Abnormal driving behavior becomes a new warning signal for Alzheimer's disease: Multi-source data synthesis and analysis

Runxuan TANG; Junzhi LI; Yiting HAO; Xinran ZHANG; Ying ZHANG

doi:10.3969/j.issn.2096-5516.2025.05.002

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Chinese Journal of Alzheimer's Disease and Related Disorders ›› 2025, Vol. 8 ›› Issue (5) : 297-303. DOI: 10.3969/j.issn.2096-5516.2025.05.002

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Abnormal driving behavior becomes a new warning signal for Alzheimer's disease: Multi-source data synthesis and analysis

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Abstract

Objective: To comprehensively evaluate the effectiveness of driving ability as a predictor for Alzheimer's disease (AD), explore relevant data collection and analysis methods, and identify valid early warning indicators. Methods: Computerized searches were conducted in databases including CNKI, CBM, Wanfang, VIP, PubMed, and Web of Science to identify studies using driving ability for AD prediction. Literature meeting inclusion criteria was screened, and data quality was assessed. Relevant information was extracted, and heterogeneous data were integrated. Principal component analysis (PCA) was used to evaluate the importance of indicators in the driving-based warning system. Meta-analysis was performed to assess the effect of AD on driving ability. Subgroup analysis was conducted to reduce intergroup heterogeneity, with stratification based on age, gender, and Mini-Mental State Examination (MMSE) scores to examine differences in effects across groups. A multifactorial interaction subgroup analysis was further proposed to minimize intergroup heterogeneity, analyzing the combined influence of age, gender, and MMSE scores on statistical outcomes. Results: After screening, 12 studies were included. PCA results identified the three most significant indicators: spatial control (9.13%), emotional adaptation (8.78%), and navigation execution (8.36%). Meta-analysis and subgroup analysis revealed that older female patients with low MMSE scores exhibited the most severe driving-related cognitive impairment (SMD = -0.75, P < 0.001). Additionally, among male AD patients, the high-score MMSE group showed a greater absolute effect size (ΔSMD = -0.22, P < 0.001). Multifactorial interaction subgroup analysis explained 78% of the heterogeneity (Q = 12.37, P = 0.006). Conclusion: This study provides preliminary evidence that abnormal driving behavior can serve as a novel biomarker for early AD detection, with spatial orientation, emotional stability, and navigation ability identified as core indicators. However, the warning system must account for population differences (higher sensitivity in older females) and individual baseline variations (longitudinal self-referencing).

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Data fusion / Abnormal driving behavior / Alzheimer’s disease / Cognitive impairment / Early warning signals

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Runxuan TANG , Junzhi LI , Yiting HAO , et al . Abnormal driving behavior becomes a new warning signal for Alzheimer's disease: Multi-source data synthesis and analysis[J]. Chinese Journal of Alzheimer's Disease and Related Disorders. 2025, 8(5): 297-303 https://doi.org/10.3969/j.issn.2096-5516.2025.05.002

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