Cargando…
Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan
The manifestation of older adults with poor sleep quality is heterogeneous. Using data-driven classifying methods, the study aims to subgroup community-dwelling older adults with poor sleep quality. Adults aged 65 and older participated in the Yilan study. Poor sleep quality was defined using the Pi...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096492/ https://www.ncbi.nlm.nih.gov/pubmed/32214167 http://dx.doi.org/10.1038/s41598-020-62374-4 |
_version_ | 1783510816315670528 |
---|---|
author | Chen, Hsi-Chung Hsu, Nai-Wei Chou, Pesus |
author_facet | Chen, Hsi-Chung Hsu, Nai-Wei Chou, Pesus |
author_sort | Chen, Hsi-Chung |
collection | PubMed |
description | The manifestation of older adults with poor sleep quality is heterogeneous. Using data-driven classifying methods, the study aims to subgroup community-dwelling older adults with poor sleep quality. Adults aged 65 and older participated in the Yilan study. Poor sleep quality was defined using the Pittsburgh Sleep Quality Index. Latent class analysis with the 7 subscores of the Pittsburgh Sleep Quality Index as the indicators was used to generate empirical subgroups. Differences in comorbidity patterns between subgroups were compared. A total of 2622 individuals, of which 1011 (38.6%) had Pittsburgh Sleep Quality Index -defined poor sleep quality, participated. Three groups for poor sleep quality were specified in the latent class analysis: High Insomnia (n = 191, 7.3%), Mild Insomnia (n = 574, 21.9%), and High Hypnotics (n = 246, 9.4%). The High Insomnia and Mild Insomnia groups shared similar profiles but different severities in the 7 domains of the Pittsburgh Sleep Quality Index. In contrast, the High Hypnotics group had the lowest Pittsburgh Sleep Quality Index total scores and insomnia severity but had similar mental and physical comorbid patterns as the High Insomnia group. This finding suggests that poor sleep quality in community-dwelling older adults had various feature-based subgroups. It also implicates the development of group-centered interventions. |
format | Online Article Text |
id | pubmed-7096492 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70964922020-03-30 Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan Chen, Hsi-Chung Hsu, Nai-Wei Chou, Pesus Sci Rep Article The manifestation of older adults with poor sleep quality is heterogeneous. Using data-driven classifying methods, the study aims to subgroup community-dwelling older adults with poor sleep quality. Adults aged 65 and older participated in the Yilan study. Poor sleep quality was defined using the Pittsburgh Sleep Quality Index. Latent class analysis with the 7 subscores of the Pittsburgh Sleep Quality Index as the indicators was used to generate empirical subgroups. Differences in comorbidity patterns between subgroups were compared. A total of 2622 individuals, of which 1011 (38.6%) had Pittsburgh Sleep Quality Index -defined poor sleep quality, participated. Three groups for poor sleep quality were specified in the latent class analysis: High Insomnia (n = 191, 7.3%), Mild Insomnia (n = 574, 21.9%), and High Hypnotics (n = 246, 9.4%). The High Insomnia and Mild Insomnia groups shared similar profiles but different severities in the 7 domains of the Pittsburgh Sleep Quality Index. In contrast, the High Hypnotics group had the lowest Pittsburgh Sleep Quality Index total scores and insomnia severity but had similar mental and physical comorbid patterns as the High Insomnia group. This finding suggests that poor sleep quality in community-dwelling older adults had various feature-based subgroups. It also implicates the development of group-centered interventions. Nature Publishing Group UK 2020-03-25 /pmc/articles/PMC7096492/ /pubmed/32214167 http://dx.doi.org/10.1038/s41598-020-62374-4 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Hsi-Chung Hsu, Nai-Wei Chou, Pesus Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan |
title | Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan |
title_full | Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan |
title_fullStr | Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan |
title_full_unstemmed | Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan |
title_short | Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan |
title_sort | subgrouping poor sleep quality in community-dwelling older adults with latent class analysis - the yilan study, taiwan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096492/ https://www.ncbi.nlm.nih.gov/pubmed/32214167 http://dx.doi.org/10.1038/s41598-020-62374-4 |
work_keys_str_mv | AT chenhsichung subgroupingpoorsleepqualityincommunitydwellingolderadultswithlatentclassanalysistheyilanstudytaiwan AT hsunaiwei subgroupingpoorsleepqualityincommunitydwellingolderadultswithlatentclassanalysistheyilanstudytaiwan AT choupesus subgroupingpoorsleepqualityincommunitydwellingolderadultswithlatentclassanalysistheyilanstudytaiwan |