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Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis
BACKGROUND: Persons living with dementia (PLWD) in adult day centers (ADCs) represent a complex and vulnerable population whose well-being is at risk based on numerous factors. Greater knowledge of the interaction between dementia, chronic conditions, and social determinants of health would enable A...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216285/ https://www.ncbi.nlm.nih.gov/pubmed/35733122 http://dx.doi.org/10.1186/s12877-022-03206-0 |
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author | Sadarangani, Tina Perissinotto, Carla Boafo, Jonelle Zhong, Jie Yu, Gary |
author_facet | Sadarangani, Tina Perissinotto, Carla Boafo, Jonelle Zhong, Jie Yu, Gary |
author_sort | Sadarangani, Tina |
collection | PubMed |
description | BACKGROUND: Persons living with dementia (PLWD) in adult day centers (ADCs) represent a complex and vulnerable population whose well-being is at risk based on numerous factors. Greater knowledge of the interaction between dementia, chronic conditions, and social determinants of health would enable ADCs to identify and target the use of their resources to better support clients in need of in-depth intervention. The purpose of this paper is to (a) classify PLWD in ADCs according to their level of medical complexity and (b) identify the demographic, functional, and clinical characteristics of those with the highest degree of medical complexity. METHODS: This was a secondary data analysis of 3052 clients with a dementia diagnosis from 53 ADCs across the state of California between 2012 and 2019. The most common diagnosis codes were organized into 28 disease categories to enable a latent class analysis (LCA). Chi-square test, analysis of variance (ANOVA), and Kruskal-Wallis tests were conducted to examine differences among latent classes with respect to clinical and functional characteristics. RESULTS: An optimal 4-class solution was chosen to reflect chronic conditions among PLWD: high medical complexity, moderate medical complexity, low medical complexity, and no medical complexity. Those in the high medical complexity were taking an average of 12.72 (+/− 6.52) medications and attending the ADC an average of 3.98 days (+/− 1.31) per week—values that exceeded any other class. They also experienced hospitalizations more than any other group (19.0%) and met requirements for the nursing facility level of care (77.4%). In addition, the group experienced the greatest frequency of bladder (57.5%) and bowel (15.7%) incontinence. CONCLUSIONS: Our results illustrate a high degree of medical complexity among PLWD in ADCs. A majority of PLWD not only have multimorbidity but are socially disadvantaged. Our results demonstrate that a comprehensive multidisciplinary approach that involves community partners such as ADCs is critically needed that addresses functional decline, loneliness, social isolation, and multimorbidity which can negatively impact PLWD. |
format | Online Article Text |
id | pubmed-9216285 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92162852022-06-22 Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis Sadarangani, Tina Perissinotto, Carla Boafo, Jonelle Zhong, Jie Yu, Gary BMC Geriatr Research BACKGROUND: Persons living with dementia (PLWD) in adult day centers (ADCs) represent a complex and vulnerable population whose well-being is at risk based on numerous factors. Greater knowledge of the interaction between dementia, chronic conditions, and social determinants of health would enable ADCs to identify and target the use of their resources to better support clients in need of in-depth intervention. The purpose of this paper is to (a) classify PLWD in ADCs according to their level of medical complexity and (b) identify the demographic, functional, and clinical characteristics of those with the highest degree of medical complexity. METHODS: This was a secondary data analysis of 3052 clients with a dementia diagnosis from 53 ADCs across the state of California between 2012 and 2019. The most common diagnosis codes were organized into 28 disease categories to enable a latent class analysis (LCA). Chi-square test, analysis of variance (ANOVA), and Kruskal-Wallis tests were conducted to examine differences among latent classes with respect to clinical and functional characteristics. RESULTS: An optimal 4-class solution was chosen to reflect chronic conditions among PLWD: high medical complexity, moderate medical complexity, low medical complexity, and no medical complexity. Those in the high medical complexity were taking an average of 12.72 (+/− 6.52) medications and attending the ADC an average of 3.98 days (+/− 1.31) per week—values that exceeded any other class. They also experienced hospitalizations more than any other group (19.0%) and met requirements for the nursing facility level of care (77.4%). In addition, the group experienced the greatest frequency of bladder (57.5%) and bowel (15.7%) incontinence. CONCLUSIONS: Our results illustrate a high degree of medical complexity among PLWD in ADCs. A majority of PLWD not only have multimorbidity but are socially disadvantaged. Our results demonstrate that a comprehensive multidisciplinary approach that involves community partners such as ADCs is critically needed that addresses functional decline, loneliness, social isolation, and multimorbidity which can negatively impact PLWD. BioMed Central 2022-06-22 /pmc/articles/PMC9216285/ /pubmed/35733122 http://dx.doi.org/10.1186/s12877-022-03206-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sadarangani, Tina Perissinotto, Carla Boafo, Jonelle Zhong, Jie Yu, Gary Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
title | Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
title_full | Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
title_fullStr | Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
title_full_unstemmed | Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
title_short | Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
title_sort | multimorbidity patterns in adult day health center clients with dementia: a latent class analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216285/ https://www.ncbi.nlm.nih.gov/pubmed/35733122 http://dx.doi.org/10.1186/s12877-022-03206-0 |
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