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[中国65岁及以上老年人日常生活活动能力残疾6年风险预测]

[Prediction of 6-year risk of activities of daily living disability in elderly aged 65 years and older in China].

作者信息

Zhou J H, Lyu Y B, Wei Y, Wang J N, Ye L L, Wu B, Liu Y, Qiu Y D, Zheng X L, Guo Y B, Ju A P, Xue K, Zhang X C, Zhao F, Qu Y L, Chen C, Liu Y C, Mao C, Shi X M

机构信息

China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.

Division of Non-communicable Disease and Aging Health Management, Chinese Center for Disease Control and Prevention, Beijing 102206, China.

出版信息

Zhonghua Yi Xue Za Zhi. 2022 Jan 11;102(2):94-100. doi: 10.3760/cma.j.cn112137-20210706-01512.

DOI:10.3760/cma.j.cn112137-20210706-01512
PMID:35012296
Abstract

To construct an easy-to-use risk prediction tool for 6-year risk of activities of daily living(ADL) disability among Chinese elderly aged 65 and above. A total of 34 349 elderly aged 65 and above were recruited from the Chinese Longitudinal Healthy Longevity Survey. Demographic characteristics, lifestyle and chronic diseases of the elderly were collected through face-to-face interviews. The functional status of the elderly was evaluated by the instrumental activities of daily living(IADL) scale. The mental health status of the elderly was evaluated by the Mini-Mental State Examination. The height, weight, blood pressure and other information of the subjects were obtained through physical examination and body mass index(BMI) was calculated. The ADL status was evaluated by Katz Scale at baseline and follow-up surveys. Taking ADL status as the dependent variable and the key predictors were selected from Lasso regression as the independent variables, a Cox proportional risk regression model was constructed and visualized by the nomogram tool. Area under the receiver operating characteristic curve(AUC) and calibration curve were used to evaluate the discrimination and calibration of the model. A total of 200 bootstrap resamples were used for internal validation of the model. Sensitivity analysis was used to evaluate the robustness of the model. The , ) of subjects' age as 86(75, 94) years old, of which 9 774(46.0%) were males. A total of 112 606 person-years were followed up, 4 578 cases of ADL disability occurred and the incidence density was 40.7/1 000 person-years. Cox proportional risk regression model analysis showed that older age, higher BMI, female, hypertension and history of cerebrovascular disease were associated with higher risk of ADL disability [(95%) were 1.06(1.05-1.06), 1.05(1.04-1.06), 1.17(1.10-1.25),1.07(1.01-1.13) and 1.41(1.23-1.62), respectively.]; Ethnic minorities, walking 1 km continuously, taking public transportation alone and doing housework almost every day were associated with lower risk of ADL disability [95%): 0.71(0.62-0.80), 0.72(0.65-0.80), 0.74(0.68-0.82) and 0.69(0.64-0.74), respectively]. The AUC value of the model was 0.853, and the calibration curve showed that the predicted probability was highly consistent with the observed probability. After excluding non-intervening factors(age, sex and ethnicity), the AUC value of the model for predicting the risk of ADL disability was 0.779. The AUC values of 65-74 years old and 75 years old and above were 0.634 and 0.765, respectively. The AUC values of the model based on walking 1 km continuous and taking public transport alone in IADL and the model based on comprehensive score of IADL were 0.853 and 0.851, respectively. The risk prediction model of ADL disability established in this study has good performance and robustness.

摘要

构建一个易于使用的风险预测工具,用于预测65岁及以上中国老年人日常生活活动(ADL)能力丧失的6年风险。从中国老年健康长寿纵向调查中招募了总共34349名65岁及以上的老年人。通过面对面访谈收集老年人的人口统计学特征、生活方式和慢性病情况。采用日常生活能力量表(IADL)评估老年人的功能状态。采用简易精神状态检查表评估老年人的心理健康状况。通过体格检查获取受试者的身高、体重、血压等信息,并计算体重指数(BMI)。在基线和随访调查中采用Katz量表评估ADL状态。以ADL状态为因变量,从Lasso回归中选择关键预测因素作为自变量,构建Cox比例风险回归模型,并通过列线图工具进行可视化展示。采用受试者工作特征曲线下面积(AUC)和校准曲线评估模型的区分度和校准度。共进行200次自助重抽样对模型进行内部验证。采用敏感性分析评估模型的稳健性。受试者年龄的中位数为86(75,94)岁,其中男性9774名(46.0%)。共随访112606人年,发生4578例ADL能力丧失病例,发病密度为40.7/1000人年。Cox比例风险回归模型分析显示,年龄较大、BMI较高、女性、高血压和脑血管病史与ADL能力丧失风险较高相关[95%置信区间分别为1.06(1.05-),分别为1.05(1.04-1.06)、1.17(1.10-1.25)、1.07(1.01-1.13)和1.41(1.23-1.62)];少数民族、能连续步行1公里、独自乘坐公共交通工具以及几乎每天做家务与ADL能力丧失风险较低相关[95%置信区间分别为0.71(0.62-0.80)、0.72(0.65-0.80)、0.74(0.68-0.82)和0.69(0.64-0.74)]。模型的AUC值为0.853,校准曲线显示预测概率与观察概率高度一致。排除非干预因素(年龄、性别和种族)后,预测ADL能力丧失风险模型的AUC值为0.779。65-74岁和75岁及以上人群的AUC值分别为0.634和0.765。基于IADL中能连续步行1公里和独自乘坐公共交通工具的模型以及基于IADL综合评分的模型的AUC值分别为0.853和0.851。本研究建立的ADL能力丧失风险预测模型具有良好的性能和稳健性。

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