Wang Xu, Xie Jinzhao, Shang Menglin, Yin Ping, Gu Jing
Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China; Sun Yat-sen Global Health Institute, School of Public Health and Institute of State Governance, Sun Yat-sen University, Guangzhou, China; Key Laboratory of Health Informatics of Guangdong Province, Sun Yat-sen University, Guangzhou, China.
Arch Gerontol Geriatr. 2024 May;120:105331. doi: 10.1016/j.archger.2024.105331. Epub 2024 Jan 15.
This study aimed to identify healthy aging trajectories of Chinese older adults, and explore the factors contributing to these trajectories.
We used data from four waves (2011-2018) of China Health and Retirement Longitudinal Study. We developed a healthy aging metric based on the healthy aging framework of World Health Organization (WHO) and Bayesian multilevel item response theory (IRT) method. The healthy aging trajectories were identified using the latent class growth analysis. The predictors of trajectories were explored using multinomial logistic regression analysis. Additionally, we developed two alternative metrics for healthy aging based on the Chinese Healthy Ageing Index (CHAI) and Rowe and Kahn's model of successful aging, respectively. We compared these metrics to the one developed based on the WHO's healthy aging framework.
We identified three distinct healthy aging trajectories with varying scores and decline rates. Individuals who were female, had lower educational levels, resided in rural areas, experienced depression, had more chronic diseases, participated in fewer social activities, had fewer childhood friends, experienced more adverse childhood events, and had worse family financial status in childhood were more likely to experience a worse healthy aging trajectory compared to their counterparts. Supplementary analysis showed that healthy aging metric based on WHO definition and IRT method had the strongest association with health outcomes compared to the metrics based on CHAI, as well as Rowe and Kahn model.
Our findings provide a foundation for the development of tailored interventions to enhance and sustain healthy aging among Chinese older adults.
本研究旨在确定中国老年人的健康衰老轨迹,并探索影响这些轨迹的因素。
我们使用了中国健康与养老追踪调查(China Health and Retirement Longitudinal Study)四轮(2011 - 2018年)的数据。我们基于世界卫生组织(WHO)的健康衰老框架和贝叶斯多级项目反应理论(IRT)方法制定了一个健康衰老指标。使用潜在类别增长分析确定健康衰老轨迹。使用多项逻辑回归分析探索轨迹的预测因素。此外,我们分别基于中国健康老龄化指数(CHAI)和罗伊(Rowe)与卡恩(Kahn)的成功衰老模型开发了两个健康衰老替代指标。我们将这些指标与基于WHO健康衰老框架开发的指标进行了比较。
我们确定了三种不同的健康衰老轨迹,其得分和下降率各不相同。与同龄人相比,女性、教育水平较低、居住在农村地区、患有抑郁症、患有更多慢性病、参加社会活动较少、童年朋友较少、童年经历更多不良事件以及童年家庭经济状况较差的个体更有可能经历较差的健康衰老轨迹。补充分析表明,与基于CHAI以及罗伊和卡恩模型的指标相比,基于WHO定义和IRT方法的健康衰老指标与健康结果的关联最强。
我们的研究结果为制定针对性干预措施以促进和维持中国老年人的健康衰老提供了基础。