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Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis

BACKGROUND: Anxiety and sleep problems are common comorbidities among outpatients living in high-altitude areas. Network analysis is a novel method to investigate the interaction and the association between symptoms across diverse disorders. This study used network analysis to investigate the networ...

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Autores principales: Jin, Yu, Li, Jiaqi, Ye, Jing, Luo, Xianyu, Wilson, Amanda, Mu, Lanxue, Zhou, Pinyi, Lv, Yunhui, Wang, Yuanyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184966/
https://www.ncbi.nlm.nih.gov/pubmed/37189050
http://dx.doi.org/10.1186/s12888-023-04767-z
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author Jin, Yu
Li, Jiaqi
Ye, Jing
Luo, Xianyu
Wilson, Amanda
Mu, Lanxue
Zhou, Pinyi
Lv, Yunhui
Wang, Yuanyuan
author_facet Jin, Yu
Li, Jiaqi
Ye, Jing
Luo, Xianyu
Wilson, Amanda
Mu, Lanxue
Zhou, Pinyi
Lv, Yunhui
Wang, Yuanyuan
author_sort Jin, Yu
collection PubMed
description BACKGROUND: Anxiety and sleep problems are common comorbidities among outpatients living in high-altitude areas. Network analysis is a novel method to investigate the interaction and the association between symptoms across diverse disorders. This study used network analysis to investigate the network structure symptoms of anxiety and sleep problems among outpatients in high-altitude areas, and to explore the differences in symptom associations in various sex, age, educational levels and employment groups. METHODS: The data was collected from the Sleep Medicine Center of The First People’s Hospital of Yunnan Province from November 2017 to January 2021 with consecutive recruitment (N = 11,194). Anxiety and sleep problems were measured by the Chinese version of the seven-item Generalized Anxiety Disorder Scale (GAD-7) and the Pittsburgh Sleep Quality Index (PSQI) respectively. Central symptoms were identified based on centrality indices and bridge symptoms were identified with bridge indices. The difference of network structures in various sex, age, educational levels and employment groups were also explored. RESULTS: Among all the cases, 6,534 (58.37%; 95% CI: 57.45-59.29%) reported experiencing anxiety (GAD-7 total scores ≥ 5), and 7,718 (68.94%; 95% CI: 68.08-69.80%) reported experiencing sleep problems (PSQI total scores ≥ 10). Based on the results of network analysis, among participants, “Nervousness”, “Trouble relaxing”, “Uncontrollable worry” were the most critical central symptoms and bridge symptoms within the anxiety and sleep problems network structure. The adjusted network model after controlling for covariates was significantly correlated with the original (r = 0.75, P = 0.46). Additionally, there were significant differences in edge weights in the comparisons between sex, age and educational levels groups (P < 0.001), while the employed and unemployed groups did not show significant differences in edge weights (P > 0.05). CONCLUSIONS: In the anxiety and sleep problems network model, among outpatients living in high-altitude areas, nervousness, uncontrollable worry, and trouble relaxing were the most central symptoms and bridge symptoms. Moreover, there were significant differences between various sex, age and educational levels. These findings can be used to provide clinical suggestions for psychological interventions and measures targeting to reduce symptoms that exacerbate mental health. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-023-04767-z.
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spelling pubmed-101849662023-05-16 Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis Jin, Yu Li, Jiaqi Ye, Jing Luo, Xianyu Wilson, Amanda Mu, Lanxue Zhou, Pinyi Lv, Yunhui Wang, Yuanyuan BMC Psychiatry Research BACKGROUND: Anxiety and sleep problems are common comorbidities among outpatients living in high-altitude areas. Network analysis is a novel method to investigate the interaction and the association between symptoms across diverse disorders. This study used network analysis to investigate the network structure symptoms of anxiety and sleep problems among outpatients in high-altitude areas, and to explore the differences in symptom associations in various sex, age, educational levels and employment groups. METHODS: The data was collected from the Sleep Medicine Center of The First People’s Hospital of Yunnan Province from November 2017 to January 2021 with consecutive recruitment (N = 11,194). Anxiety and sleep problems were measured by the Chinese version of the seven-item Generalized Anxiety Disorder Scale (GAD-7) and the Pittsburgh Sleep Quality Index (PSQI) respectively. Central symptoms were identified based on centrality indices and bridge symptoms were identified with bridge indices. The difference of network structures in various sex, age, educational levels and employment groups were also explored. RESULTS: Among all the cases, 6,534 (58.37%; 95% CI: 57.45-59.29%) reported experiencing anxiety (GAD-7 total scores ≥ 5), and 7,718 (68.94%; 95% CI: 68.08-69.80%) reported experiencing sleep problems (PSQI total scores ≥ 10). Based on the results of network analysis, among participants, “Nervousness”, “Trouble relaxing”, “Uncontrollable worry” were the most critical central symptoms and bridge symptoms within the anxiety and sleep problems network structure. The adjusted network model after controlling for covariates was significantly correlated with the original (r = 0.75, P = 0.46). Additionally, there were significant differences in edge weights in the comparisons between sex, age and educational levels groups (P < 0.001), while the employed and unemployed groups did not show significant differences in edge weights (P > 0.05). CONCLUSIONS: In the anxiety and sleep problems network model, among outpatients living in high-altitude areas, nervousness, uncontrollable worry, and trouble relaxing were the most central symptoms and bridge symptoms. Moreover, there were significant differences between various sex, age and educational levels. These findings can be used to provide clinical suggestions for psychological interventions and measures targeting to reduce symptoms that exacerbate mental health. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12888-023-04767-z. BioMed Central 2023-05-15 /pmc/articles/PMC10184966/ /pubmed/37189050 http://dx.doi.org/10.1186/s12888-023-04767-z Text en © The Author(s) 2023 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
Jin, Yu
Li, Jiaqi
Ye, Jing
Luo, Xianyu
Wilson, Amanda
Mu, Lanxue
Zhou, Pinyi
Lv, Yunhui
Wang, Yuanyuan
Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
title Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
title_full Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
title_fullStr Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
title_full_unstemmed Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
title_short Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
title_sort mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184966/
https://www.ncbi.nlm.nih.gov/pubmed/37189050
http://dx.doi.org/10.1186/s12888-023-04767-z
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