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Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes
PURPOSE: This study aimed to assess the prevalence of depression in middle-aged and elderly patients with diabetes in China, determine the risk factors of depression in these patients, and explore the internal relationship between influencing factors and depression by constructing a pathway model. M...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896971/ https://www.ncbi.nlm.nih.gov/pubmed/36741813 http://dx.doi.org/10.2147/PPA.S392508 |
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author | Yang, Jielin Li, XiaoJu Mao, Lu Dong, Jiaxin Fan, Rong Zhang, Liwen |
author_facet | Yang, Jielin Li, XiaoJu Mao, Lu Dong, Jiaxin Fan, Rong Zhang, Liwen |
author_sort | Yang, Jielin |
collection | PubMed |
description | PURPOSE: This study aimed to assess the prevalence of depression in middle-aged and elderly patients with diabetes in China, determine the risk factors of depression in these patients, and explore the internal relationship between influencing factors and depression by constructing a pathway model. METHODS: Data were collected from the 2018 China Health and Retirement Longitudinal Study (CHRLS). We included 1743 patients with diabetes who were assessed using the CES-D10, which is used to measure depressive symptoms in Chinese older adults. Based on the theory of psychological stress, data were analyzed using SPSS software version 22.0 and MPLUS 8.0. A correlation analysis was used to explore the relationship between the variables and depression scores. A path model was constructed to explore the interrelationships between variables and verify the relationships between variables and depression in patients with diabetes. RESULTS: The prevalence of depression among patients with diabetes was 42.5%. The path analysis results showed that income, diabetes duration, sleep duration, pain distress, self-rated health, and glycemic control directly affected depression, and self-rated health had the largest effect value. With self-rated health and glycemic control as mediator variables, income, diabetes duration, sleep duration, pain distress, glycemic control, and insulin use had indirect effects on depression by influencing self-rated health. Age, frequency of blood glucose monitoring, and exercise glycemic control awareness indirectly affected depression by affecting glycemic control, self-rated health status, and depression. CONCLUSION: We found that the path analysis model could construct the interaction between the influencing factors and explore the potential interrelationship between the influencing factors and diabetes-related depression. Patients with diabetes must adhere to regular medication, maintain a healthy lifestyle, and have effective glycemic control. Diabetes depression can be effectively prevented by making psychological knowledge publicly available, providing health education, and establishing corresponding for diabetes. |
format | Online Article Text |
id | pubmed-9896971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-98969712023-02-04 Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes Yang, Jielin Li, XiaoJu Mao, Lu Dong, Jiaxin Fan, Rong Zhang, Liwen Patient Prefer Adherence Original Research PURPOSE: This study aimed to assess the prevalence of depression in middle-aged and elderly patients with diabetes in China, determine the risk factors of depression in these patients, and explore the internal relationship between influencing factors and depression by constructing a pathway model. METHODS: Data were collected from the 2018 China Health and Retirement Longitudinal Study (CHRLS). We included 1743 patients with diabetes who were assessed using the CES-D10, which is used to measure depressive symptoms in Chinese older adults. Based on the theory of psychological stress, data were analyzed using SPSS software version 22.0 and MPLUS 8.0. A correlation analysis was used to explore the relationship between the variables and depression scores. A path model was constructed to explore the interrelationships between variables and verify the relationships between variables and depression in patients with diabetes. RESULTS: The prevalence of depression among patients with diabetes was 42.5%. The path analysis results showed that income, diabetes duration, sleep duration, pain distress, self-rated health, and glycemic control directly affected depression, and self-rated health had the largest effect value. With self-rated health and glycemic control as mediator variables, income, diabetes duration, sleep duration, pain distress, glycemic control, and insulin use had indirect effects on depression by influencing self-rated health. Age, frequency of blood glucose monitoring, and exercise glycemic control awareness indirectly affected depression by affecting glycemic control, self-rated health status, and depression. CONCLUSION: We found that the path analysis model could construct the interaction between the influencing factors and explore the potential interrelationship between the influencing factors and diabetes-related depression. Patients with diabetes must adhere to regular medication, maintain a healthy lifestyle, and have effective glycemic control. Diabetes depression can be effectively prevented by making psychological knowledge publicly available, providing health education, and establishing corresponding for diabetes. Dove 2023-01-30 /pmc/articles/PMC9896971/ /pubmed/36741813 http://dx.doi.org/10.2147/PPA.S392508 Text en © 2023 Yang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Yang, Jielin Li, XiaoJu Mao, Lu Dong, Jiaxin Fan, Rong Zhang, Liwen Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes |
title | Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes |
title_full | Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes |
title_fullStr | Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes |
title_full_unstemmed | Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes |
title_short | Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes |
title_sort | path analysis of influencing factors of depression in middle-aged and elderly patients with diabetes |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9896971/ https://www.ncbi.nlm.nih.gov/pubmed/36741813 http://dx.doi.org/10.2147/PPA.S392508 |
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