The complexity of comorbidity distribution and pathogenesis in the elderly based on a dependency network simulation
Abstract Multiple chronic diseases in the elderly significantly impact health and quality of life. Identifying key comorbidities and their formation can aid in controlling their progression. Using two follow-up datasets from CHARLS, we constructed a dependency network of disease progression and appl...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-90622-y |
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| Summary: | Abstract Multiple chronic diseases in the elderly significantly impact health and quality of life. Identifying key comorbidities and their formation can aid in controlling their progression. Using two follow-up datasets from CHARLS, we constructed a dependency network of disease progression and applied multi-centrality indicators to analyze relationships among chronic disease comorbidities. (1) Chronic disease comorbidities follow a power-law distribution. (2) Common chronic disease comorbidities include heart disease and stroke, dyslipidemia and stroke, dyslipidemia and chronic liver disease, and chronic liver disease and stroke. (3) Key states in comorbidity formation include complete health, only asthma, only arthritis, and stomach disease with arthritis. (4) Controlling a single disease state does not alter the final distribution of comorbidities. The formation of chronic disease comorbidities show complexity. Reducing individual comorbidity prevalence requires intervention across the entire formation process, as targeting single diseases has limited impact on the overall population distribution. |
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| ISSN: | 2045-2322 |