BACKGROUND Assessing the risk of disability in older adults is important for developing prevention and intervention strategies to decrease potential disability and dependency. The aim of this study was to examine the association between spatio-temporal gait variables and disability among older adults. METHODS We conducted a prospective study in a community setting. We collected data from 4121 subjects (≥ 65 years, mean age: 71.9 years). Gait speed, cadence, stride length, and stride length variability were measured at baseline. Participants were instructed to walk at their usual pace along a 6.4 m straight and flat path on which an electronic gait measuring device was mounted at mid 2.4 m. Subsequent disability was confirmed from long-term care insurance records. RESULTS During follow-up duration (mean: 49.6 months), 425 participants had incident disability. The cut-off value to detect high or low function in each gait variable was determined using the Youden index. Cox proportional hazard analysis adjusted for covariates showed that disability was significantly predicted by low function in each gait variable using the cut-off values: gait speed (hazard ratio [95% confidential intervals]: 2.06 [1.65-2.57]), stride length (2.17 [1.72-2.73]), cadence (1.49 [1.20-1.86], and stride length variability (1.46 [1.19-1.80]). The number of gait variables that scored in the low function category were also cumulatively related to subsequent disability (p < .001). CONCLUSIONS This study revealed that spatio-temporal gait variables had a significant predictive value for incident disability. Multifaceted and quantitative gait analysis can contribute to disability risk assessment.

中文翻译：

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时空步态变量预测事件残疾。

背景技术评估老年人的残疾风险对于制定预防和干预策略以减少潜在的残疾和依赖性很重要。这项研究的目的是检查时空步态变量和老年人之间的残疾之间的关联。方法我们在社区环境中进行了前瞻性研究。我们收集了来自4121名受试者（≥65岁，平均年龄：71.9岁）的数据。在基线测量步态速度，节奏，步幅和步幅变异性。指示参与者按照通常的步伐沿着6.4 m平坦且平坦的路径行走，并在2.4 m中部安装了电子步态测量装置。随后的残疾从长期护理保险记录中确认。结果在随访期间（平均：49.6个月），425名参与者有事故残疾。使用Youden指数确定检测每个步态变量中高低功能的临界值。校正协变量的Cox比例风险分析表明，使用以下临界值对每个步态变量的低功能进行了显着预测：步态速度（危险比[95％机密间隔]：2.06 [1.65-2.57]），步幅（ 2.17 [1.72-2.73]），节奏（1.49 [1.20-1.86]和步幅可变性（1.46 [1.19-1.80]）。在低功能类别中得分的步态变量数量也与随后的残疾相关（ p <.001）。结论这项研究表明，时空步态变量对事件残疾具有重要的预测价值。