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Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

ABSTRACT: OBJECTIVES:The aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity. METHODS:We applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults living in the Bronx, NY. We used 10 neurocognitive tests and 3 covariates (age, sex, education) to identify latent subgroups. We used goodness-of-fit statistics to identify the optimal class solution and assess model adequacy. We also validated our model using two-fold split-half cross-validation. RESULTS:The sample had a mean age of 78.0 (SD=5.4) and a mean of 13.6 years of education (SD=3.5). A 9-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the 9 identified classes as (i) disadvantaged, (ii) poor language, (iii) poor episodic memory and fluency, (iv) poor processing speed and executive function, (v) low average, (vi) high average, (vii) average, (viii) poor executive and poor working memory, (ix) elite. The cross validation indicated stable class assignment with the exception of the average and high average classes. CONCLUSIONS:LC modeling in a community sample of older adults revealed 9 cognitive subgroups. Assignment of subgroups was reliable and associated with external validators. Future work will test the predictive validity of these groups for outcomes such as Alzheimer's disease, vascular dementia and death, as well as markers of biological pathways that contribute to cognitive decline. (JINS, 2018, 24, 511-523).

SUBMITTER: Zammit AR

PROVIDER: S-EPMC6484858 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

Zammit Andrea R AR Hall Charles B CB Lipton Richard B RB Katz Mindy J MJ Muniz-Terrera Graciela G

Journal of the International Neuropsychological Society : JINS 20180110 5

<h4>Objectives</h4>The aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity.<h4>Methods</h4>We applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults livi ...[more]

PMID: 29317003

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Project description:BackgroundSocial relationships may be the key to successful aging among older adults. However, little is known about the variability of social relationships among community-dwelling older people. This study aimed to describe the patterns of social relationships and examine the differences in sociodemographic characteristics and mental and physical health status among these patterns.MethodsWe obtained the data from a questionnaire survey in 2017 for older adults aged 65 and above who lived in a suburban area in Japan. The Index of Social Interaction (ISI) was used to evaluate social relationships. The final sample comprised 964 people who were independently mobile and answered at least one item of the ISI. To clarify the patterns of social relationships, latent class analysis was performed with five subscales of ISI treated as indicator variables. Multinomial logistic regression was conducted to examine the factors associated with the patterns of social relationships.ResultsThe patterns of social relationships were classified into three classes: "Active" (73.6%), "Socially isolated" (14.7%), and "Less motivated" (11.7%). Persons who had depressive symptoms were more likely to be allocated to the "Socially isolated" (Odds Ratio [OR] 1.80, 95% Confidence Interval [CI] 1.13-2.86) or the "Less motivated" groups (OR 1.69, 95% CI 1.00-2.85) compared to the "Active" group. In addition, men (OR 1.72, 95% CI 1.07-2.76) and those living alone (OR 3.07, 95% CI 1.43-6.61) were more likely to be allocated to the "Socially isolated" group. Moreover, those who were dependent, according to the instrumental activities and daily living functions, were more likely to be assigned to the "Socially isolated" (OR 2.19, 95% CI 1.21-3.97) or "Less motivated" (OR 6.29, 95% CI 3.47-11.39) groups.ConclusionThis study revealed the patterns of social relationships in older adults and suggested that there may be variations of social relationships among community dwellers. The results also indicated the necessity of assessing individual patterns of social relationships and devising strategies for each pattern in public health practice.

Project description:BackgroundExisting studies have used ADL and IADL separately as measures of dependency. However, dependency is a heterogeneous and complex issue, and the dependency of each older adult is a synergistic combination of several functional activities. In this study, we assess the pattern of multidimensional dependency of older adults based on ADL, IADL, visual impairment, difficulty in climbing a flight of stairs, pushing or pulling objects, depressive symptoms, cognitive impairment, marital status, and economic distress. It is important to classify the dependency status of older adults because this will be key to evaluating the needs for care, and plan services that effectively cater for the needs of the older adults. The classification into different latent classes means that older adults within each class have the same needs of dependency but different needs between the latent classes. Our objective is to identify patterns of multidimensional dependency in older adults.MethodsData from the Longitudinal Ageing Study in India (LASI) Wave-1, was used, the analytical sample consisted of 32,827 individuals of age 45 years and above. LCA was used to identify the multidimensional dependency class. LCA was conducted in R statistical package, using the poLCA package. The optimal number of classes was selected based on the comparison of model fit statistics. Independent variables were incorporated to explore the association between these variables and the latent class.ResultsBased on nine indicator variables, three latent classes were identified: "Active Older adults", "Moderately independent" and "Psychological and physically impaired". The "Active older adults" profile is comprised of older adults who have a very low probability of needing help for any ADL, IADL and other activities. The "Moderately independent" class were characterized as those older adults who were visually impaired but less likely to need help for IADL activities. The "Psychological and physically impaired", the smallest of all classes, comprised of older adults with poor dependency status.ConclusionsIn this study, we found that the dependency status of older adults which is based on several domains of functional activity has been classified into three distinct classes. These three classes have distinct physical, psychological, economic, and socio-demographic characteristics in terms of activities in which help is required.

Project description:BACKGROUND:Physical frailty, characterized by reduced physiologic complexity and ability to cope with stressors, is closely associated with cognitive impairment, which increases the risk of poor clinical outcomes. To better capture the association between frailty and cognitive impairment, a new construct, cognitive frailty, has been proposed. Cognitive frailty is a clinical condition characterized by the simultaneous presence of physical frailty and cognitive impairment. There is little evidence on the relationship between physical frailty and cognition, as well as cognitive frailty, in Chinese older adults. We aimed to elucidate whether physical frailty is associated with cognitive impairment in an older Chinese population. METHODS:Data were obtained from the China Comprehensive Geriatric Assessment Study. The sample comprised 3202 community-dwelling adults, aged 60 years and older, from seven Chinese cities. Physical frailty was assessed using a modified, four-item version of the Fried criteria, according to frailty phenotype. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). RESULTS:The prevalence of physical frailty, prefrailty, cognitive impairment, and cognitive frailty was 9.9, 33.9, 7.5, and 2.3%, respectively (weighted: 8.8, 33.8, 6.5, and 2.0%). The prevalence of the combination of prefrail/frail and cognitive impairment was 5.1% (weighted 4.5%). Frail participants performed worse on global cognition and all cognitive domains than robust and prefrail participants. The MMSE total score was positively correlated with walking speed and negatively correlated with age and frailty. A multivariate logistic regression revealed that after adjusting for age, gender, education level, living area, and chronic diseases, frailty, exhaustion, slowness, and inactivity were significantly associated with poor global cognition. CONCLUSIONS:The standard prevalence of physical frailty, prefrailty, cognitive impairment, and cognitive frailty in community-dwelling older adults in China was 8.8, 33.8, 6.5, and 2.0%, respectively. Frailty, exhaustion, slowness, and inactivity were significantly associated with poor global cognition.

Project description:BackgroundFew studies have explored patterns of physical activity (PA) and examined their relationship with depression among community-dwelling older adults. We aimed to identify the patterns of PA through a person-centered analytical approach and examine the association between quantity and patterns of PA, and depression among community-dwelling older adults.MethodsWe conducted a cross-sectional survey study in the Minhang district, Shanghai, China, in August 2019, and used a self-administered questionnaire to collect data through home visits. The total sample included 2525 older adults. This study used the Physical Activity Scale for the Elderly (PASE) to assess the quantity of PA in older adults. Depression was evaluated with the Geriatric Depression Scale (GDS). Latent class analysis (LCA) was used to identify subpopulations by shared item response patterns. Logistic regressions were performed to estimate the relationship between PASE score, patterns of PA, and depression. An exploratory analysis of joint levels and patterns of PA effects on depression was based on sample subgroups with combinations of levels and patterns of PA. Logistic regression was used to calculate the odds ratio for combined subgroups.ResultsFour latent classes were identified: "domestic types," "athletic types," "gardening/caring types," and "walkers." PASE scores and patterns of PA both were associated with depression. Older adults who were the most active (PASE quartile: 75-100%) and the athletic types had the strongest significant association with depression (OR = 0.19, 95% CI: 0.06-0.65), followed by those who were the most active (PASE quartile: 75-100%) and the walkers (OR = 0.28, 95% CI: 0.14-0.57) when compared with older adults with the least activity (PASE quartile: 0-25%) and domestic types.ConclusionThis study suggests both the quantity and patterns of physical activity are associated with depressive symptoms among community-dwelling older adults. Population-level intervention should encourage community-dwelling older adults to increase their quantity of PA to reduce the risk of depression. Athletics and walkers are recommended. To develop individual-level tailored interventions, more attention should be paid to older adults who are highly engaged in gardening/caring for others.

Dataset Information

Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

Publications

Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

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