Zhu Xuan, Ma He, Zhang Hangjing, Zhang Yuting, Tang Shangfeng, Xiong Juyang
School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, Hubei, 430040, People's Republic of China.
Melbourne Institute: Applied Economic & Social Research, The University of Melbourne, Melbourne, VIC, Australia.
BMC Public Health. 2025 Jun 7;25(1):2132. doi: 10.1186/s12889-025-23397-6.
While healthy lifestyles mitigate the risk of multimorbidity (≥ 2 chronic diseases), their temporal dynamics in aging populations, particularly in low- and middle-income countries undergoing rapid demographic structure transition, remain understudied.
Using longitudinal data (2014-2020) from 6,852 Chinese adults (aged ≥ 45 years) in the China Family Panel Studies, we used the subgroup analysis to investigate high risk groups in the chronic diseases status, employed alluvial diagrams to visualize diseases status transition and random intercept cross-lagged panel model to quantify the lagged effect between healthy lifestyles (sleep, physical exercise, smoking, drinking) and chronic diseases status (without diseases, single, multimorbidity).
Compared to male, urban and middle-aged individuals, female, rural and older adults demonstrated more severe chronic diseases status (P < 0.05). The proportion of people with multimorbidity increased over time, from 9.2% in 2014 to 29.1% in 2020. A total of 37.8% of participants experienced diseases status transition, and more than half of whom progressed to multimorbidity. Disease trajectories disproportionately progressed toward multimorbidity. The direction and size of the cross-lagged effects are dynamic. Healthier lifestyles predicted reduced disease severity from 2014 to 2018 (β=-0.106, P < 0.001; β=-0.111, P < 0.001), but this protective effect reversed post-2018, with multimorbidity predicting lower probability of choosing healthy lifestyles (β=-0.160, P < 0.001).
Our study demonstrates dynamic cross-lagged effect exists between healthy lifestyles and chronic diseases status in middle-aged and older Chinese. Disease trajectories and lifestyle-disease interplay reveal critical time-sensitive windows for intervention. Early-stage lifestyle promotion could delay progression, whereas later-stage disease management requires system-level strategies addressing urban-rural healthcare disparities and self-efficacy barriers. These findings directly inform China's Healthy Aging 2030 priorities.
虽然健康的生活方式可降低多种疾病（≥2种慢性病）的风险，但在老龄化人口中，尤其是在经历快速人口结构转变的低收入和中等收入国家，其随时间的动态变化仍未得到充分研究。
利用中国家庭追踪调查中6852名中国成年人（年龄≥45岁）的纵向数据（2014 - 2020年），我们采用亚组分析来研究慢性病状态下的高危人群，使用冲积图来可视化疾病状态转变，并采用随机截距交叉滞后面板模型来量化健康生活方式（睡眠、体育锻炼、吸烟、饮酒）与慢性病状态（无疾病、单一疾病、多种疾病）之间的滞后效应。
与男性、城市和中年个体相比，女性、农村和老年人的慢性病状态更为严重（P < 0.05）。多种疾病患者的比例随时间增加，从2014年的9.2%增至2020年的29.1%。共有37.8%的参与者经历了疾病状态转变，其中超过一半进展为多种疾病。疾病轨迹向多种疾病发展的比例不均衡。交叉滞后效应的方向和大小是动态的。2014年至2018年，更健康的生活方式预示着疾病严重程度降低（β = -0.106，P < 0.001；β = -0.111，P < 0.001），但2018年后这种保护作用逆转，多种疾病预示着选择健康生活方式的可能性降低（β = -0.160，P < 0.001）。
我们的研究表明，中国中老年人的健康生活方式与慢性病状态之间存在动态交叉滞后效应。疾病轨迹和生活方式 - 疾病相互作用揭示了关键的时间敏感干预窗口。早期促进生活方式可延缓疾病进展，而后期疾病管理需要解决城乡医疗差距和自我效能障碍的系统层面策略。这些发现直接为中国《健康老龄化2030规划》提供了依据。
