Optimal cutoffs for the Montreal Cognitive Assessment vary by race and ethnicity

Sadaf Arefi Milani, Michael Marsiske, Linda B. Cottler, Xinguang Chen, Catherine W. Striley

Research output: Contribution to journalArticlepeer-review

169 Scopus citations

Abstract

Introduction: The Montreal Cognitive Assessment (MoCA), scored from 0 to 30, is used as a screening tool for mild cognitive impairment (MCI). The current cutoff (26) may not be optimal among minorities. Methods: Data from the National Alzheimer's Coordinating Center Uniform Data Set March 2018 data freeze was used to calculate optimal cutoffs for detection of MCI and dementia by race/ethnic group and education. Results: Of the 3895 individuals included, 80.7% were non-Hispanic White, 15.0% were non-Hispanic Black, and 4.2% were Hispanic. Optimal cutoffs for detection of MCI were 25 among non-Hispanic Whites, 24 among Hispanics, and 23 among non-Hispanic Blacks. Optimal cutoffs for detection of dementia were 19 among non-Hispanic Whites and 16 for both non-Hispanic Blacks and Hispanics. Lower educational attainment produced lower optimal cutoffs. Discussion: Our findings suggest cutoffs may need to be stratified by race/ethnicity and education to ensure detecting MCI from normal and MCI from dementia.

Original languageEnglish (US)
Pages (from-to)773-781
Number of pages9
JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume10
DOIs
StatePublished - 2018
Externally publishedYes

Keywords

  • Alzheimer's disease
  • Dementia
  • Disparities
  • Education
  • Ethnicity
  • Montreal Cognitive Assessment
  • Race
  • Screening

ASJC Scopus subject areas

  • Clinical Neurology
  • Psychiatry and Mental health

Fingerprint

Dive into the research topics of 'Optimal cutoffs for the Montreal Cognitive Assessment vary by race and ethnicity'. Together they form a unique fingerprint.

Cite this