An Chuanbo, Chen Hui, Cheng Yangyang, Zhang Zifan, Yuan Changzheng, Xu Xiaolin
School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang, China.
School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang, China.
Maturitas. 2025 Jan;192:108160. doi: 10.1016/j.maturitas.2024.108160. Epub 2024 Nov 23.
The prevalence of multimorbidity is socially patterned, but little is known about how socioeconomic inequality might affect the long-term progression of multimorbidity. This study aimed to identify multimorbidity trajectories and to examine their association with socioeconomic status (SES) among middle-aged and older Chinese adults.
A total of 3837 middle-aged and older participants were included from the dynamic cohort of the China Health and Retirement Longitudinal Study, 2011-2018. Multimorbidity trajectories were assessed using the Chinese Multimorbidity-Weighted Index (CMWI), which covers 14 chronic conditions. Group-based trajectory modeling was used to identify multimorbidity developmental trajectories. Education, working status, and total household income were used to construct SES scores. The associations between SES and CMWI trajectories were estimated using multinomial logistic regression models adjusting for sociodemographic and lifestyle factors.
Four distinct CMWI trajectories were identified: 'no multimorbidity' (16.8 %), 'new-onset multimorbidity' (48.7 %), 'slowly increasing multimorbidity' (24.3 %), and 'rapidly increasing multimorbidity' (10.2 %). Lower SES was associated with higher odds of experiencing the 'rapidly increasing' trajectory (P < 0.01); for example, compared with the 'no multimorbidity' group, participants with low SES had a 96 % (OR, 1.96; 95 % CI, 1.29 to 2.98) increased odds of belonging to the 'rapidly increasing' group.
Socioeconomic inequalities were observed in the CMWI trajectories of multimorbidity in middle-aged and older Chinese adults. The findings suggest effective strategies for preventing and controlling multimorbidity should be made from a long-term perspective, especially for those of lower SES.
多种疾病并存的患病率存在社会模式差异，但对于社会经济不平等如何影响多种疾病并存的长期发展知之甚少。本研究旨在确定多种疾病并存的轨迹，并研究其与中国中老年成年人社会经济地位（SES）之间的关联。
从中国健康与养老追踪调查2011 - 2018年的动态队列中纳入了3837名中老年参与者。使用涵盖14种慢性病的中国多种疾病加权指数（CMWI）评估多种疾病并存的轨迹。采用基于组的轨迹模型来识别多种疾病并存的发展轨迹。使用教育程度、工作状态和家庭总收入来构建SES得分。使用多项逻辑回归模型估计SES与CMWI轨迹之间的关联，并对社会人口学和生活方式因素进行了调整。
确定了四种不同的CMWI轨迹：“无多种疾病并存”（16.8%）、“新发多种疾病并存”（48.7%）、“缓慢增加的多种疾病并存”（24.3%）和“快速增加的多种疾病并存”（10.2%）。较低的SES与经历“快速增加”轨迹的较高几率相关（P < 0.01）；例如，与“无多种疾病并存”组相比，低SES参与者属于“快速增加”组的几率增加了96%（OR，1.96；95% CI，1.29至2.98）。
在中国中老年成年人多种疾病并存的CMWI轨迹中观察到了社会经济不平等。研究结果表明应从长期角度制定预防和控制多种疾病并存的有效策略，特别是对于SES较低的人群。
