Duan Qi, Zhang Yinuo, Zhuang Weihao, Li Wenlong, He Jincai, Wang Zhen, Cheng Haoran
Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou 325000, China.
Brain Sci. 2023 Nov 17;13(11):1599. doi: 10.3390/brainsci13111599.
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder with cognitive dysfunction and behavioral impairment. We aimed to use principal components factor analysis to explore the association between gait domains and AD under single and dual-task gait assessments. METHODS: A total of 41 AD participants and 41 healthy control (HC) participants were enrolled in our study. Gait parameters were measured using the JiBuEn gait analysis system. The principal component method was used to conduct an orthogonal maximum variance rotation factor analysis of quantitative gait parameters. Multiple logistic regression was used to adjust for potential confounding or risk factors. RESULTS: Based on the factor analysis, three domains of gait performance were identified both in the free walk and counting backward assessments: "rhythm" domain, "pace" domain and "variability" domain. Compared with HC, we found that the pace factor was independently associated with AD in two gait assessments; the variability factor was independently associated with AD only in the counting backwards assessment; and a statistical difference still remained after adjusting for age, sex and education levels. CONCLUSIONS: Our findings indicate that gait domains may be used as an auxiliary diagnostic index for Alzheimer's disease.
Brain Sci. 2023-11-17
Front Hum Neurosci. 2023-12-19
Alzheimers Dement. 2019-9-20
Alzheimers Dement (Amst). 2020-8-25
Biomed Signal Process Control. 2021-2
Anesth Analg. 2021-2-1
Alzheimers Res Ther. 2020-5-6
Gait Posture. 2019-9-16
Alzheimers Dement. 2019-9-20
Gait Posture. 2019-8-12
J Alzheimers Dis. 2019