Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS)
Abstract Background Given the increased risk of chronic diseases and comorbidity among middle-aged and older adults in China, it is pivotal to identify the disease trajectory of developing chronic multimorbidity and address the temporal correlation among chronic diseases. Method The data of 15895 pa...
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| Format: | Article |
| Language: | English |
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BMC
2024-02-01
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| Series: | BMC Public Health |
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| Online Access: | https://doi.org/10.1186/s12889-024-17890-7 |
| _version_ | 1797272879718465536 |
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| author | Jiade Chen Fan Zhang Yuan Zhang Ziqiang Lin Kaisheng Deng Qingqin Hou Lixia Li Yanhui Gao |
| author_facet | Jiade Chen Fan Zhang Yuan Zhang Ziqiang Lin Kaisheng Deng Qingqin Hou Lixia Li Yanhui Gao |
| author_sort | Jiade Chen |
| collection | DOAJ |
| description | Abstract Background Given the increased risk of chronic diseases and comorbidity among middle-aged and older adults in China, it is pivotal to identify the disease trajectory of developing chronic multimorbidity and address the temporal correlation among chronic diseases. Method The data of 15895 participants from the China Health and Retirement Longitudinal Study (CHARLS 2011 – 2018) were analyzed in the current study. Binomial tests and the conditional logistic regression model were conducted to estimate the associations among 14 chronic diseases, and the disease trajectory network analysis was adopted to visualize the relationships. Results The analysis showed that hypertension is the most prevalent disease among the 14 chronic conditions, with the highest cumulative incidence among all chronic diseases. In the disease trajectory network, arthritis was found to be the starting point, and digestive diseases, hypertension, heart diseases, and dyslipidemia were at the center, while memory-related disease (MRD), stroke, and diabetes were at the periphery of the network. Conclusions With the chronic disease trajectory network analysis, we found that arthritis was prone to the occurrence and development of various other diseases. In addition, patients of heart diseases/hypertension/digestive disease/dyslipidemia were under higher risk of developing other chronic conditions. For patients with multimorbidity, early prevention can preclude them from developing into poorer conditions, such as stroke, MRD, and diabetes. By identifying the trajectory network of chronic disease, the results provided critical insights for developing early prevention and individualized support services to reduce disease burden and improve patients’ quality of life. |
| first_indexed | 2024-03-07T14:36:36Z |
| format | Article |
| id | doaj.art-212bd2b8ec2744c6b588d76d235a0c67 |
| institution | Directory Open Access Journal |
| issn | 1471-2458 |
| language | English |
| last_indexed | 2024-03-07T14:36:36Z |
| publishDate | 2024-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj.art-212bd2b8ec2744c6b588d76d235a0c672024-03-05T20:37:26ZengBMCBMC Public Health1471-24582024-02-0124111110.1186/s12889-024-17890-7Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS)Jiade Chen0Fan Zhang1Yuan Zhang2Ziqiang Lin3Kaisheng Deng4Qingqin Hou5Lixia Li6Yanhui Gao7Department of Public Health and Preventive Medicine, School of Medicine, Jinan UniversityDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan UniversityGuangdong Provincial Institute of Sports ScienceDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan UniversitySchool of Public Health, Guangdong Pharmaceutical UniversitySchool of Public Health, Guangdong Pharmaceutical UniversitySchool of Public Health, Guangdong Pharmaceutical UniversityDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan UniversityAbstract Background Given the increased risk of chronic diseases and comorbidity among middle-aged and older adults in China, it is pivotal to identify the disease trajectory of developing chronic multimorbidity and address the temporal correlation among chronic diseases. Method The data of 15895 participants from the China Health and Retirement Longitudinal Study (CHARLS 2011 – 2018) were analyzed in the current study. Binomial tests and the conditional logistic regression model were conducted to estimate the associations among 14 chronic diseases, and the disease trajectory network analysis was adopted to visualize the relationships. Results The analysis showed that hypertension is the most prevalent disease among the 14 chronic conditions, with the highest cumulative incidence among all chronic diseases. In the disease trajectory network, arthritis was found to be the starting point, and digestive diseases, hypertension, heart diseases, and dyslipidemia were at the center, while memory-related disease (MRD), stroke, and diabetes were at the periphery of the network. Conclusions With the chronic disease trajectory network analysis, we found that arthritis was prone to the occurrence and development of various other diseases. In addition, patients of heart diseases/hypertension/digestive disease/dyslipidemia were under higher risk of developing other chronic conditions. For patients with multimorbidity, early prevention can preclude them from developing into poorer conditions, such as stroke, MRD, and diabetes. By identifying the trajectory network of chronic disease, the results provided critical insights for developing early prevention and individualized support services to reduce disease burden and improve patients’ quality of life.https://doi.org/10.1186/s12889-024-17890-7Disease trajectory1Chronic diseases2Middle-aged and older people3China4CHARLS5 |
| spellingShingle | Jiade Chen Fan Zhang Yuan Zhang Ziqiang Lin Kaisheng Deng Qingqin Hou Lixia Li Yanhui Gao Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS) BMC Public Health Disease trajectory1 Chronic diseases2 Middle-aged and older people3 China4 CHARLS5 |
| title | Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS) |
| title_full | Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS) |
| title_fullStr | Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS) |
| title_full_unstemmed | Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS) |
| title_short | Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS) |
| title_sort | trajectories network analysis of chronic diseases among middle aged and older adults evidence from the china health and retirement longitudinal study charls |
| topic | Disease trajectory1 Chronic diseases2 Middle-aged and older people3 China4 CHARLS5 |
| url | https://doi.org/10.1186/s12889-024-17890-7 |
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