大数据环境下老年人失能失智因素关联  

Correlative Factors about Elderly Disabled and Dementia in Big Data Environments

作　　者：李涵 李慧嘉[1] 张林姿 黄钰瑛 LI Han, LI Hui- jia ,ZHANG Lin -zi, HUANG Yu- ying(School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, Chin)

机构地区：[1]中央财经大学管理科学与工程学院,北京100081

出　　处：《计算机科学》2018年第B06期497-501,512,共6页Computer Science

摘　　要：近年来,老年人失能失智问题愈发普遍,不断增加的老年失能失智人口在为家庭和政府带来沉重养老负担的同时,也引发了社会公众的广泛关注。老年人年龄增长、状态和控制能力调查(ASOC)是通过1995年-2001年每隔3年连续调查美国老年人健康方面的问题而得到的数据。利用ASOC的3轮调查数据,通过跟踪研究和大数据分析,尝试将能力、智力衰退与生活习惯、情绪发泄渠道等诸多因素相关联,全面考察老年人失能失智的影响因素。在描述性统计的基础上,通过Logistic回归并去除关联性强的因素发现,年龄、性别、抽烟、饮酒、运动、心脏病、关节炎/风湿病、参与社区服务8个因素与老年人失能有较强的相关性,年龄、饮酒、高血压、参与社区服务、婚姻状况5个因素与老年人失智显著相关。借助本研究成果,可以对老年人的日常行为、生活习惯、健康状况等进行评价,找出其失能失智的潜在风险,从而指导家庭和养老服务机构等采取相应的措施以规避风险,为改善老年人的健康状况、提高生活质量和延长生命周期提供参考依据。Recently,with the deepening of China＇s population aging problem,the rising family pension burden,government pressure and the decline of demographic dividend have gained wide attention.Aging,status,and sense of control（ASOC）is a continuous survey data about elderly＇s health in American which was conducted every three years from1995 to 2001.Using three waves of ASOC,we have found influential factors related to disability and dementia by logistic regression based on the descriptive statistical analysis.On the basis of the descriptive statistics,by Logistic regression and removing strong related factors,we discovered that age,gender,smoking,drinking,exercise,heart disease,arthritis/rheumatism,and participation in community service have strong correlation with the elderly disability.Age,drinking,hypertension,participation in community service and marital status are significantly related to dementia in the elderly.

关 键 词：老年人 失能 失智 大数据 关联 

分 类 号：C931[经济管理—管理学]