Xuan Zhu, He Ma, Hangjing Zhang, Yuting Zhang, Shangfeng Tang, Juyang Xiong
{"title":"Dynamic cross-lagged effects between healthy lifestyles and multimorbidity among middle-aged and older adults in China.","authors":"Xuan Zhu, He Ma, Hangjing Zhang, Yuting Zhang, Shangfeng Tang, Juyang Xiong","doi":"10.1186/s12889-025-23397-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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<sub>1</sub>=-0.106, P<sub>1</sub> < 0.001; β<sub>2</sub>=-0.111, P<sub>2</sub> < 0.001), but this protective effect reversed post-2018, with multimorbidity predicting lower probability of choosing healthy lifestyles (β<sub>3</sub>=-0.160, P<sub>3</sub> < 0.001).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2132"},"PeriodicalIF":3.6000,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12144725/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Public Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12889-025-23397-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Background: 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.
Methods: 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).
Results: 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 (β1=-0.106, P1 < 0.001; β2=-0.111, P2 < 0.001), but this protective effect reversed post-2018, with multimorbidity predicting lower probability of choosing healthy lifestyles (β3=-0.160, P3 < 0.001).
Conclusions: 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.
背景:虽然健康的生活方式可以降低多种疾病(≥2种慢性病)的风险,但其在老龄化人口中的时间动态,特别是在经历快速人口结构转型的低收入和中等收入国家,仍未得到充分研究。方法:利用中国家庭面板研究中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调查慢性疾病状态的高危人群,采用冲积图来可视化疾病状态转换,采用随机截点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)与慢性疾病状态(无疾病、单一、多疾病)之间的滞后效应。结果:与男性、城市和中年人相比,女性、农村和老年人的慢性疾病状况更严重(P < 1=-0.106, P < 2=-0.111, P < 3=-0.160, P < 3)。结论:健康生活方式与中国中老年人群的慢性疾病状况存在动态交叉滞后效应。疾病轨迹和生活方式与疾病的相互作用揭示了干预的关键时间敏感窗口。早期生活方式的促进可以延缓疾病进展,而晚期疾病管理需要系统层面的策略来解决城乡医疗保健差距和自我效能障碍。这些发现直接为中国2030年健康老龄化的优先事项提供了依据。
期刊介绍:
BMC Public Health is an open access, peer-reviewed journal that considers articles on the epidemiology of disease and the understanding of all aspects of public health. The journal has a special focus on the social determinants of health, the environmental, behavioral, and occupational correlates of health and disease, and the impact of health policies, practices and interventions on the community.