文章摘要
石婧,石冰,陶永康,孟丽,周子一,陈术强,段春波,于普林.基于衰弱指数评估的老年人衰弱状况与死亡风险的相关性分析[J].中华流行病学杂志,2020,41(11):1824-1830
基于衰弱指数评估的老年人衰弱状况与死亡风险的相关性分析
Relationship between frailty status and risk of death in the elderly based on frailty index analysis
收稿日期:2020-05-06  出版日期:2020-11-25
DOI:10.3760/cma.j.cn112338-20200506-00691
中文关键词: 衰弱  老年人  死亡率
英文关键词: Frailty  Elderly  Mortality rate
基金项目:
作者单位E-mail
石婧 北京医院, 国家老年医学中心, 国家卫生健康委北京老年医学研究所, 中国医学科学院老年医学研究院 100730  
石冰 吉林大学白求恩第一医院胃肠内科内镜中心, 长春 130021  
陶永康 北京中日友好医院消化科 100029  
孟丽 北京医院, 国家老年医学中心, 国家卫生健康委北京老年医学研究所, 中国医学科学院老年医学研究院 100730  
周子一 北京医院, 国家老年医学中心, 国家卫生健康委北京老年医学研究所, 中国医学科学院老年医学研究院 100730  
陈术强 北京医院, 国家老年医学中心, 国家卫生健康委北京老年医学研究所, 中国医学科学院老年医学研究院 100730  
段春波 北京医院, 国家老年医学中心, 国家卫生健康委北京老年医学研究所, 中国医学科学院老年医学研究院 100730  
于普林 北京医院, 国家老年医学中心, 国家卫生健康委北京老年医学研究所, 中国医学科学院老年医学研究院 100730 pulin_yu@163.com 
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中文摘要:
      目的 分析基于衰弱指数(FI)评估的老年人衰弱状况与死亡风险的相关性。方法 以北京市城市社区老年人健康状况及跌倒情况随访调查数据库中2005年基线调查人群作为本研究的分析样本,以2015年随访调查中收集该队列人群的死亡情况作为结局变量进行分析。采用FI模型对老年人进行衰弱评估,分析不同年龄组老年人FI与死亡率的关系;采用Cox回归模型评估FI对不同年龄组老年人死亡风险的影响,应用Kaplan-Meier法绘制不同衰弱程度老年人的生存曲线。结果 最终纳入分析的1 301例老年人,至2015年共死亡403例,死亡率为31.0%(403/1 301)。老年人死亡率随着FI的增加而增加,且随着FI值的增加死亡率增加的速度减缓,老年人FI值所致死亡存在极限值约0.70,在此基础上任何新增加的健康缺陷均可能导致老年人死亡。多因素Cox回归结果显示,FI值增加会增加老年人死亡的风险(HR=1.143,95% CI:1.034~1.248,P=0.000),且FI值相比于年龄对死亡风险的预测价值更高(HR=1.143比HR=1.048,t=5.827,P=0.000)。随年龄增加,FI值即老年人衰弱对死亡风险影响的HR值从1.179降至1.120,即衰弱对死亡的影响也逐渐降低。生存曲线结果显示,各年龄组老年人的生存率均随衰弱程度的增加而降低(Log-rank=317.812、354.203、247.258,均P=0.000);对不同衰弱程度进行两两比较结果显示,仅≥80岁组高龄老年人衰弱程度较高组(0.4≤FI<0.5、FI≥0.5)生存率比较差异无统计学意义(P=0.368)。结论 采用FI模型对北京市城市社区老年人进行衰弱评估能够较好地反映老年人的衰弱特征,在预测不良健康预后如死亡率方面具有较高的敏感性;在对老年人进行衰弱的干预时,着重于衰弱程度较低或相对年轻的老年人可能更有效地减少衰弱所导致的不良结局。
英文摘要:
      Objective To analyze the relationship between frailty status and the risk of death in the elderly based on the frailty index (FI). Methods Data from a prospective cohort study conducted between 2005 and 2015 in elderly people of an urban community in Beijing were analyzed. The variables related to health and frailty status based on the 2005 baseline survey and death as outcome variables collected in 2015 were used. A FI model was used to evaluate the correlation between FI and mortality in the elderly people in different age groups was analyzed. Cox regression was applied to evaluate the influence of FI on the risk of death, and Kaplan-Meier curves was used to show the survival rate of different frailty levels in the elderly adults. Results Of the 1 301 elderly people included in the analysis, 403 died during 2005-2015, with the 10-year mortality rate of 31.0%(403/1 301). The mortality rate of the elderly increased with the increase of FI, but, with the increase of FI value, the rate of mortality increased slowly. The limit value of FI causing death was around 0.70, indicating any new health problem might cause death at this value. Cox regression analysis showed that higher FI was associated with higher risk for death (HR=1.143, 95%CI: 1.034-1.248, P=0.000), and FI was more significantly associated with death than age (HR=1.143 vs. HR=1.048, t=5.827, P=0.000). With the increase of age, the effect of frailty on the risk of death decreased (HR=1.179 to HR=1.120). Kaplan-Meier curves showed that the survival rate of the elderly in all age groups decreased with the increase of frailty (Log-rank=317.812, 354.203, 247.258, all P=0.000). The survival time between different frailty levels in the elderly were significantly different, except for the elderly adults aged ≥80 years with severe frailty level (0.4≤FI<0.5, FI≥0.5, P=0.368). Conclusions Compared with other evaluation tools of frailty, FI model can better reflect the frailty status of the elderly in communities in Beijing and has a high sensitivity in predicting adverse outcomes such as mortality. In the intervention of frailty in the elderly, focusing on relatively young elderly might be more effective in reducing the adverse outcomes caused by frailty.
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