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Uncovering bridging diseases in complex multimorbidity pathways: A network science approach.
Javier Alvarez-Galvez1,2, Javier Arroyo3,4
1Computational Social Science DataLab (CS2 DataLab), University Institute for Sustainable Social Development, University of Cádiz, Cádiz, Spain.
Plos One
|May 7, 2025
Summary
Multimorbidity, the presence of multiple chronic diseases, shows gender differences. Network science identified liver dysfunction in men and depression in women as key drivers of complex disease patterns.
Area of Science:
- Gerontology
- Network Science
- Public Health
Background:
- Multimorbidity, the co-occurrence of multiple chronic diseases, poses a significant healthcare challenge.
- Understanding the underlying patterns and key drivers of multimorbidity is crucial for effective management.
- Existing research often lacks detailed analysis of specific diseases that bridge different chronic conditions.
Purpose of the Study:
- To apply network science to analyze multimorbidity structures in older adults.
- To identify specific diseases that act as bridging conditions in the development of complex multimorbidity.
- To investigate potential sex/gender differences in multimorbidity patterns and their drivers.
Main Methods:
- Network science analysis was employed to map disease co-occurrences.
- Data from a representative sample of 2,200 individuals aged 50+ in southern Spain were utilized.
- Bridging diseases contributing to complex multimorbidity structures were identified.
Main Results:
- Significant gender-based differences in multimorbidity patterns were observed.
- Women exhibited a higher burden of chronic diseases, leading to more complex disease networks.
- Liver dysfunction was identified as a key bridging disease in men, while depression was highlighted in women.
Conclusions:
- Sex/gender-specific factors significantly influence multimorbidity patterns.
- Targeting specific bridging diseases like liver dysfunction and depression may help manage complex multimorbidity.
- Developing tailored healthcare strategies based on sex/gender is essential for preventing multisystem multimorbidity and its impact on health outcomes.
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