Neuropsychiatric and Cognitive Subtypes among Community-Dwelling Older Persons and the Association with DSM-5 Mild Neurocognitive Disorder: Latent Class Analysis

2018 ◽  
Vol 62 (2) ◽  
pp. 675-686 ◽  
Author(s):  
Tau Ming Liew ◽  
Junhong Yu ◽  
Rathi Mahendran ◽  
Tze-Pin Ng ◽  
Ee-Heok Kua ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Older Persons ◽  
Latent Class ◽  
Community Dwelling ◽  
Neurocognitive Disorder ◽  
Class Analysis ◽  
Dsm 5 ◽  
Mild Neurocognitive Disorder

scholarly journals Profiles of Family and Friend Caregivers of Community-Dwelling People With Dementia: A Latent Class Analysis

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 59-59
Author(s):  
Eric Jutkowitz ◽  
Lauren Mitchell ◽  
Joseph Gaugler
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Disease Onset ◽  
Community Dwelling ◽  
Health And Retirement Study ◽  
Class Analysis ◽  
People With Dementia ◽  
The Hours ◽  
Retirement Study ◽  
Post Onset

Abstract People living with Alzheimer’s disease and related dementias (ADRD) receive most of their care from family/friends, but little is known about the organization of this care. We used data from the Health and Retirement Study and latent class analysis to determine variation in the hours of care received by community-dwelling people with ADRD from disease onset up to 6-years post onset. At incidence (n=1,158), the latent class analysis identified two groups of caregiving patterns. In the first group, 10% (n=109) of people with ADRD received 481 hours (SD=177) of care. Most care was provided by a spouse (411 hours) with less from children (28 hours), other family/friends (17 hours), and paid individuals (25 hours). In the second latent class, the remaining 90% (n=1,049) of people with ADRD received 114 hours (SD=202) of care which was distributed between spouses (12 hours), children (51 hours), other relatives/friends (22 hours), and paid individuals (29 hours). By 6-years post incidence, 7% (n=76) of the original ADRD cohort remained in the community, and we identified two latent classes independent of those identified at incidence. Almost 15% (n=11) of people with ADRD received a majority of care from a spouse (376 hours) with care supplemented by children (10 hours) and paid individuals (54 hours). The remaining 85% (n=65) of people with ADRD received 294 (SD=314) hours of care from spouses (13 hours), children (104 hours), other family/friends (83 hours), and paid individuals (67 hours). Policies/interventions supporting caregivers must account for the heterogeneity in the organization caregivers.

Latent class analysis of the Apathy Scale does not identify subtypes of apathy in general population-based older persons

2016 ◽  
Vol 31 (9) ◽  
pp. 1021-1028 ◽  
Author(s):  
Isis Groeneweg-Koolhoven ◽  
Lotte J. Huitema ◽  
Margot W. M. de Waal ◽  
Max L. Stek ◽  
Jacobijn Gussekloo ◽  
...  
Keyword(s):  
General Population ◽  
Latent Class Analysis ◽  
Older Persons ◽  
Latent Class ◽  
Population Based ◽  
Class Analysis

scholarly journals Multidimensional dependency subgroups in community-dwelling older adults: A latent class analysis

2020 ◽  
Vol 52 (2) ◽  
pp. 101-109
Author(s):  
Kely Rely ◽  
Delfino Vargas-Chanes ◽  
Carmen García-Peña ◽  
Guillermo Salinas-Escudero ◽  
Luis-Miguel Gutiérrez-Robledo ◽  
...  
Keyword(s):  
Older Adults ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Community Dwelling ◽  
Future Research ◽  
Class Analysis ◽  
Class Membership ◽  
Fit Statistics ◽  
Nationally Representative ◽  
Using Data

Objectives: Use latent class analysis (LCA) to identify patterns of multidimensional dependency in a sample of older adults and assess sociodemographic, predictors of class membership. Material and methods: Longitudinal data were usedfrom the Mexican Health and Aging Study (MHAS). 7,920 older adults, 55% women, were recruited. LCA were used to identify meaningful subgroups. LCA was conducted using MPlus version. The final class model was chosen based on the comparison of multiple fit statistics and theoretical parsimony, with models of increasing complexity analyzed sequentially until the best fitting model was identified. Covariates were incorporated to explore the association between these variables and class membership. Results: Three classes groups based on the nine indicators were identified: “Active older adults” was comprised of 64% of the sample participants, “Relatively independent” and “Physically impaired” were comprised of 26% and 10% of the sample. The “Active older adults” profile comprised the majority of respondents who exhibited high endorsement rates across all criteria. The profiles of the “Active older adults” and “Relatively independent” were comparatively more uniform. Finally, respondents belonging to the “Physically impaired” profile, the smallest subgroup, encompassed the individuals most susceptible to a poor dependency profile. Conclusions: These findings highlighted the usefulness to adopt a person-centered approach rather than a variable-centered approach, suggesting directions for future research and tailored interventions approaches to older adults with particular characteristics. Based on patterns of multidimensional dependency, this study identified a typology of dependency using data from a large, nationally representative survey.

Patterns of geriatric health assessment use among community dwelling older Australian women over a 14-year period

2019 ◽  
Vol 24 (2) ◽  
pp. 100-107
Author(s):  
Tazeen Majeed ◽  
Meredith Tavener ◽  
Xenia Dolja-Gore ◽  
Balakrishnan Nair ◽  
Catherine Chojenta ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Older Women ◽  
Latent Class ◽  
Health Assessment ◽  
Community Dwelling ◽  
Class Analysis ◽  
Health Services Use ◽  
Financial Barriers ◽  
Prospective Longitudinal ◽  
The Impact

Objective To assess which older Australian women had Medicare subsidized health assessments between 1999 and 2013. Methods This study used prospective, longitudinal survey data from the 1921 to 1926 birth cohort of Australian Longitudinal Study on Women’s Health (ALSWH) linked with Medicare Australia data on health services use. Over 11,000 Australian women were included in the study. Latent class analysis was used to identify assessment patterns over time, accounting for death, and based on three categories (‘no assessment’; ‘assessment; ‘deceased’) for each year between 1999 and 2013. Further analysis explored the impact of health and sociodemographic characteristics on class membership. Results Of the women included in the latent class analysis, 37% never had any assessment and the remainder had had at least one assessment. After a steady uptake from 1999 to 2003, there was decline in uptake from 2003 onwards. A six-class model with sufficient homogeneity and reliable estimation was selected to represent assessment patterns and mortality risk, labelled as: ‘high mortality’ rate with little chance for assessment (12.4%), ‘intermediate mortality, low assessment’ (14.1%), ‘later mortality/low assessment’ (13.1%), ‘later mortality, high assessment’ (7.0%), ‘low mortality, low assessment’ (31.8%), ‘low mortality, high assessment’ (21.6%). Older women with certain conditions (such as diabetes, depression, heart disease) were more likely to be in the low assessment groups, and women with difficulty managing on income were more likely to be in low assessment groups. Conclusion Distinct assessment and mortality patterns were seen, with many women not having assessment, in particular those who had certain health conditions, were taking 3+ medications, had difficulty in managing on income, needed help or were in respite care, and had caring responsibilities. The findings point to a need to promote these assessments among older women, and to reduce financial barriers, even within the context of a heavily subsidized health care system.

scholarly journals 86Segmenting persistently high-cost individuals into actionable groups

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Paul Ronksley ◽  
James Wick ◽  
Dave Campbell ◽  
Reed Beall ◽  
Brenda Hemmelgarn ◽  
...  
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Population Level ◽  
Latent Class Models ◽  
Community Dwelling ◽  
Local Context ◽  
Medication Cost ◽  
Class Analysis ◽  
Targeted Interventions ◽  
Clinical Diagnoses

Abstract Background Despite growing evidence describing high cost patients, decision-makers struggle to implement effective strategies to improve care and curb spending in this population. Using a multi-phased approach, we aimed to classify high cost patients into homogeneous subgroups amenable to targeted interventions. Methods We linked population-level administrative health data in Alberta, Canada from 2012-2017. We defined “persistently high-cost” as those in the top 1% of cumulative inpatient, outpatient and medication cost in at least two consecutive years. We used latent class analysis to separate this persistent high-cost population into potentially actionable subgroups. Results Of the 3,795,067 adults residing in Alberta, 21,361 were ‘persistently high-cost’. Latent class models identified 10 high-cost subgroups: individuals with CKD (19.3% of persistent high-cost individuals), those undergoing joint surgery/replacement and rehabilitation (18.6%), individuals with IBD (11.6%), patients receiving biologics for autoimmune conditions (11.3%), patients receiving high cost drugs for other conditions (11.1%), community-dwelling individuals with multimorbid chronic conditions (9.0%), individuals with schizophrenia (6.8%), individuals with other mental health issues (6.2%), rural individuals with COPD (3.4%), and frail elderly in institutional settings (2.7%). Conclusions Latent class analysis was able to identify 10 persistently high-cost groups based on meaningful differences in health care spending, demographics, and clinical diagnoses. Key messages This taxonomy will inform the identification of interventions shown to improve care and reduce cost for each subgroup in addition to consultation with key stakeholders to identify and reflect on key barriers and facilitators to implementing identified interventions within the local context.

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