Methods of analysing patterns of multimorbidity using network analysis: a scoping review.

Jones, Imogen; Cocker, Fiona; Jose, Matthew; Charleston, Michael A.; Neil, Amanda L.

doi:10.1007/s10389-021-01685-w

Cited by 11 publications

(15 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The latter pattern included diseases, such as heart attack, coronary heart disease, stroke, and kidney disease. The latter pattern has been reported more frequently in several similar studies ( 21 , 22 ).…”

Section: Discussionsupporting

confidence: 72%

Identifying latent comorbidity patterns in adults with perceived cognitive impairment: Network findings from the behavioral risk factor surveillance system

Ramos-Vera

Saintila

O'Diana

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

BackgroundPeople with cognitive impairment may be exposed to an increased risk of comorbidities; however, the clustering of comorbidity patterns in these patients is unclear.ObjectiveTo explore the network structure of chronic comorbidity in a U.S. national sample spanning all 50 U.S. states with more than 170,000 participants reporting perceived cognitive impairment.MethodsThis is a cross-sectional study conducted using Behavioral Risk Factor Surveillance System (BRFSS) secondary data collected in 2019 and covering 49 U.S. states, the District of Columbia, Guam, and the Commonwealth of Puerto Rico. A total of 15,621 non-institutionalized U.S. adult participants who reported “yes” to the subjective cognitive impairment question were considered, of whom 7,045 were men and 8,576 were women. All participants were aged 45 years or older. A statistical graphical model was used that included clustering algorithms and factorization of variables in a multivariate network relationship system [exploratory graphical analysis (EGA)].ResultsThe results of the EGA show associations between the comorbid conditions evaluated. These associations favored the clustering of various comorbidity patterns. In fact, three patterns of comorbidities have been identified: (1) arthritis, asthma, respiratory diseases, and depression, (2) obesity, diabetes, blood pressure high, and blood cholesterol high, and (3) heart attack, coronary heart disease, stroke, and kidney disease.ConclusionThese results suggest the development of interdisciplinary treatment strategies in patients with perceived cognitive impairment, which could help to design an integrated prevention and management of the disease and other related health problems, such as Alzheimer's disease and related dementias.

show abstract

Section: Discussionsupporting

confidence: 72%

Identifying latent comorbidity patterns in adults with perceived cognitive impairment: Network findings from the behavioral risk factor surveillance system

Ramos-Vera

Saintila

O'Diana

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…Second, it may be worthwhile to compare CORA, its operations, and its results to those of other techniques currently used or being developed in psychology and neighboring disciplines for the analysis of multioutput problems such as multimorbidity and polypharmacy. For instance, some researchers have recommended a focus on the algorithms and techniques of network analysis to do justice to the analytical complexity inherent in analyzing data on multimorbid patients (Jones et al, 2023). Irrespective of the direction that is eventually taken first, there is no doubt that the importance of methods and techniques for the analysis of multieffect data will grow in parallel with the prevalence of multimorbidity issues in psychological research.…”

Section: Discussionmentioning

confidence: 99%

Combinational regularity analysis (CORA): An introduction for psychologists.

Thiem,

Mkrtchyan,

Sebechlebská

2024

Psychological Methods

View full text Add to dashboard Cite

“…The second comorbid dimension integrated asthma-respiratory disease, and the third latent group jointly identified cardiovascular disease (heart attack-coronary heart disease-stroke conditions). The latter two factors have been reported most frequently in various studies of comorbidity patterns using factor analysis and multivariate relationship network models [ 45 , 46 ].…”

Section: Discussionmentioning

confidence: 99%

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

Ramos-Vera

Serpa

Saldarriaga

et al. 2023

Depression Research and Treatment

View full text Add to dashboard Cite

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.

show abstract

Methods of analysing patterns of multimorbidity using network analysis: a scoping review.

Cited by 11 publications

References 24 publications

Identifying latent comorbidity patterns in adults with perceived cognitive impairment: Network findings from the behavioral risk factor surveillance system

Identifying latent comorbidity patterns in adults with perceived cognitive impairment: Network findings from the behavioral risk factor surveillance system

Combinational regularity analysis (CORA): An introduction for psychologists.

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

Contact Info

Product

Resources

About