多维度失能测度指标体系构建及失能分级研究

以ICF理论框架的交互影响理念为依据,从多维度视角构建了失能测度指标体系。首先,通过赋值法,得到多维度下的失能总分,依据得分将其划分为重度失能、偏重度失能、中度失能、轻度失能及健康五种功能状态,构造死亡概率模型及失能状态转移概率模型,结果显示,失能分级标准是可靠的。其次,利用CLHLS数据库2011年及2014年追踪调查数据,通过构造多状态转移概率矩阵,实证测算了多状态失能转移概率;借助第六次全国人口普查数据,估算了中国65岁及以上失能人口规模、各状态维持时间及预期寿命等。结果显示,初始健康的老人三年期转移概率维持在健康的概率最高,其死亡率也最低;而初始状态为重度失能的老人死亡率最高,其维持重度失能及转移到偏重度等失能状态的概率也最高。研究结论表明,直接依据数据的失能状态转移概率测算比建模估计要准确;基于多状态转移概率矩阵评估的失能规模、预期寿命等均比已有分级测度结果可靠性更高。

Construction of Multi-dimensional Disability Measurement Index System and Disability Classification

Based on the interaction concept of ICF theoretical framework,this study constructs a disability measurement index system from a multi-dimensional perspective.First of all,we get the total score of disability in multi-dimension by assignment method.According to the score,it was divided into five functional states:severe disability,partial disability,moderate disability,mild disability and health.At the same time,we construct death probability model and disability state transition probability model,and the results show that the disability classification standard is reliable.Secondly,we use the tracking survey data of 2011 and 2014 in CLHLS database to empirically measure the transition probability of multi state disability by constructing the multi-state transition probability matrix.With the data of the sixth national census,we estimate the scale of disabled population aged 65 and above,and the maintenance time of each state and life expectancy.The results show that the three-year transfer probability of the initial healthy elderly is the highest,and the mortality rate is the lowest;while the mortality rate of the elderly with severe disability is the highest,and the probability of maintaining severe disability and transferring to the disabled state of overweight degree is also the highest.In addition,the conclusion of this study shows that the estimation of the disabled state transition probability based on the data is more accurate than the modeling estimation;the failure scale and life expectancy based on the multi state transition probability matrix evaluation are more reliable than the existing hierarchical measurement results.