Background

While gait assessments are recommended to evaluate fall risk in older adults, these often involve walking in a straight line, even though one-third of steps taken throughout the day involve turning. Falls that occur during a turn tend to be more serious than falls that occur during a straight walk, but little is known about how gait variables collected during a turn can predict falls.

Research question

How do gait characteristics collected from straight and turning walking phases predict falls in older adults?

Methods

We prospectively examined the association between six quantitative gait variables measured during normal walking turn and straight walking phases as predictors of incident falls in a community-based sample of older adults (N = 253; mean age 78.5; 51% women). Cox regressions adjusted for multiple potential confounders were used to examine the associations.

Results

Participants had significantly slower stride velocity (57.81 vs 83.26 cm/s), shorter stride length (74.76 vs 101.81 cm,), lower swing (30.1 vs 32.41%), higher double support (39.79 vs 35.19%), and more swing (30.09 vs 32.41%) and stride length variability (31.86 vs 6.35 %) during turns compared with straights. Higher swing percent in both turns (adjusted hazard ratio; HR 0.92, 95% CI 0.87, 0.97) and straights (HR 0.89, 95% CI 0.84, 0.96) was associated with reduced risk of falls. Higher double support percent during both turns (HR 1.04, 95% CI 1.01, 1.07) and straights (HR 1.06, 95% CI 1.02, 1.09) was associated with increased risk of falls. More swing variability during turns (HR 1.03, 95% CI 1.00, 1.06), but not straights, was associated with increased risk of falls.

Significance

Gait variables collected during turning and walking straight were similar in their predictions of future falls. In the future, clinical research that builds on these findings could improve identification and prevention of falls.

中文翻译：

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将转弯和笔直行走阶段作为事故预测指标的比较。

背景

尽管建议通过步态评估来评估老年人的跌倒风险，但尽管整天采取的步骤中有三分之一涉及转弯，但这些评估通常都涉及直线行走。转弯时发生的跌倒比直走时发生的跌倒更严重，但对于转弯期间收集的步态变量如何预测跌倒的知之甚少。

研究问题

从笔直和转弯步行阶段收集的步态特征如何预测老年人的跌倒？

方法

我们前瞻性地检查了在正常的步行转弯和笔直的步行阶段中测得的六个定量步态变量之间的关联，因为该事件的预测因素落在社区为基础的老年人样本中（N  = 253；平均年龄78.5； 51％的女性）。使用针对多个潜在混杂因素进行调整的Cox回归来检查关联。

结果

参与者的步速显着降低（57.81 vs.83.26 cm / s），步幅较短（74.76 vs 101.81 cm），较低的挥杆（30.1 vs 32.41％），较高的双支撑（39.79 vs 35.19％）和较高的挥杆（30.09 vs. 32.41％）和转弯时的步长变化（31.86 vs 6.35％）。转弯（调整后的危险比； HR 0.92，95％CI 0.87，0.97）和直道（HR 0.89，95％CI 0.84，0.96）中较高的挥杆百分比与降低跌倒风险相关。两次转弯（HR 1.04，95％CI 1.01，1.07）和直道（HR 1.06，95％CI 1.02，1.09）较高的双支撑率与跌倒风险增加相关。转弯时挥杆变化性更大（HR 1.03，95％CI 1.00，1.06），但不直，则与摔倒风险增加相关。

意义

在转弯和直行期间收集的步态变量在对未来跌倒的预测中相似。将来，基于这些发现的临床研究可以改善跌倒的识别和预防。