Michel Emeline, Zory Raphael, Guerin Olivier, Prate Frederic, Sacco Guillaume, Chorin Fréderic
Department of Geriatric Medicine, Université Côte d'Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique de Soins Ambulatoires, 06003, Nice, France.
Université Côte d'Azur, LAMHESS, Nice, France.
Eur Geriatr Med. 2024 Oct;15(5):1301-1311. doi: 10.1007/s41999-024-01020-y. Epub 2024 Aug 3.
Falling is an important public health issue because of its prevalence and severe consequences. Evaluating muscle performance is important when assessing fall risk. The study aimed to identify factors [namely muscle capacity (strength, quality, and power) and spatio-temporal gait attributes] that best discriminate between fallers and non-fallers in older adults. The hypothesis is that muscle quality, defined as the ratio of muscle strength to muscle mass, is the best predictor of fall risk.
184 patients were included, 81% (n = 150) were women and the mean age was 73.6 ± 6.83 years. We compared body composition, mean grip strength, spatio-temporal parameters, and muscle capacity of fallers and non-fallers. Muscle quality was calculated as the ratio of maximum strength to fat-free mass. Mean handgrip and power were also controlled by fat-free mass. We performed univariate analysis, logistic regression, and ROC curves.
The falling patients had lower muscle quality, muscle mass-controlled power, and mean weighted handgrip than the non-faller. Results showing that lower muscle quality increases fall risk (effect size = 0.891). Logistic regression confirmed muscle quality as a significant predictor (p < .001, OR = 0.82, CI [0.74; 0.89]). ROC curves demonstrated muscle quality as the most predictive factor of falling (AUC = 0.794).
This retrospective study showed that muscle quality is the best predictor of fall risk, above spatial and temporal gait parameters. Our results underscore muscle quality as a clinically meaningful assessment and may be a useful complement to other assessments for fall prevention in the aging population.
跌倒因其普遍性和严重后果，是一个重要的公共卫生问题。在评估跌倒风险时，评估肌肉功能很重要。本研究旨在确定能最佳区分老年人跌倒者和非跌倒者的因素（即肌肉能力[力量、质量和功率]以及时空步态属性）。假设是，肌肉质量（定义为肌肉力量与肌肉质量之比）是跌倒风险的最佳预测指标。
纳入184例患者，其中81%（n = 150）为女性，平均年龄为73.6 ± 6.83岁。我们比较了跌倒者和非跌倒者的身体成分、平均握力、时空参数和肌肉能力。肌肉质量计算为最大力量与去脂体重之比。平均握力和功率也通过去脂体重进行校正。我们进行了单因素分析、逻辑回归和ROC曲线分析。
跌倒患者的肌肉质量、肌肉质量校正后的功率和平均加权握力均低于非跌倒者。结果表明，较低的肌肉质量会增加跌倒风险（效应量 = 0.891）。逻辑回归证实肌肉质量是一个显著的预测指标（p <.001，OR = 0.82，CI [0.74; 0.89]）。ROC曲线表明肌肉质量是跌倒的最具预测性的因素（AUC = 0.794）。
这项回顾性研究表明，肌肉质量是跌倒风险的最佳预测指标，优于空间和时间步态参数。我们的结果强调了肌肉质量作为一项具有临床意义的评估指标，可能是老年人群跌倒预防其他评估的有用补充。
