Objective: This study aims to evaluate the performance of a Chinese version of the Montreal Cognitive Assessment (MoCA) as a screener to detect mild cognitive impairment (MCI) and dementia from normal cognition in the monolingual Chinese-speaking immigrant population. Method: A cohort of 176 Chinese-speaking older adults from the National Alzheimer’s Coordinating Center Uniform Data Set is used for analysis. We explore the impact of demographic variables on MoCA performance and calculate the optimal cutoffs for the detection of MCI and dementia from normal cognition with appropriate demographic adjustment. Results: MoCA performance is predicted by age and education independent of clinical diagnoses, but not by sex, years of living in the U.S., or primary Chinese dialect spoken (i.e., Mandarin vs. Cantonese). With adjustment and stratification for education and age, we identify optimal cutoff scores to detect MCI and dementia, respectively, in this population. These optimal cutoff scores are different from the established scores for non-Chinese-speaking populations residing in the U.S. Conclusions: Our findings suggest that the Chinese version of MoCA is a valid screener to detect cognitive decline in older Chinese-speaking immigrants in the U.S. They also highlight the need for population-based cutoff scores with appropriate considerations for demographic variables.

目的: 本研究旨在评估中文版蒙特利尔认知评估 (MoCA) 作为筛查工具的性能，以检测单语中文移民人群中正常认知的轻度认知障碍 (MCI) 和痴呆症。方法：使用来自国家阿尔茨海默病协调中心统一数据集的 176 名说中文的老年人队列进行分析。我们探讨了人口统计变量对 MoCA 表现的影响，并计算了通过适当的人口统计调整从正常认知中检测 MCI 和痴呆症的最佳临界值。结果：MoCA 的表现由独立于临床诊断的年龄和教育来预测，而不是由性别、在美国生活的年限或主要的中国方言（即普通话与广东话）来预测。通过对教育和年龄的调整和分层，我们确定了最佳截止分数，以分别检测该人群中的 MCI 和痴呆症。这些最佳截止分数不同于居住在美国的非华语人群的既定分数结论：我们的研究结果表明，中文版的 MoCA 是检测美国年长华语移民认知能力下降的有效筛查工具 他们还强调需要适当考虑人口变量的基于人口的截止分数。