scholarly journals Physical Frailty and Cognitive Impairment in Older Nursing Home Residents: A Latent Class Analysis

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 823-824
Author(s):  
Yiyang Yuan ◽  
Kate Lapane ◽  
Jennifer Tjia ◽  
Jonggyu Baek ◽  
Shao-Hsien Liu ◽  
...  
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Nursing Home Residents ◽  
Class Analysis ◽  
Physical Frailty ◽  
Data Set ◽  
Clinical Presentations ◽  
New Evidence

Abstract Physical frailty (PF) has various clinical presentations and often co-occurs with cognitive impairment in older adults. In older adults in nursing homes (NHs), no research has examined the heterogeneous profile of PF and its association with cognitive impairment. Minimum Data Set 3.0 was used to identify older, long-stay, newly-admitted NH residents (2014-16; n=871,801). Latent class analysis was used to identify PF subgroups with FRAIL-NH items as indicators. Logistic regression was used to estimate the association between PF subgroups and cognitive impairment. The final model indicated three PF subgroups (prevalence): “mild PF” (7.6%), “moderate PF” (44.5%), and “severe PF” (47.9%). In all subgroups, residents had high probability of needing help with dressing. Older adults likely to belong to the “moderate PF” or the “severe PF” subgroups had high probabilities of requiring physical assistance to transfer between locations and inability to walk in a room. Additionally, residents likely to be in the “severe PF” subgroup had greater probability of bowel incontinence. Greater cognitive impairment was associated with increasingly higher odds to be in the “moderate PF” and “severe PF” subgroups: older residents with severe cognitive impairment were 20% more likely [adjusted odds ratio (aOR): 1.20, 95% confidence interval (CI): 1.17-1.23] and almost 7 times as likely (aOR: 6.86, 95%CI: 6.66-7.06) to belong to the “moderate PF” and “severe PF” subgroups, respectively. Findings provide new evidence for the interrelationship between PF and cognitive impairment in older NH residents and have implications for the development of interventions tailored to older residents’ specific PF experience.

scholarly journals Physical frailty and cognitive impairment in older nursing home residents: a latent class analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yiyang Yuan ◽  
Kate L. Lapane ◽  
Jennifer Tjia ◽  
Jonggyu Baek ◽  
Shao-Hsien Liu ◽  
...  
Keyword(s):  
Nursing Home ◽  
Cognitive Impairment ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Nursing Home Residents ◽  
Class Analysis ◽  
Physical Frailty ◽  
Data Set ◽  
Severe Cognitive Impairment ◽  
Moderate Cognitive Impairment

Abstract Background Little is known about the heterogeneous clinical profile of physical frailty and its association with cognitive impairment in older U.S. nursing home (NH) residents. Methods Minimum Data Set 3.0 at admission was used to identify older adults newly-admitted to nursing homes with life expectancy ≥6 months and length of stay ≥100 days (n = 871,801). Latent class analysis was used to identify physical frailty subgroups, using FRAIL-NH items as indicators. The association between the identified physical frailty subgroups and cognitive impairment (measured by Brief Interview for Mental Status/Cognitive Performance Scale: none/mild; moderate; severe), adjusting for demographic and clinical characteristics, was estimated by multinomial logistic regression and presented in adjusted odds ratios (aOR) and 95% confidence intervals (CIs). Results In older nursing home residents at admission, three physical frailty subgroups were identified: “mild physical frailty” (prevalence: 7.6%), “moderate physical frailty” (44.5%) and “severe physical frailty” (47.9%). Those in “moderate physical frailty” or “severe physical frailty” had high probabilities of needing assistance in transferring between locations and inability to walk in a room. Residents in “severe physical frailty” also had greater probability of bowel incontinence. Compared to those with none/mild cognitive impairment, older residents with moderate or severe impairment had slightly higher odds of belonging to “moderate physical frailty” [aOR (95%CI)moderate cognitive impairment: 1.01 (0.99–1.03); aOR (95%CI)severe cognitive impairment: 1.03 (1.01–1.05)] and much higher odds to the “severe physical frailty” subgroup [aOR (95%CI)moderate cognitive impairment: 2.41 (2.35–2.47); aOR (95%CI)severe cognitive impairment: 5.74 (5.58–5.90)]. Conclusions Findings indicate the heterogeneous presentations of physical frailty in older nursing home residents and additional evidence on the interrelationship between physical frailty and cognitive impairment.

scholarly journals Depression symptoms and cognitive impairment in older nursing home residents in the USA : A latent class analysis

2020 ◽  
Vol 35 (7) ◽  
pp. 769-778 ◽  
Author(s):  
Yiyang Yuan ◽  
Hye Sung Min ◽  
Kate L. Lapane ◽  
Anthony J. Rothschild ◽  
Christine M. Ulbricht
Keyword(s):  
Nursing Home ◽  
Cognitive Impairment ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Nursing Home Residents ◽  
Depression Symptoms ◽  
Class Analysis ◽  
The Usa

The Patterns of Caregiving Activities for Family Caregivers of Older Adults in Hong Kong: An Exploratory Latent Class Analysis

2020 ◽  
Author(s):  
Jing Huang ◽  
Pui Hing Chau ◽  
Edmond Pui Hang Choi ◽  
Bei Wu ◽  
Vivian W Q Lou
Keyword(s):  
Older Adults ◽  
Hong Kong ◽  
Activities Of Daily Living ◽  
Latent Class Analysis ◽  
Family Caregivers ◽  
Caregiver Burden ◽  
Daily Living ◽  
Latent Class ◽  
Class Analysis ◽  
High Demand

Abstract Objectives This study identified the classes (i.e., patterns) of caregivers’ activities, based on their engagements in caregiving activities, and explored the characteristics and the caregiver burden of these classes. Methods This study was a secondary analysis of a cross-sectional survey on the profiles of family caregivers of older adults in Hong Kong. A latent class analysis approach was adopted to classify family caregivers (N = 932) according to their routine involvements in 17 daily caregiving activities: 6 activities of daily living (ADLs) and 8 instrumental activities of daily living activities (IADLs) in addition to emotional support, decision making, and financial support. Multinomial logistic regression and multiple linear regression illuminated the characteristics of the classes and compared their levels of caregiver burden. Results The family caregivers fell into 5 classes: All-Round Care (High Demand, 19.5%), All-Round Care (Moderate Demand, 8.2%), Predominant IADLs Care (High Demand, 23.8%), Predominant IADLs Care (Moderate Demand, 32.5%), and Minimal ADLs and IADLs Care (Low Demand, 16.0%). These classes exhibited different characteristics in terms of care recipients’ cognitive statuses and caregiver backgrounds. The levels of caregiver burden differed across classes; the All-Round Care (High Demand) class experienced the highest levels of caregiver burden. Discussion This study contributes to existing scholarship by turning away from a predefined category of care tasks to explore the patterns of caregiving activities. By identifying caregiving activity patterns and understanding their associated characteristics and caregiver burden, prioritizing and targeting caregiver support interventions better is possible.

scholarly journals Using the Past to Predict the Future: Latent Class Analysis of Patterns of Health Service Use of Older Adults in the Emergency Department

2014 ◽  
Vol 62 (4) ◽  
pp. 711-715 ◽  
Author(s):  
S. Nicole Hastings ◽  
Heather E. Whitson ◽  
Richard Sloane ◽  
Lawrence R. Landerman ◽  
Carolyn Horney ◽  
...  
Keyword(s):  
Older Adults ◽  
Emergency Department ◽  
Health Service ◽  
Latent Class Analysis ◽  
Service Use ◽  
Latent Class ◽  
Health Service Use ◽  
Class Analysis ◽  
The Past ◽  
The Future

scholarly journals Oral health status in older adults with social security in Mexico City: latent class analysis

2014 ◽  
pp. e29-35 ◽  
Author(s):  
S. Sanchez-Garcia ◽  
E. Heredia-Ponce ◽  
P. Cruz-Hervert ◽  
T. Juarez-Cedillo ◽  
Á. Cardenas-Bahena ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Status ◽  
Oral Health ◽  
Social Security ◽  
Latent Class Analysis ◽  
Mexico City ◽  
Latent Class ◽  
Oral Health Status ◽  
Class Analysis

scholarly journals Applying latent class analysis in the identification of occupational accident patterns

2020 ◽  
Vol 2020 (146) ◽  
pp. 339-355
Author(s):  
Marzena NOWAKOWSKA ◽  
◽  
Michał PAJĘCKI ◽  
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Latent Class Model ◽  
Severe Accident ◽  
Occupational Accidents ◽  
Occupational Accident ◽  
Class Analysis ◽  
Data Set ◽  
Pilot Studies ◽  
Individual Record

Purpose: The objective of the study is to use selected data mining techniques to discover patterns of certain recurring mechanisms related to the occurrence of occupational accidents in relation to production processes. Design/methodology/approach: The latent class analysis (LCA) method was employed in the investigation. This statistical modeling technique enables discovering mutually exclusive homogenous classes of objects in a multivariate data set on the basis of observable qualitative variables, defining the class homogeneity in terms of probabilities. Due to a bilateral agreement, Statistics Poland provided individual record-level real data for the research. Then the data were preprocessed to enable the LCA model identification. Pilot studies were conducted in relation to occupational accidents registered in production plants in 2008-2017 in the Wielkopolskie voivodeship. Findings: Three severe accident patterns and two light accident patterns represented by latent classes were obtained. The classes were subjected to descriptive characteristics and labeling, using interpretable results presented in the form of probabilities classifying categories of observable variables, symptomatic for a given latent class. Research limitations/implications: The results from the pilot studies indicate the necessity to continue the research based on a larger data set along with the analysis development, particularly as regards selecting indicators for the latent class model characterization. Practical implications: The identification of occupational accident patterns related to the production process can play a vital role in the elaboration of efficient safety countermeasures that can help to improve the prevention and outcome mitigation of such accidents among workers. Social implications: Creating a safe work environment comprises the quality of life of workers, their families, thus affirming the enterprises' principles and values in the area of corporate social responsibility. Originality/value: The investigation showed that latent class analysis is a promising tool supporting the scientific research in discovering the patterns of occupational accidents. The proposed investigation approach indicates the importance for the research both in terms of the availability of non-aggregated occupational accident data as well as the type of value aggregation of the variables taken for the analysis.

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