Comparison of UDSNB 3.0 normative data with those developed in a diverse community cohort of older adults: Results from the Einstein Aging Study

AbstractBackgroundNormative data for the Uniform Data Set, Version 3 Neuropsychological Battery (UDSNB3.0), from the database of the University of Washington’s National Alzheimer’s Coordinating Center (NACC), are limited by an overrepresentation of white, female, and highly‐educated older adults. Original norms, based on >3000 cognitively normal participants from US Alzheimer’s Disease Centers (ADCs), did not divide the sample by race/ethnicity as the sample is 83% White (Weintraub et al., 2018). In the current study, we compare the originally reported UDS norms with those derived from a systematically‐recruited, community‐residing, racially/ethnically diverse cohort of older adults and provide expanded norms for Black‐Americans and Whites.MethodsThe Einstein Aging Study (EAS) is a longitudinal cohort of racially/ethnically diverse community‐dwelling individuals, ≥ age 70, who reside in the Bronx, NY. Analyses include data from 225 cognitively normal EAS participants and 1759 cognitively normal participants ≥ age 70 from the NACC database. Descriptive statistics are in Table 1. Linear regression models were used to examine the effects of demographic factors—including sex, age, education, and further including race—on UDSNB3.0 test performance in the two samples and to develop demographically adjusted z‐scores for the EAS cohort.ResultsIn both EAS and NACC samples, higher scores were observed for those with more years of education. Both samples demonstrated lower scores for non‐Hispanic Blacks and other racial/ethnic groups compared to non‐Hispanic Whites (Table 2). After accounting for sex, age, education, and race, mean performance was lower in the EAS sample compared to that of NACC across neurocognitive domains, including memory, visuospatial skills, attention, language, processing speed, and executive function (Tables 3‐4).ConclusionRacial differences in UDSNB3.0 tests were observed in both EAS and NACC samples. These differences between the UDSNB 3.0 normative data and the EAS sample, after adjusting for age, sex, education, and race, suggest that normative data from samples of optimally healthy, well‐educated individuals are not generalizable to those in diverse, urban communities. Furthermore, results suggest a need for local norms for community‐dwelling, racially/ethnically diverse cohorts to improve diagnostic accuracy and the ability to distinguish cognitive impairment from healthy cognitive aging.