Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System

Background: People with depression are at increased risk for comorbidities; however, the clustering of comorbidity patterns in these patients is still unclear. Objective: The aim of the study was to identify latent comorbidity patterns and explore the comorbidity network structure that included 12 c...

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Autores principales: Ramos-Vera, Cristian, Serpa‐Barrientos, Antonio, Vallejos-Saldarriaga, José, Calizaya Milla, Yaquelin Eveling, Saintila, Jacksaint
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Lenguaje:inglés
Publicado: 2023
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author Ramos-Vera, Cristian
Serpa‐Barrientos, Antonio
Vallejos-Saldarriaga, José
Calizaya Milla, Yaquelin Eveling
Saintila, Jacksaint
author_browse Calizaya Milla, Yaquelin Eveling
Ramos-Vera, Cristian
Saintila, Jacksaint
Serpa‐Barrientos, Antonio
Vallejos-Saldarriaga, José
author_facet Ramos-Vera, Cristian
Serpa‐Barrientos, Antonio
Vallejos-Saldarriaga, José
Calizaya Milla, Yaquelin Eveling
Saintila, Jacksaint
author_sort Ramos-Vera, Cristian
collection Producción científica
description Background: People with depression are at increased risk for comorbidities; however, the clustering of comorbidity patterns in these patients is still unclear. Objective: The aim of the study was to identify latent comorbidity patterns and explore the comorbidity network structure that included 12 chronic conditions in adults diagnosed with depressive disorder. Methods: A cross-sectional study was conducted based on secondary data from the 2017 behavioral risk factor surveillance system (BRFSS) covering all 50 American states. A sample of 89,209 U.S. participants, 29,079 men and 60,063 women aged 18 years or older, was considered using exploratory graphical analysis (EGA), a statistical graphical model that includes algorithms for grouping and factoring variables in a multivariate system of network relationships. Results: The EGA findings show that the network presents 3 latent comorbidity patterns, i.e., that comorbidities are grouped into 3 factors. The first group was composed of 7 comorbidities (obesity, cancer, high blood pressure, high blood cholesterol, arthritis, kidney disease, and diabetes). The second pattern of latent comorbidity included the diagnosis of asthma and respiratory diseases. The last factor grouped 3 conditions (heart attack, coronary heart disease, and stroke). Hypertension reported higher measures of network centrality. Conclusion: Associations between chronic conditions were reported; furthermore, they were grouped into 3 latent dimensions of comorbidity and reported network factor loadings. The implementation of care and treatment guidelines and protocols for patients with depressive symptomatology and multimorbidity is suggested.
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spelling oai:cris.upeu.edu.pe:20.500.15037/3002026-11-02T22:00:04ZNetwork Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance SystemRamos-Vera, CristianSerpa‐Barrientos, AntonioVallejos-Saldarriaga, JoséCalizaya Milla, Yaquelin EvelingSaintila, JacksaintBackground: People with depression are at increased risk for comorbidities; however, the clustering of comorbidity patterns in these patients is still unclear. Objective: The aim of the study was to identify latent comorbidity patterns and explore the comorbidity network structure that included 12 chronic conditions in adults diagnosed with depressive disorder. Methods: A cross-sectional study was conducted based on secondary data from the 2017 behavioral risk factor surveillance system (BRFSS) covering all 50 American states. A sample of 89,209 U.S. participants, 29,079 men and 60,063 women aged 18 years or older, was considered using exploratory graphical analysis (EGA), a statistical graphical model that includes algorithms for grouping and factoring variables in a multivariate system of network relationships. Results: The EGA findings show that the network presents 3 latent comorbidity patterns, i.e., that comorbidities are grouped into 3 factors. The first group was composed of 7 comorbidities (obesity, cancer, high blood pressure, high blood cholesterol, arthritis, kidney disease, and diabetes). The second pattern of latent comorbidity included the diagnosis of asthma and respiratory diseases. The last factor grouped 3 conditions (heart attack, coronary heart disease, and stroke). Hypertension reported higher measures of network centrality. Conclusion: Associations between chronic conditions were reported; furthermore, they were grouped into 3 latent dimensions of comorbidity and reported network factor loadings. The implementation of care and treatment guidelines and protocols for patients with depressive symptomatology and multimorbidity is suggested.Articlehttps://pubmed.ncbi.nlm.nih.gov/37096248https://downloads.hindawi.com/journals/drt/2023/9969532.pdfhttp://dx.doi.org/10.1155/2023/9969532PMC1012260310.1155/2023/9969532https://hdl.handle.net/20.500.15037/30037096248W4365815908enDepression Research and Treatment2090-13212090-133X2023-04-152026-06-13T08:10:11Z2026-06-13T08:10:11Z
spellingShingle Ramos-Vera, Cristian
Serpa‐Barrientos, Antonio
Vallejos-Saldarriaga, José
Calizaya Milla, Yaquelin Eveling
Saintila, Jacksaint
Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System
title Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System
title_full Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System
title_fullStr Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System
title_full_unstemmed Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System
title_short Network Structure of Comorbidity Patterns in U.S. Adults with Depression: A National Study Based on Data from the Behavioral Risk Factor Surveillance System
title_sort network structure of comorbidity patterns in u s adults with depression a national study based on data from the behavioral risk factor surveillance system
url https://pubmed.ncbi.nlm.nih.gov/37096248
https://downloads.hindawi.com/journals/drt/2023/9969532.pdf
http://dx.doi.org/10.1155/2023/9969532
https://hdl.handle.net/20.500.15037/300
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