP contributed to a higher risk of cognitive impairment. The findings have important implications for preventing cognitive impairment in elder adults based on the long-term trajectories of changes in CVRFs.

Prediction of depressive symptoms onset and long-term trajectories in home-based older adults using machine learning techniques

OBJECTIVES

Our aim was to explore the possibility of using machine learning (ML) in predicting the onset and trajectories of depressive symptom in home-based older adults over a 7-year period.

METHODS

Depressive symptom data (collected in the year 2011, 2013, 2015 and 2018) of home-based older Chinese (n = 2650) recruited in the China Health and Retirement Longitudinal Study (CHARLS) were included in the current analysis. The latent class growth modeling (LCGM) and growth mixture modeling (GMM) were used to classify different trajectory classes. Based on the identified trajectory patterns, three ML classification algorithms (i.e. gradient boosting decision tree, support vector machine and random forest) were evaluated with a 10-fold cross-validation procedure and a metric of the area under the receiver operating characteristic curve (AUC).

RESULTS

Four trajectories were identified for the depressive symptoms: no symptoms (63.9%), depressive symptoms onset {incident increasing symptoms [new-onset increasing (16.8%)], chronic symptoms [slowly decreasing (12.5%), persistent high (6.8%)]}. Among the analyzed baseline variables, the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) score, cognition, sleep time, self-reported memory were the top five important predictors across all trajectories. The mean AUCs of the three predictive models had a range from 0.661 to 0.892.

CONCLUSIONS

ML techniques can be robust in predicting depressive symptom onset and trajectories over a 7-year period with easily accessible sociodemographic and health information.

Supplemental data for this article is available online at http://dx.doi.org/10.1080/13607863.2022.2031868.

Joint developmental trajectories and temporal precedence of physical function decline and cognitive deterioration: A longitudinal population-based study

Objectives

Previous studies primarily explored the unidirectional impact of cognition on physical function. However, the interplay between physical function and cognition and the temporal precedence in their predictive relationships have not been elucidated. We explored the bidirectional mechanism between physical function and cognition in a longitudinal dataset.

Materials and methods

A total of 1,365 participants in the Chinese Longitudinal Healthy Longevity Survey assessed physical function and cognition in 2011 (T1), 2014 (T2), and 2018 (T3) by the Katz scale and the Chinese version of the Mini-Mental State Examination scale, respectively. Changes in the trajectories of physical function and cognition were examined using the latent growth model. The correlational and reciprocal relationships between physical function and cognition were examined using the parallel process latent growth model and autoregressive cross-lagged (ARCL) models.

Results

Cognition and physical function decreased by an average of 0.096 and 0.017 points per year, respectively. Higher physical function was associated with better cognition at baseline (r = 0.237, p &lt; 0.05), and longitudinal changes in physical function and cognition were positively correlated (r = 0.756, p &lt; 0.05). ARCL analysis indicated that physical function at T1 positively predicted T2 cognitive function. However, this predictive relationship reversed between T2 and T3, whereby cognitive function at T2 predicted physical function at T3.

Conclusion

Both physical function and cognition declined over time. Early identification and intervention in physical dysfunction among older adults could be critical to prevent further cognitive impairment and maintain functional independence. Hence, regular functional assessment and individualized care plans are required to achieve healthy aging.

Predicting the long-term cognitive trajectories using machine learning approaches: A Chinese nationwide longitudinal database

OBJECTIVES

This study aimed to explore the long-term cognitive trajectories and its' determinants, and construct prediction models for identifying high-risk populations with unfavorable cognitive trajectories.

METHODS

This study included 3502 older adults aged 65-105 years at their first observations in a 16-year longitudinal cohort study. Cognitive function was measured by the Chinese version Mini Mental State Examination. The heterogeneity of cognitive function was identified through mixed growth model. Machine learning algorithms, namely regularized logistic regression (r-LR), support vector machine (SVM), random forest (RF), and super learner (SL) were used to predict cognitive trajectories. Discrimination and calibration metrics were used for performance evaluation.

RESULTS

Two distinct trajectories were identified according to the changes of MMSE scores: intact cognitive functioning (93.6%), and dementia (6.4%). Older age, female gender, Han ethnicity, having no schooling, rural residents, low-frequency leisure activities, and low baseline BADL score were associated with a rapid decline in cognitive function. r-LR, SVM, and SL performed well in predicting cognitive trajectories (Sensitivity: 0.73, G-mean: 0.65). Age and psychological well-being were key predictors.

CONCLUSION

Two cognitive trajectories were identified among older Chinese, and the identified key factors could be targeted for constructing early risk prediction models.

Trajectories of General Health Status and Depressive Symptoms Among Persons With Cognitive Impairment in the United States

ObjectivesTo identify and examine heterogeneous trajectories of general health status (GHS) and depressive symptoms (DS) among persons with cognitive impairment (PCIs). Methods: We use group-based trajectory models to study 2361 PCIs for GHS and 1927 PCIs for DS from the National Health and Aging Trends Survey 2011-2018, and apply multinomial logistic regressions to predict identified latent trajectory group memberships using individual characteristics. Results: For both GHS and DS, there were six groups of PCIs with distinct trajectories over a 7-year period. More than 40% PCIs experienced sharp declines in GHS, and 35.5% experienced persistently poor GHS. There was greater heterogeneity in DS trajectories with 55% PCIs experiencing improvement, 16.4% experiencing persistently high DS, and 30.5% experiencing deterioration. Discussion: The GHS trajectories illustrate the heavy burden of poor and declining health among PCIs. Further research is needed to understand the factors underlying stable or improving DS despite declining GHS.

Vision impairment and cognitive decline among older adults: a systematic review

OBJECTIVES

There has been increasing epidemiological research examining the association between vision impairment (VI) and cognitive impairment and how poor vision may be a modifiable risk factor for cognitive decline. The objective of this systematic review is to synthesise the published literature on the association of VI with cognitive decline, cognitive impairment or dementia, to aid the development of interventions and guide public policies pertaining to the relationship between vision and cognition.

METHODS

A literature search was performed with Embase, Medline and Cochrane library databases from inception to March 2020, and included abstracts and articles published in peer-reviewed journals in English. Our inclusion criteria included publications that contained subjective/objective measures of vision and cognition, or a diagnosis of VI, cognitive impairment or dementia. Longitudinal or cross-sectional studies with ≥100 participants aged >50 years were included. The search identified 11 805 articles whose abstracts underwent screening by three teams of study authors. Data abstraction and quality assessment using the Effective Public Health Practice Project Quality Assessment Tool were performed by one author (NN). 10% of the articles underwent abstraction and appraisal by a second author (LA/VV), results were compared between both and were in agreement.

RESULTS

110 full-text articles were selected for data extraction, of which 53 were cross-sectional, 43 longitudinal and 14 were case-control studies. The mean age of participants was 73.0 years (range 50-93.1). Ninety-one (83%) of these studies reported that VI was associated with cognitive impairment.

CONCLUSION

Our systematic review indicates that a majority of studies examining the vision-cognition relationship report that VI is associated with more cognitive decline, cognitive impairment or dementia among older adults. This synthesis supports the need for additional research to understand the mechanisms underlying the association between VI and cognitive impairment and to test interventions that mitigate the cognitive consequences of VI.