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Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus

PURPOSE: Gestational diabetes mellitus (GDM) negatively affects the quality of life of pregnant women and is influenced by several factors. Research to date treats pregnant women with gestational diabetes as a homogeneous group based on their quality of life. We attempted to identify subgroups based...

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Autores principales: Zhou, Xin-yi, Wang, Yan-feng, Yang, Jie-mei, Yang, Li-yuan, Zhao, Wei-jia, Chen, Yan-ling, Yang, Qiao-hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638685/
https://www.ncbi.nlm.nih.gov/pubmed/37951868
http://dx.doi.org/10.1186/s12884-023-06079-2
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author Zhou, Xin-yi
Wang, Yan-feng
Yang, Jie-mei
Yang, Li-yuan
Zhao, Wei-jia
Chen, Yan-ling
Yang, Qiao-hong
author_facet Zhou, Xin-yi
Wang, Yan-feng
Yang, Jie-mei
Yang, Li-yuan
Zhao, Wei-jia
Chen, Yan-ling
Yang, Qiao-hong
author_sort Zhou, Xin-yi
collection PubMed
description PURPOSE: Gestational diabetes mellitus (GDM) negatively affects the quality of life of pregnant women and is influenced by several factors. Research to date treats pregnant women with gestational diabetes as a homogeneous group based on their quality of life. We attempted to identify subgroups based on self-reported quality of life and explored variables associated with subgroups. METHODS: From September 1, 2020 to November 29, 2020, pregnant women with GDM from two hospitals in Guangdong Province were selected as subjects by convenience sampling method. Medical records provided sociodemographic data, duration of GDM, pregnancy status, and family history of diabetes. Participants completed validated questionnaires for quality of life, anxiety and depression. Latent profile analysis was used to identify profiles of quality of life in pregnant women with GDM, and then a mixed regression method was used to analyze the influencing factors of different profiles. RESULTS: A total of 279 valid questionnaires were collected. The results of the latent profile analysis showed that the quality of life of pregnant women with GDM could be divided into two profiles: C1 “high worry-high support” group (75.6%) and C2 “low worry-low support” group (24.4%). Daily exercise duration and depression degree are negative influencing factors, making it easier to enter the C1 group (p < 0.05). Disease duration and family history of diabetes are positive influencing factors, making it easier to enter the C2 group (p < 0.05). CONCLUSION: The quality of life of pregnant women with GDM had obvious classification characteristics. Pregnant women with exercise habits and depression are more likely to enter the “high worry-high support” group, and health care providers should guide their exercise according to exercise guidelines during pregnancy and strengthen psychological intervention. Pregnant women with a family history of diabetes and a longer duration of the disease are more likely to fall into the “low worry-low support” group. Healthcare providers can strengthen health education for them and improve their disease self-management abilities.
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spelling pubmed-106386852023-11-11 Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus Zhou, Xin-yi Wang, Yan-feng Yang, Jie-mei Yang, Li-yuan Zhao, Wei-jia Chen, Yan-ling Yang, Qiao-hong BMC Pregnancy Childbirth Research PURPOSE: Gestational diabetes mellitus (GDM) negatively affects the quality of life of pregnant women and is influenced by several factors. Research to date treats pregnant women with gestational diabetes as a homogeneous group based on their quality of life. We attempted to identify subgroups based on self-reported quality of life and explored variables associated with subgroups. METHODS: From September 1, 2020 to November 29, 2020, pregnant women with GDM from two hospitals in Guangdong Province were selected as subjects by convenience sampling method. Medical records provided sociodemographic data, duration of GDM, pregnancy status, and family history of diabetes. Participants completed validated questionnaires for quality of life, anxiety and depression. Latent profile analysis was used to identify profiles of quality of life in pregnant women with GDM, and then a mixed regression method was used to analyze the influencing factors of different profiles. RESULTS: A total of 279 valid questionnaires were collected. The results of the latent profile analysis showed that the quality of life of pregnant women with GDM could be divided into two profiles: C1 “high worry-high support” group (75.6%) and C2 “low worry-low support” group (24.4%). Daily exercise duration and depression degree are negative influencing factors, making it easier to enter the C1 group (p < 0.05). Disease duration and family history of diabetes are positive influencing factors, making it easier to enter the C2 group (p < 0.05). CONCLUSION: The quality of life of pregnant women with GDM had obvious classification characteristics. Pregnant women with exercise habits and depression are more likely to enter the “high worry-high support” group, and health care providers should guide their exercise according to exercise guidelines during pregnancy and strengthen psychological intervention. Pregnant women with a family history of diabetes and a longer duration of the disease are more likely to fall into the “low worry-low support” group. Healthcare providers can strengthen health education for them and improve their disease self-management abilities. BioMed Central 2023-11-11 /pmc/articles/PMC10638685/ /pubmed/37951868 http://dx.doi.org/10.1186/s12884-023-06079-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 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
Zhou, Xin-yi
Wang, Yan-feng
Yang, Jie-mei
Yang, Li-yuan
Zhao, Wei-jia
Chen, Yan-ling
Yang, Qiao-hong
Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
title Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
title_full Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
title_fullStr Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
title_full_unstemmed Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
title_short Latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
title_sort latent profile analysis and influencing factors of quality of life in pregnant women with gestational diabetes mellitus
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638685/
https://www.ncbi.nlm.nih.gov/pubmed/37951868
http://dx.doi.org/10.1186/s12884-023-06079-2
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