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分解日常生活活动受限情况以预测养老院入住率。

Disaggregating activities of daily living limitations for predicting nursing home admission.

作者信息

Fong Joelle H, Mitchell Olivia S, Koh Benedict S K

机构信息

SIM University, 461 Clementi Road, Singapore, 599491.

出版信息

Health Serv Res. 2015 Apr;50(2):560-78. doi: 10.1111/1475-6773.12235. Epub 2014 Sep 26.

Abstract

OBJECTIVE

To examine whether disaggregated activities of daily living (ADL) limitations better predict the risk of nursing home admission compared to conventionally used ADL disability counts.

DATA SOURCES

We used panel data from the Health and Retirement Study (HRS) for years 1998-2010. The HRS is a nationally representative survey of adults older than 50 years (n = 18,801).

STUDY DESIGN

We fitted Cox regressions in a continuous time survival model with age at first nursing home admission as the outcome. Time-varying ADL disability types were the key explanatory variables.

PRINCIPAL FINDINGS

Of the six ADL limitations, bathing difficulty emerged as the strongest predictor of subsequent nursing home placement across cohorts. Eating and dressing limitations were also influential in driving admissions among more recent cohorts. Using simple ADL counts for analysis yielded similar adjusted R(2) s; however, the amount of explained variance doubled when we allowed the ADL disability measures to time-vary rather than remain static.

CONCLUSIONS

Looking beyond simple ADL counts can provide health professionals insights into which specific disability types trigger long-term nursing home use. Functional disabilities measured closer in time carry more prognostic power than static measures.

摘要

目的

与传统使用的日常生活活动(ADL)残疾计数相比,研究分解后的日常生活活动受限情况是否能更好地预测入住养老院的风险。

数据来源

我们使用了1998 - 2010年健康与退休研究(HRS)的面板数据。HRS是一项针对50岁以上成年人的全国代表性调查(n = 18,801)。

研究设计

我们在一个连续时间生存模型中拟合了Cox回归,将首次入住养老院的年龄作为结果。随时间变化的ADL残疾类型是关键解释变量。

主要发现

在六种ADL受限情况中,洗澡困难是各队列中后续入住养老院最强的预测因素。进食和穿衣受限在近期队列的入住情况中也有影响。使用简单的ADL计数进行分析得到了相似的调整后R²;然而,当我们允许ADL残疾测量随时间变化而非保持不变时,解释的方差量增加了一倍。

结论

超越简单的ADL计数可以让健康专业人员了解哪些特定的残疾类型会引发长期入住养老院。与静态测量相比,更接近时间测量的功能残疾具有更强的预后能力。

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