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社区居住的有癌症病史的老年人跌倒。

Falls in the community-dwelling elderly with a history of cancer.

机构信息

College of Nursing, Michigan State University, East Lansing, Michigan 48824, USA.

出版信息

Cancer Nurs. 2010 Mar-Apr;33(2):149-55. doi: 10.1097/NCC.0b013e3181bbbe8a.

Abstract

BACKGROUND

Falls place older adults at risk for injuries, resulting in functional decline, hospitalization, institutionalization, higher healthcare costs, and decreased quality of life.

OBJECTIVE

This study examined community-dwelling elderly to identify if individuals with a history of cancer fall at a higher rate than those without cancer, and if the occurrence of falls was influenced by individual characteristics, symptoms, or function.

METHODS

This was a retrospective, cross-sectional study, in 2007, examining 7,448 community-dwelling elderly 65 years or older in a state in the Midwest. Fallers were identified based on a diagnosis of cancer, age, sex, race and ethnicity, poor vision, reduced activities of daily living (ADLs), instrumental ADLs, cognition, incontinence, pain, or depression.

RESULTS

Findings indicated that 2,125 (28.5%) had at least 1 fall. Of those who fell, 967 (13.0%) had cancer, and 363 (4.9%) with cancer had a fall.

CONCLUSION

Predictors of falls in this population included race, sex, ADLs, incontinence, depression, and pain, all with P <.05. Cancer was not a predictor of falls in this study.

IMPLICATIONS FOR PRACTICE

This study found a high frequency of falls and suggests a predictive model for fall risk in the vulnerable, community-dwelling elderly and will be used to inform future studies.

摘要

背景

老年人跌倒会增加受伤风险,导致功能下降、住院、住院治疗、医疗费用增加和生活质量下降。

目的

本研究旨在调查社区居住的老年人,以确定是否有癌症病史的个体跌倒率高于无癌症病史的个体,以及跌倒的发生是否受到个体特征、症状或功能的影响。

方法

这是一项 2007 年进行的回顾性、横断面研究,调查了中西部一个州的 7448 名 65 岁或以上的社区居住的老年人。根据癌症诊断、年龄、性别、种族和民族、视力不佳、日常生活活动(ADL)减少、辅助日常生活活动(IADL)、认知、尿失禁、疼痛或抑郁来确定跌倒者。

结果

结果表明,有 2125 人(28.5%)至少跌倒过一次。在跌倒的人中,有 967 人(13.0%)患有癌症,有 363 人(4.9%)患有癌症并有跌倒。

结论

本研究中,该人群跌倒的预测因素包括种族、性别、ADL、尿失禁、抑郁和疼痛,均 P <.05。癌症不是本研究中跌倒的预测因素。

实践意义

本研究发现跌倒频率较高,并提出了一个脆弱的、社区居住的老年人跌倒风险预测模型,将用于指导未来的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e763/4471335/3e9c6f58d0e6/nihms265569f1.jpg

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