Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS)

• Published in: BMC public health 2024-02, Vol.24 (1), p.559-11, Article 559
• Main Authors: Chen, Jiade, Zhang, Fan, Zhang, Yuan, Lin, Ziqiang, Deng, Kaisheng, Hou, Qingqin, Li, Lixia, Gao, Yanhui
• Format: Article
• Language: English
• Subjects: Adults; Aged; Analysis; Arthritis; Arthritis - epidemiology; Binomial distribution; Cardiac patients; Cardiovascular diseases; CHARLS5; China - epidemiology; China4; Chronic conditions; Chronic Disease; Chronic diseases; Chronic diseases2; Chronic illnesses; Chronic obstructive pulmonary disease; Comorbidity; Correlation analysis; Demographic aspects; Development and progression; Diabetes; Diabetes mellitus; Diabetes Mellitus - epidemiology; Diagnosis; Digestive System Diseases; Disease trajectory1; Dyslipidemia; Dyslipidemias; Gastrointestinal diseases; Health aspects; Heart diseases; Heart Diseases - epidemiology; Humans; Hypertension; Hypertension - epidemiology; Longitudinal Studies; Medical research; Medicine, Experimental; Middle age; Middle Aged; Middle aged persons; Middle-aged and older people3; Network analysis; Older people; Prevention; Quality of Life; Regression analysis; Regression models; Retirement; Risk factors; Stroke; Stroke - epidemiology; Support services; Trajectory analysis
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-024-17890-7

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. 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. 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. 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.