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中年和老年人慢性病轨迹网络分析:来自中国健康与养老追踪调查(CHARLS)的证据。

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

机构信息

Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China.

Guangdong Provincial Institute of Sports Science, Guangzhou, Guangdong, China.

出版信息

BMC Public Health. 2024 Feb 22;24(1):559. doi: 10.1186/s12889-024-17890-7.

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.

摘要

背景

鉴于中国中年和老年人慢性病和共病风险增加,确定慢性病发展轨迹并解决慢性病之间的时间相关性至关重要。

方法

本研究分析了来自中国健康与退休纵向研究(CHARLS 2011-2018)的 15895 名参与者的数据。使用二项式检验和条件逻辑回归模型来估计 14 种慢性疾病之间的关联,并采用疾病轨迹网络分析来可视化这些关系。

结果

分析表明,高血压是 14 种慢性疾病中最常见的疾病,在所有慢性疾病中具有最高的累积发病率。在疾病轨迹网络中,关节炎被发现是起点,而消化疾病、高血压、心脏病和血脂异常处于中心位置,而与记忆相关的疾病(MRD)、中风和糖尿病则处于网络的外围。

结论

通过慢性疾病轨迹网络分析,我们发现关节炎容易发生和发展为各种其他疾病。此外,心脏病/高血压/消化疾病/血脂异常患者发生其他慢性疾病的风险更高。对于患有多种疾病的患者,早期预防可以防止他们病情恶化,如中风、MRD 和糖尿病。通过确定慢性疾病的轨迹网络,研究结果为制定早期预防和个性化支持服务提供了重要的见解,以减轻疾病负担并提高患者的生活质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/598b/10882875/1f06eea13083/12889_2024_17890_Fig1_HTML.jpg

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