| 郭雁飞,阮晔,孙双圆,黄哲宙,董俣君,蒋安丽,施燕,吴凡.中国50岁及以上人群衰弱轨迹的研究[J].Chinese journal of Epidemiology,2022,43(11):1711-1716 |
| 中国50岁及以上人群衰弱轨迹的研究 |
| Frailty trajectories in people aged 50 years and above in China |
| Received:May 28, 2022 |
| DOI：10.3760/cma.j.cn112338-20220528-00477 |
| KeyWord: 衰弱 轨迹 纵向研究 |
| English Key Word: Frailty Trajectory Longitudinal study |
| FundProject:美国国立老龄研究所项目（R01-AG034479）；上海市卫生健康委员项目（201840118）；上海市医学领军人才（2019LJ24）；上海市公共卫生三年行动计划（2020-2022年）（GWV-10.1-XK16） |
| Author Name | Affiliation | E-mail | | Guo Yanfei | Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
School of Public Health and Community Medicine, Institution of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg 40530, Sweden | | | Ruan Ye | Shanghai Institutes of Preventive Medicine, Shanghai 200336, China | | | Sun Shuangyuan | Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China | | | Huang Zhezhou | Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China | | | Dong Yujun | Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China | | | Jiang Anli | Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China | | | Shi Yan | Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China | shiyan@scdc.sh.cn | | Wu Fan | Shanghai Medical College, Fudan University, Shanghai 200032, China | wufan@shmu.edu.cn |
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| Abstract: |
| 目的 识别中国≥50岁人群的衰弱轨迹，并探索相关影响因素。方法 采用WHO“全球老龄化与成人健康研究”（SAGE）中国项目第一至第三轮纵向数据，由32种变量计算衰弱指数得分，并在此基础上在组基轨迹模型中采用删失正态模型确定随时间变化的衰弱轨迹模式，采用多项式logistic回归模型研究社会经济地位和行为影响因素对衰弱轨迹的影响。结果 共纳入4 303名≥50岁且拥有3轮完整数据的调查对象进入分析，本研究识别出3条衰弱轨迹：低水平稳定轨迹（LT）、中度增加轨迹（MT）和高度增加轨迹（HT），分别占所有调查对象的75.9%，19.1%和5.0%。多项式logistic回归分析的结果显示，与LT组相比，HT组更倾向是女性（OR=1.88，95%CI：1.22~2.92）和农村居民（OR=1.87，95%CI：1.29~2.70）。在家庭人均财富方面，OR值有一个明显的梯度，较低的家庭财富更有可能归为HT组。结论 本研究识别出了3种我国≥50岁人群衰弱轨迹的进展模式，并强调了干预措施应尽可能地以那些衰弱进展快速的脆弱人群为目标。 |
| English Abstract: |
| Objective To identify distinct frailty trajectories in a cohort of nationwide community adults aged 50 years and above, and explore the relationship between frailty trajectories and their socioeconomic characteristics and behavioral factors at baseline survey. Methods Data were from the three waves of "Global Ageing and Adult Health Research" (SAGE) by World Health Organization in China. The frailty index is generated from 32 items. Group-based trajectory modeling using a censored normal model was conducted to identify the patterns in frailty progression over time. Multinomial logistic regression model was used to examine the effect of socioeconomic status and behavioral factors on the frailty trajectories. Results A total of 4 303 adults aged 50 years and above with complete data from all three rounds of project were included in the final analysis. Three frailty trajectories were identified:low and stable trajectory (LT) (56.8%), moderately increased trajectory (MT) (34.4%) and highly increased trajectory (HT) (8.8%). The results of the multinomial logistic regression analysis showed that the HT group was more likely to be women (OR=1.88, 95%CI:1.22-2.92) and rural residents (OR=1.87, 95%CI:1.29-2.70) compared with the LT group. In terms of household wealth per capita, there was a clear gradient in ORs, the people with lower household wealth were more likely to be classified in the HT group. Conclusion This study identified three patterns of progression of frailty trajectories in population aged 50 years and above in China and highlighted that interventions should target those vulnerable populations with rapid progression of frailty. |
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