Ong Reuben, Yap Chun Wei, Ge Lixia
Health Services & Outcomes Research, National Healthcare Group, 1 Mandalay Rd, Singapore, 308205, Singapore.
Sci Rep. 2025 May 23;15(1):17895. doi: 10.1038/s41598-025-03167-5.
This study aimed to calculate stratified normative scores of the Montreal Cognitive Assessment (MoCA) in an adult population in Singapore, accounting for key demographic influences. Demographic data and MoCA scores of 1,103 healthy adults (aged 21 to 97) were obtained from a community health study conducted in central Singapore. Factors associated with MoCA scores were identified using multiple linear regression and β coefficients were used to estimate normative MoCA scores across strata. Model performance was assessed using five-fold cross-validation. Normative reference scores were calculated and stratified by age group, education level, and ethnicity to reflect typical MoCA performance across demographic groups. The final regression model had an adjusted R of 0.284 (p < 0.001), with age group (β = -0.325 to -2.312) and education level (β = 1.783 to 4.206) accounting for the majority of the explained variance (R = 0.271). Ethnicity also remained a significant factor in the model, with lower scores observed among Malay (β = -1.248) and Indian (β =-0.795) participants compared to Chinese. Among the 64 demographic combinations of age group, education level and ethnicity, the lowest normative score (20.0) was derived for Malay individuals aged ≥ 75 years with no formal education. MoCA scores varied systematically with age, education level, and ethnicity in the study population. The resulting stratified reference scores provide clinicians and researchers a useful context for interpreting individual MoCA performance relative to demographically similar peers in Singapore's adult population. However, these reference scores are not diagnostic thresholds and should be interpreted with caution until validated against clinically diagnosed cognitive impairment.
本研究旨在计算新加坡成年人群中蒙特利尔认知评估量表（MoCA）的分层常模分数，并考虑关键人口统计学因素的影响。从新加坡中部开展的一项社区健康研究中获取了1103名健康成年人（年龄在21岁至97岁之间）的人口统计学数据和MoCA分数。使用多元线性回归确定与MoCA分数相关的因素，并使用β系数估计各分层的MoCA常模分数。通过五折交叉验证评估模型性能。计算常模参考分数，并按年龄组、教育水平和种族进行分层，以反映不同人口群体的典型MoCA表现。最终回归模型的调整后R值为0.284（p < 0.001），年龄组（β = -0.325至-2.312）和教育水平（β = 1.783至4.206）解释了大部分变异（R = 0.271）。种族在模型中也是一个显著因素，与华裔参与者相比，马来族（β = -1.248）和印度族（β = -0.795）参与者的分数较低。在年龄组、教育水平和种族的64种人口统计学组合中，未接受过正规教育的75岁及以上马来族个体的常模分数最低（20.0）。在研究人群中，MoCA分数随年龄、教育水平和种族而系统性变化。所得的分层参考分数为临床医生和研究人员提供了一个有用的背景，以便在新加坡成年人群中相对于人口统计学上相似的同龄人解释个体的MoCA表现。然而，这些参考分数并非诊断阈值，在与临床诊断的认知障碍进行验证之前应谨慎解释。
