Identification of Fall Risk Predictors in Daily Life Measurements: Gait Characteristics' Reliability and Association With Self-reported Fall History
Identification of Fall Risk Predictors in Daily Life Measurements: Gait Characteristics' Reliability and Association With Self-reported Fall History
复制标题
DOI：
10.1177/1545968314532031
复制
发表时间：
2015-01-01
影响因子：
4.2
通讯作者：
van Dieen, Jaap H.
中科院分区：
文献类型：
--
作者：
Rispens, Sietse M.;van Schooten, Kimberley S.;van Dieen, Jaap H.
背景在日常生活运动过程中从躯干加速度中提取的步态特征是对基于问卷或实验室的步态和平衡评估的补充，可能有助于改善跌倒风险预测。Objective.本研究的目的是确定与自我报告的跌倒史相关的步态特征，并根据一周内收集的动态数据进行可靠评估。方法.我们分析了在113名老年人（年龄范围，65-97岁）中收集的2周躯干加速度数据（DynaPort MoveMonitor，McRoberts）。在运动的情节，各种步态特征进行了测定，包括局部动态稳定性，跨变异性，和几个光谱特征。对于每个特征，我们进行了负二项回归分析，结果是参与者在前一年自我报告的福尔斯次数。步态特征的可靠性进行了评估两个测量周之间的组内相关性。结果沿垂直轴和前后轴沿着低于0.7 Hz和沿中侧轴低于沿着10 Hz的频谱功率百分比，以及局部动态稳定性、每步局部动态稳定性、步态平滑性和沿垂直轴的主频率沿着的振幅和斜率，与前一年的福尔斯次数相关，可以可靠地评估（所有P <0.05，组内相关性> 0.75）。结论.日常生活步态特征与老年人的跌倒史相关，可以通过一周的行走躯干加速度测量可靠地估计。
Background. Gait characteristics extracted from trunk accelerations during daily life locomotion are complementary to questionnaire- or laboratory-based gait and balance assessments and may help to improve fall risk prediction. Objective. The aim of this study was to identify gait characteristics that are associated with self-reported fall history and that can be reliably assessed based on ambulatory data collected during a single week. Methods. We analyzed 2 weeks of trunk acceleration data (DynaPort MoveMonitor, McRoberts) collected among 113 older adults (age range, 65-97 years). During episodes of locomotion, various gait characteristics were determined, including local dynamic stability, interstride variability, and several spectral features. For each characteristic, we performed a negative binomial regression analysis with the participants' self-reported number of falls in the preceding year as outcome. Reliability of gait characteristics was assessed in terms of intraclass correlations between both measurement weeks. Results. The percentages of spectral power below 0.7 Hz along the vertical and anteroposterior axes and below 10 Hz along the mediolateral axis, as well as local dynamic stability, local dynamic stability per stride, gait smoothness, and the amplitude and slope of the dominant frequency along the vertical axis, were associated with the number of falls in the preceding year and could be reliably assessed (all P < .05, intraclass correlation > 0.75). Conclusions. Daily life gait characteristics are associated with fall history in older adults and can be reliably estimated from a week of ambulatory trunk acceleration measurements.