Prediction of mild cognitive impairment in elderly patients with type 2 diabetes mellitus by walking speed combined with life-space mobility
10.3760/cma.j.cn115682-20230907-00947
- VernacularTitle:步速联合生活空间移动性在老年2型糖尿病患者轻度认知障碍中的预测作用
- Author:
Haiyan ZHANG
1
;
Weihua YU
;
Li ZHANG
;
Man DENG
;
Yuxi ZHANG
;
Xia YANG
Author Information
1. 安徽医科大学护理学院，合肥 230032
- Keywords:
Diabetes mellitus, type 2;
Cognitive function;
Mild cognitive impairment;
The elderly in the community;
Walking speed;
Life-space mobility
- From:
Chinese Journal of Modern Nursing
2024;30(12):1567-1574
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the relationship between walking speed, life-space mobility (LSM), cognitive function and mild cognitive impairment (MCI) in elderly patients with type 2 diabetes mellitus in community, and compare the predictive value of walking speed and LSM alone and combined in elderly patients with type 2 diabetes mellitus.Methods:This was a cross-sectional study. Using the convenient sampling method, a total of 448 elderly patients with type 2 diabetes mellitus from three communities in Hefei City were selected as the research objects from September 2022 to May 2023. Daily walking speed was measured using the 4-Meter Walking Speed, LSM was assessed using the Chinese version of Life-Space Assessment (LSA), and cognitive function was evaluated using the Chinese version of Montreal Cognitive Assessment (MoCA). Participants were divided to the MCI group and non-MCI group. Spearman correlation analysis was used to explore the relationships between walking speed, LSM and cognitive function. Logistic regression analysis was used to analyze the relationship between walking speed, LSM and MCI. Area under the curve ( AUC) of receiver operating characteristic (ROC) curve analysis was performed to compare the effects of walking speed and Chinese version LSA score on the prediction of MCI alone and in combination. Results:The walking speed and the Chinese version LSA score were both positively correlated with the Chinese version MoCA score ( r=0.598, 0.543; P<0.05). Chinese version LSA score ( OR=0.942) and walking speed score ( OR=0.490) were influencing factors for MCI in elderly patients with type 2 diabetes mellitus ( P<0.05). The AUC for walking speed in predicting MCI was 0.875, with a cutoff value of 3 points. Chinese version LSA score in predicting MCI had an AUC of 0.887 with a cutoff value of 59 points. When used in combination, they achieved an AUC of 0.915, with cutoff values of 55 points for Chinese version LSA scores and 3 points for walking speed scores. Conclusions:The combination of walking speed and LSM can more accurately predict the occurrence of MCI in elderly patients with type 2 diabetes mellitus than the single application, which provide a reference for improving the cognitive function of elderly patients with type 2 diabetes mellitus.
