The Montreal Cognitive Assessment (MoCA) is a popular screening tool for Mild Cognitive Impairment (MCI). The psychometric properties of the MoCA have not been widely examined in minority groups. We aimed to analyze the discriminate ability of subtests and items by race and ethnicity given gold-standard clinical diagnosis of cognitive status.
We analyzed data from the National Alzheimer Coordinating Center Uniform Data Set March 2018 data freeze. Stepwise regression was used to determine which subtests predicted cognitive status (normal cognition, MCI, or dementia), by race/ethnicity. Item discrimination and difficulty was calculated by race/ethnicity and cognitive status.
In our sample (n=3895), with an average age of 69.7, 80.7% were non-Hispanic white, 15.0% were non-Hispanic black, and 4.2% were Hispanic. Among non-Hispanic whites all subtests, education, and age predicted clinician diagnosis, while visuospatial/executive, attention, language, delayed recall, and orientation subtests were predictive among non-Hispanic blacks and visuospatial/executive, delayed recall, and orientation subtests and education were predictive among Hispanics. Item discrimination and difficulty varied by race/ethnicity and cognitive status.
By understanding the psychometric properties of MoCA subtests, we can focus on subtests that have higher discrimination and more diagnostic utility. Subtests should be further evaluated for use in screening of minority individuals.
*Sealy Center on Aging, University of Texas Medical Branch, Galveston, TX
†Department of Clinical and Health Psychology, College of Public Health and Health Professions
‡Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, FL
S.A.M. is currently funded through the training grant #T32AG000270 (PI Wong) from the National Institute on Aging/National Institutes of Health. She was also funded for a portion of this work through the Graduate School Fellowship at the University of Florida. M.M. and C.W.S. are partially funded by the 1Florida Alzheimer’s Disease Research Center, funded by the National Institute on Aging, P50 AG047266 (PI Todd Golde, MD, PhD). The NACC database is funded by the National Institute on Aging/National Institutes of Health Grant U01 AG016976. NACC data are contributed by the National Institute on Aging -funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Thomas Wisniewski, MD), P30 AG013854 (PI M. Marsel Mesulam, MD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD, MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P50 AG005131 (PI James Brewer, MD, PhD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG053760 (PI Henry Paulson, MD, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P30 AG049638 (PI Suzanne Craft, PhD), P50 AG005136 (PI Thomas Grabowski, MD), P50 AG033514 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PI John Morris, MD), P50 AG047270 (PI Stephen Strittmatter, MD, PhD).
The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The authors declare no conflicts of interest.
Reprints: Sadaf Arefi Milani, PhD, MPH, Sealy Center on Aging, The University of Texas Medical Branch, 301 University Blvd, Galveston, TX 77555-0177 (e-mail: email@example.com).
Received January 22, 2019
Accepted March 20, 2019