Department of Medicine, Albert Einstein College of Medicine, Bronx, NY.
Department of Medicine, Albert Einstein College of Medicine, Bronx, NY; Department of Neurology, Albert Einstein College of Medicine, Bronx, NY.
Arch Phys Med Rehabil. 2023 Feb;104(2):245-250. doi: 10.1016/j.apmr.2022.08.975. Epub 2022 Sep 13.
To examine whether falls are associated with longitudinal changes in different gait domains and onset of clinical gait abnormalities.
Longitudinal study.
General community.
Ambulatory older adults free of dementia (N=428; mean age, 77.8±6.4 years).
Not applicable.
Gait was assessed with a computerized walkway. Pace, rhythm, and variability (outcome measures) were derived from individual gait measures, using principal component analysis. Clinical gait abnormalities (neurologic, nonneurologic, mixed) were visually assessed by clinicians. Linear mixed-effects models were used to examine the associations between falls (the exposure variable coded as none, single, and multiple) and changes in gait domains. Multinomial logistic regression was used to examine associations between falls and the onset of clinical gait abnormalities. Models were adjusted for sex, education, age, body mass index, number of comorbidities, gait speed at the first follow-up, and time between the last fall and the first follow-up gait assessment.
Pace declined while rhythm and variability increased at a faster rate (P<.05) among 32 participants with multiple falls in the first year of follow-up compared with 299 participants with no falls. Risk for clinical gait abnormalities between those with no falls, a single fall, or multiple falls was not different.
Multiple falls predict future gait decline in multiple domains in aging. Interventions to prevent gait decline after multiple falls should be investigated.
研究跌倒是否与不同步态领域的纵向变化和临床步态异常的发生有关。
纵向研究。
一般社区。
无痴呆的活动老年人(N=428;平均年龄,77.8±6.4 岁)。
不适用。
步态使用计算机步道进行评估。通过主成分分析,从个体步态测量中得出步速、节奏和变异性(观察指标)。临床步态异常(神经、非神经、混合)由临床医生进行视觉评估。线性混合效应模型用于检查跌倒(暴露变量编码为无、单次和多次)与步态领域变化之间的关系。使用多项逻辑回归检查跌倒与临床步态异常发生之间的关联。模型调整了性别、教育、年龄、体重指数、共病数量、首次随访时的步态速度以及最后一次跌倒和首次随访步态评估之间的时间。
在随访的第一年中,与 299 名无跌倒的参与者相比,32 名多次跌倒的参与者的步速下降,而节奏和变异性的增加速度更快(P<.05)。无跌倒、单次跌倒或多次跌倒的参与者发生临床步态异常的风险无差异。
多次跌倒预示着衰老过程中多个步态领域的未来步态下降。应研究预防多次跌倒后步态下降的干预措施。